Phase 1 Feasibility Full Report

Phase 1 FEASIBILITY STUDY FINAL REPORT BEIS | Domestic Demand Side Response Friday 27th July 2018 Public Version

2 CONTENTS

Public Description of the Project ...... 4 Executive Summary ...... 5 Aims and Objectives ...... 6 BEIS Competition ...... 6 The “FLATLINE” Proposal ...... 7 Technical Solution and Expected Performance ...... 8 Technical Feasibility Report Structure ...... 8 Performance information ...... 9 Legal & Regulatory Environment ...... 10 Legal Considerations ...... 10 Regulatory Considerations ...... 11 Technical Solution Methodology ...... 12 Pilot Site ...... 13 Establishing Energy Demand ...... 13 Technical Solution Analysis ...... 19 Sequential Analysis of Homes ...... 19 Control System Flexibility ...... 27 FLATLINE – The Next Evolution...... 29 Systems Analysis ...... 30 Existing Control Systems ...... 30 User Interface ...... 31 Connecting the System ...... 32 System Control (All Devices) ...... 33 Data Exchange/Processing & Storage ...... 34 System Redundancy ...... 34 Cyber Security ...... 34 Internet Connectivity ...... 36 Construction & Post Occupancy ...... 37 Construction Requirements ...... 37 Innovation and Technology Readiness ...... 40 Market Potential and Exploitation Plans ...... 41 Overview of DSR Revenues ...... 41 Capacity Market ...... 42 Network & Policy Charges ...... 42 Wholesale Market ...... 43 Balancing Services ...... 43 Capital Costs...... 44 Conclusions ...... 45 Uk & International Market Size and Job Creation ...... 48 Conclusions & Next Steps ...... 49 Key Recommendations ...... 49 Wider Conclusions ...... 49 Appendix A The FLATLINE Project Partners & Associates ...... 50 Appendix B Estimating overall energy demand for dwellings at the site ...... 56 Appendix C Estimating energy generation for the site ...... 70 Appendix D System descriptions ...... 88 Appendix E FLATLINE "Control Logic" ...... 89 Appendix F Sensors & Monitoring Supporting Information ...... 91 Appendix G Device level security for Samsung appliances ...... 93

Appendix H All BEIS Funded “Feasibility” Phase projects: ...... 96

4 PUBLIC DESCRIPTION OF THE PROJECT Sero Homes are collaborating with BRE, Minus 7, Samsung and sonnen to deliver the FLATLINE project: Fixed Level Affordable Tariffs Led by Intelligently Networked Energy, in response to a competition from UK Government. The FLATLINE project will deliver typical domestic energy consumers with set price heat and power fuel bills through an innovative integration and management structure between the collaborators’ systems. Stable monthly bills will be possible by using a combination of domestic Demand Side Response and demand shifting (for both heat and electricity) across networked districts of homes, operating to control domestic appliances, heating, photovoltaic generations and battery storage in combination. In aggregate across the homes, the energy load will be managed between generation, supply and demand times as well as energy forms, with the goal of achieving a flat line energy demand placed on the Distribution Network Operator and better value to the consumer. The project is divided into two phases. The completed feasibility phase of FLATLINE has undertaken detailed investigations, modelling and prototyping in order to demonstrate that there is a viable business model that can deliver these FLATLINE goals of very low, fixed bills to occupants whilst providing domestic Demand Side Response services to the Grid. The extensive work has included the systems architecture for the management platform, occupant user interfaces, cyber security, underpinning business model rates, legal and regulatory boundaries, and data storage and relevant data rights and protections. This feasibility has also undertaken a pilot site modelling of 58 homes, assessing their detailed energy demands and generation potential. The feasibility phase has demonstrated that there is a viable business model that can deliver the FLATLINE goals of very low, fixed bills to occupants whilst providing domestic Demand Side Response services to the Grid. The detailed modelling of the pilot site has demonstrated that, even when built to modern Building Regulations (EPC A or B), the site would have an annual fuel cost of £49,900 (electric and gas), which means an average monthly fuel cost per house of approximately £72, an energy demand that peaks with the worst times for National Grid impact. When modelled as FLATLINE homes, the pilot site has an annual fuel cost of £18,000 (all electric), a cost reduction of 64%, which equates to average monthly fuel cost per house of less than £26 before taking into account further dDSR income or management charges. This near-threefold reduction in forecast energy costs is also achieved with a practically complete avoidance of any impact on the National Grid at peak times. This FLATLINE phase 1 feasibility report concludes that there is a strong, viable and well-evidenced case to suggest that the FLATLINE project can deliver meaningful Domestic Demand Side Response services to the National Grid, whilst achieving very significant fuel bill reductions to residents, in an economically sustainable business model. The second phase of the project will be to construction a real demonstration, if the project is selected to proceed by UK’s Department of Business, Energy & Industrial Strategy, the competition sponsor. FLATLINE’s demonstration phase will then develop the management platform and implement the aggregated system on a c.50 new pilot homes in South Wales. These new low energy homes (themselves separately funded to already have heat pumps and photovoltaics) will be equipped with a live trial of the integrated FLATLINE system. The management system will then operate in passive “learn” mode for six months, before switching to full active “management” trial operation, when both performance data and occupant feedback will be collected to inform future progress and the wider potential of domestic demand side response in this format. The demonstration phase of FLATLINE will deliver a genuine real-world pilot of significant scale, providing a springboard to evidence the viability of this future “energy as service” business model. High level lessons, including around cyber security and qualitative occupancy feedback from the trials, will be disseminated to the wider industry to help support the wider awareness and understanding of the potential opportunities connected to a more intelligent, balanced and responsive energy network. This will be linked with the provision of a Data Repository database containing granular, interrogateable information to support future research and uptake (subject to personal and commercial data protection obligations).

5 EXECUTIVE SUMMARY This Phase 1 feasibility FLATLINE project report is a response to the Department for Business, Energy and Industrial Strategy’s competition for “Domestic Demand Side Response” (dDSR), and is written by project leaders Sero Homes with BRE, Minus 7, Samsung and sonnen, with further input from Smarter Lives, Cornwall Insight and Capital Law. The objective of this feasibility study was to demonstrate in detail that the project concept can be delivered. FLATLINE’s concept is that typical domestic energy consumers can benefit from very low, fixed price heat and power fuel bills; that this can be done whilst providing domestic Demand Side Response services to lessen the impact of those homes on the National Grid; and that this can be an economically viable business model without subsidy. This has been envisaged through using a low energy demand homes installed with renewable, low carbon and energy storage technologies, and by managing these homes through an advanced control network to intelligently draw, discharge and anticipate energy demands, whilst using this control to provide dDSR services to the Grid. Put simply, the FLATLINE concept proposes a win:win:win scenario – significantly lower bills to home occupants practically eliminating the risk of fuel poverty, electrical demands on the National Grid being shifted entirely ‘off peak’, and a new UK business model that can lead to growth at home and abroad (the model is internationally replicable). The work undertaken by the partners for this feasibility report has investigated this concept in considerable detail across a significant range of important topics. Briefly, this has comprised: • Piloting a ‘typical’ housing site (South Wales), to individually model 58 homes to forecast their fabric and occupant energy demands, and to predict their renewable energy generation potential, • Analysis of the communications network and system architecture that will be required to build and operate these homes, including reviewing cyber security and resilience, • Prototyping of the advanced control network required to manage FLATLINE system across the pilot homes in order to simulate the performance of this platform in operation, • Investigating the legal and regulatory barriers (or absence) for both current and reasonably anticipated future marketplaces, • Developing the detailed commercial understanding of the energy markets, their DSR opportunities and the likely prices/tariff scenarios currently and into the future. This report demonstrates that there is a viable business model that can deliver the FLATLINE goals of very low, fixed bills to occupants whilst providing domestic Demand Side Response services to the Grid. The investigations into the practicalities of legally and technically operating the FLATLINE model have found no insurmountable barriers, whilst the study of the system architecture has suggested a number of viable solutions for delivery. In parallel, work to understand the energy markets has illustrated pricing structures which are viable and underpin the pilot. Detailed modelling of the pilot site has demonstrated that, if built to modern Building Regulations as a baseline, the 58 homes would have an annual fuel cost of £49,900 (electric and gas). This represents the best of what is currently built in the UK at any scale since these “baseline” homes would achieve an Energy Performance Certificate of “A” or “B”, and would average monthly fuel cost per house of approximately £72. In terms of the energy networks, electricity demands for such a development coincide with the worst times for National Grid impact. When modelled as FLATLINE homes, the 58 properties are forecast to have an annual fuel cost of £18,000 (all electric), a cost reduction of 64%, which equates to average monthly fuel cost per house of less than £26, before taking into account further dDSR income or management charges. This is derived from initial prototype simulations demonstrating a reduction to £29,100, with identified anomalies quantified as a further saving of £11,100 of electricity. This near-threefold reduction in forecast energy costs is also achieved with a practically complete avoidance of impact on the National Grid at peak times (noting the current first prototype has some impact under the anomaly). The report shows that the project can offer significant ‘Demand Turn Up’ capacity (250-300kW) to the grid at the times it needs it most, whilst offering moderate ‘Reserve’ capacity due to the fact the homes are already turned down at peak times. This Phase 1 feasibility report therefore concludes that there is a strong, viable and well-evidenced case to suggest that the FLATLINE project can deliver meaningful Domestic Demand Site Response services to the National Grid, whilst achieving very significant fuel bill reductions to residents, in an economically sustainable business model.

6 AIMS AND OBJECTIVES BEIS COMPETITION

This report and the overall Phase 1 FLATLINE project is a response by the collaborating partners to a competition call from UK Government’s Department for Business, Energy and Industrial Strategy (BEIS) titled “Domestic Demand Side Response (DSR) Competition”. The competition provided for a first phase feasibility study, with selected projects being eligible for a second demonstration phase to be awarded towards the end of 2018. A synopsis of BEIS’s information on the competition comprises: The 2017 BEIS Rapid Evidence Assessment (REA)1 on ‘Realising the Potential of DSR to 2025’ ... concluded that successful DSR business models target high electricity load devices.... This represents an established source of shiftable load in the UK and tapping into a proportion of this load could secure significant flexibility. In addition ..., there are other areas that may see a rise in domestic consumption in the future which could increase the need and opportunities for DSR. For example, decarbonisation of heat could result in electrifying heating via heat pumps, and increased use of electric hot water heaters and cookers that will increase the electric load per home. .... In future, micro-CHP systems or fuel cells could also provide flexibility from households. The aim of this Competition is to identify and demonstrate controllable, flexible demand in real domestic environments which can be replicated at significant scale in identical or similar applications. The focus of the Competition is on identifying and testing novel usage of flexible demand which do not currently participate in DSR, largely using the application and integration of existing DSR and other IT or communication technologies - rather than on the development of new DSR consumer products such as ‘smart appliances’. ...Projects that demonstrate novel business models that engage consumers are also encouraged. The specific objectives for the Competition are: 1. Secure earlier and greater levels of deployment of DSR applications in domestic environments by delivering such DSR applications, each of which is ready to be rolled out to multiple other similar settings within 2 years of completion of the funded project. In turn, deployment of DSR is expected to enable the realisation of a number of system benefits, including: i. Deferral or avoidance of investment in network reinforcement; ii. Reduction in the need for a significant increase in reserve generation capacity; iii. Meeting of binding climate change targets with less low carbon generation; iv. Making the best use of our low carbon generation; v. Optimising the balancing of our energy system on a minute-by-minute basis. 2. Provide more detailed, robust data about the likely extent of and potential for DSR deployment in domestic environments in the UK and the savings which could be secured from domestic DSR in the UK. 3. Create greater awareness of the potential benefits and scope for deploying DSR among domestic users. 4. Create greater awareness of the potential benefits to be secured from Smart Meters among domestic users. 5. Implement potentially attractive business models for capacity-based services from the perspective of residential end-users who can adjust their energy consumption. 6. Strengthen UK supply chains for DSR applications and deployment. 7. Encourage collaboration and partnership between DSR users, technology developers and academic or other supply chain partners; help to involve supply chain partners in finding innovative solutions. In total, it is understood that 35 projects were awarded funding to investigate the feasibility of their proposed responses to the competition. From these submissions, BEIS can select which proposals may proceed to a second phase of the competition, which is intended to consist of demonstrating and testing of the proposed dDSR concept and disseminating the lessons learnt to communities with similar opportunities.

THE “FLATLINE” PROPOSAL

The project proposal (and therefore the subsequent evidence in this report) was for the feasibility of delivering typical domestic energy consumers with very low, fixed price heat and power fuel bills through an innovative integration and management structure between the collaborators’ systems, and to deliver this in an economically sustainable and viable business model that does not require ongoing subsidy. Fixed monthly bills were proposed as possible by using a combination of domestic Demand Side Response and demand shifting (for both heat and electricity) across networked districts of homes, operating to control domestic appliances, heating, photovoltaic generations and battery storage in combination. In aggregate across the homes, the energy load was proposed to be managed between generation, supply and demand times as well as energy forms, with the goal of achieving a flat line energy demand placed on the Distribution Network Operator and better value to the consumer. This was proposed as Fixed Level Affordable Tariffs Led by Intelligently Networked Energy: FLATLINE. Energy shifting between peak and off-peak half-hour periods is already rewarded to a basic extent by some utilities through basic static time-of-use tariffs (e.g. Green Energy UK). In 2015/16 Tempus energy offered low cost electricity in return for controlling residential appliance loads. Similarly, the 'energy-as-a-service' (EAAS) business model is not new, but has also yet to get traction in the UK. The FLATLINE innovation is to embed a demand response solution into an existing EAAS business model for domestic properties and thus include a property’s complete energy demand as a movable resource. A typical property uses significant heat and electricity each year, with peak loads occurring at the peak Grid demand times (and indeed largely responsible for them). Aggregating these loads in the domestic sector will therefore have a material impact on national demand once undertaken at scale, whilst for the Phase 2 Demonstrator project we propose to aggregate 50 homes in order to generate a meaningful trial dataset and evidence base. The future pricing structures and values of Grid services is likely to determine how the underpinning technologies are configured and in particular the energy storage capacity (i.e the more storage, the more demand can be shifted and the more solar energy can be stored). The exciting value proposition for FLATLINE is that these technologies (Minus7 heat/power and sonnen batteries) each has proven cost justifications individually. This dDSR capability is an additional value that is provided with a minimal incremental cost. Monetising this value would considerably boost the commercial value of the technology service bundle: The Sero business model has the potential to be truly disruptive. From the UK’s perceptive, there is an understood need to develop an electricity-based low carbon/low cost heating solution for residential properties with attuned with Grid impact. FLATLINE proposes this outcome and seeks to demonstrate here that commercial returns will be high enough such that the benefits to customers are irrefutable.

8 TECHNICAL SOLUTION AND EXPECTED PERFORMANCE TECHNICAL FEASIBILITY REPORT STRUCTURE

The feasibility phase of FLATLINE has undertaken more detailed investigations across a broad range of topics within the scope of the overall concept, and has delivered a large volume of work in considerable detail for many of these areas. The underpinning key driver for the work has been to evidence the economic feasibility of the proposal for fixed, low bills to occupants through providing grid dDSR services. In order to achieve this, the project partners have covered topics including the physical construction of the homes, the management system architecture, forecasting occupant energy demands, cyber security, future energy tariff rates, legal and regulatory boundaries, renewable energy generation modelling, and data storage, rights and protection. Given this level of detail, in order to maintain a legible report much of the detailed underpinning work has been placed in appendices, with only the key findings and steps included in the report’s main body. The main body of this report is structured to sequentially work through the primary questions that are relevant to the delivery of providing fixed, low bills to occupants alongside grid dDSR services. Broadly, these are: 1. What are the legal and regulatory barriers or challenges to undertaking this? 2. How much energy might reasonably be generated on a typical site, and when? 3. How much energy may be demanded by occupants, and when? 4. What component elements will be required to deliver the overall system? 5. What controls will be required to manage the system? 6. What security and protection will be needed to ensure safe, robust operation? The report works through each of these topics to ultimately answer the feasibility key question: Can we create a viable business case to deliver fixed, low bills to occupants through grid dDSR services?

PERFORMANCE INFORMATION

LEGAL & REGULATORY ENVIRONMENT

This section of the report investigates the current legal and regulatory framework in which the proposed business model would currently operate. It also looks at the ‘direction of travel’ as declared by relevant authorities to review whether these frameworks may have changes occurring in future that could enable, or disable, functions of the business model. LEGAL CONSIDERATIONS

This section outlines the legal requirements for the partners and host development in order to deliver the outcome required for Domestic DSR. The project relies on the ability to have a ‘right’ to manage technology within a tenants or private homeowners home in order to deliver an outcome for which they specify. It is important that the system remains operational with minimal interference from 3rd parties. RIGHT TO BUY Recently abolished in Wales, Right to Buy gives social housing tenants the ability to purchase their home. It will be important that any agreement with Housing Associations in England includes provisions for any covenants typically included in a sale to a private home owner. GENERAL DATA PROTECTION REGULATIONS Separate to ‘Personal Data’ that is required to maintain a contractual relationship with the customer such as name, contact details etc. there is a need to collect data from the installed technologies and sensors to optimise the system. This data is stored and used to create patterns that enable better forecasting and optimisation of the energy management strategy. Under GDPR ‘Personal Data’ is defined as any information relating to an identifiable natural person, the information or data needs to be linked to the person such that they can be identified. For the FLATLINE project it will be important that ‘Personal Data’ such as name, address or any directly or indirectly related data to the customer of Sero Energy is stored separately from ‘System Data’. The System Data will be anonymised data that is first collected by the

11 technology providers in their data clouds then passed to the Aggregator to perform the optimisation of the system, part of the service being provided by Sero Energy. It will be important that Sero Energy states clearly in its Privacy Policy that the System Data it collects is used for optimising the service. REGULATORY CONSIDERATIONS THE RIGHT TO SWITCH Dependant on the relationship with the customer as outlined above, there is a right for tenants and homeowners to switch suppliers. 1. The energy costs are included as part of the tenancy agreement (‘default supplier clause’) and the landlord (Sero Homes) has responsibility for paying the bill. This removes the tenants’ right to switch the energy supplier however the Landlord can only charge for energy use, standing charges and VAT. Overcharging will expose the landlord to scrutiny of the charges to the tenant and may incur a claim. An exclusive relationship between Sero Homes and Sero Energy with bills included within the tenancy provides the most secure position for the FLATLINE business model. 2. Where a third party landlord has a relationship with Sero Energy, they may wish to opt for the model described in point (1) however this is unlikely for most Housing associations. Sero Energy would reserve the right to manage the energy for the homes however the tenant would have the right to switch suppliers. This will create the need for Sero Energy as energy manager or aggregator to liaise with the tenants’ supplier over DSR activity. 3. For private home owners, the ability to switch supplier means Sero Energy would lose that customer in the aggregation of Energy Positive homes. ELECTRICITY SUPPLY Sero Energy is working in partnership with a licensed supplier for electricity supply to all homes in the project and the wider business. The supplier is a separate company and will be responsible for Compliance with industry codes, Sero Energy will operate as a White Label or other suitable ‘license free’ operator mechanism. The Energy Service model represents a new way to supply energy to customers as a simplified package deal and will face regulatory hurdles which require engagement with Ofgem. Sero Energy’s purpose in the energy market is to reduce bills, enable budgeting, simplify new technology, optimise the grid and accelerate the clean energy shift. Consumers are at the forefront of the Energy Service model and Ofgem’s move to Principle Based Regulation will help new and innovative models succeed in the market. It will be important the Sero Energy complies with the Standards of Conduct to ensure that customers understand the tariff that’s being offered to them. It will also be important that they can compare the cost of energy with the market to make sure that Sero Energy is offering fair value.

HEAT SUPPLY The Minus7 system has two methods for charging heat to consumers; as metered heat or as electricity charged through their SmartSwitch system. This system meters the heat for all homes on the network and intelligently switches between the homes for electricity supply to the heat pump. This allocates the run time of the system proportionally between the homes based on their individual heat consumption, this allows the user choice in supplier for heat. HEAT NETWORK METERING & BILLING REGULATIONS 20141 As the Minus7 system is a ‘micro district’ heating network and Sero Energy is a Heat supplier the Regulations place obligations on Sero Energy to; - Notify the National Measurement and Regulation Office (NMRO) of the heat network and metering. - Ensure Heat Meters are accurate, maintained and periodically checked.

1 http://www.legislation.gov.uk/uksi/2014/3120/pdfs/uksi_20143120_en.pdf

HEAT TRUST The Heat Trust protection is aimed at heat energy suppliers who contract with metered or unmetered domestic and micro business properties where the heat customer pays their supplier directly for their heat energy. Although voluntary, the Scheme is supported by government as a self-regulation initiative that recognises best practice. The Scheme sets customer service standards and customer protection requirements we expect heat suppliers to provide. These requirements are comparable to the quality and performance standards for regulated utilities and draw on legislation and industry best practice. As members of the Scheme, suppliers agree to abide by the Scheme Rules and Bye-Laws. AGGREGATION To date, there is no Regulation for the activities of aggregators, Sero Energy would likely fall under Regulation activity as it procures the services of Aggregators to deliver the Energy Service. Aggregation to date has focused around large consumers and Ofgem has not had cause for concern on the conduct of the industry. However, there has been little activity to date with household consumers and there is a potential need for consumer protection. A report in May 20162 by Ofgem highlighted potential policy changes in this area; - Industry accreditation scheme – voluntary scheme (i.e. Heat Trust) - Voluntary code of conduct - Formal licensing by Ofgem TECHNICAL SOLUTION METHODOLOGY

This section of the report investigates the levels of energy that could be generated from homes, as well as the probable demand which may arise from those same homes. Critically to the success of providing the business case, this section considers this not just total levels of generation and demand, but also the timings of these. To ensure that the basis of the FLATLINE feasibility is a realistic representation of future potential, the detailed technical analysis has been undertaken on 58 homes that form part of a real planned housing development. The pilot element of this housing development has been selected as one which is representative of wider housing schemes throughout the UK, and importantly is a site that was not planned out with the FLATLINE proposal in mind. As such, these 58 homes make a fair representation of the potential generation, demand and other restrictions without being unduly positive or prescriptive. Based on the 58 homes pilot site, this establishes; 1. The forecast total electrical and heating demand of the homes from buildings & occupants, 2. The forecast total electrical and heating generation of the homes from on-site renewables. These two key outputs have been developed for each half hour period of a representative day for each month of the year. This provides the key base information from which the performance of the housing development can be extrapolated, which is undertaken in the following section.

2https://www.ofgem.gov.uk/system/files/docs/2016/07/aggregators_barriers_and_external_impacts_a_report_by_pa_cons ulting_0.pdf

PILOT SITE

The 58 home pilot site has been selected from a large housing development in South Wales. The site is being developed by a collaboration of a Housing Association and a not-for- profit housing developer, both of whom are working with Sero Homes with a view to delivering the FLATLINE model on the site. The 15-acre site is intended to be developed over six phases, ultimately delivering 225 homes split between 1, 2 3 and 4 bedroom properties. These will be provided as a mix of rental (100+), shared ownership (70+) and open market sale (50+). The site was granted planning consent prior to the FLATLINE project, which means that the overall masterplan is practically fixed without requiring a new planning approval. These homes will sit amongst the hills of South Wales, which will no doubt be a great amenity for the future residents. For FLATLINE, however, the site represents a few of the challenges that may occur for any housing development: the area is defined as a severe exposure zone, and it has an element of solar shading from surrounding hills, most notably to the West. These restrict the potential construction typologies that may be usable, and limit the potential that can be achieve from solar renewable generation. The 58 homes are therefore taken as a reasonable representation of UK housing development: They are not “solar oriented”; they have site-specific environmental restrictions; and they have an aesthetic layout and design that is not driven by the FLATLINE business model demands and is demonstrably acceptable to planning authorities. The site therefore provide a realistic basis for the work of this feasibility study that does not embed undue optimism into the results. Furthermore, it also presents a very real opportunity to deliver the Phase 2 work of FLATLINE, if selected. ESTABLISHING ENERGY DEMAND

Each of the homes on the pilot site has undergone an extensive assessment of the likely energy demands that will arise from both occupancy and building fabric. For brevity, this is summarised here, however full details of the data sources and calculations that have been used to derive the energy demands discussed here are given in the relevant appendix. HEAT ENERGY DEMAND Forecasts of heat energy demand include that for space heating and for domestic hot water. Space heating demand is calculated for each house type based on a set fabric performance specification and using climate data for Cardiff for an indicative test reference year. (The reference data is an average of real climate conditions measured over a number of years and is typically used for forecasting purposes since ‘real world’ data can be highly variable.) Hot water demand is separately determined based on occupant numbers with the energy required to heat the water subsequently calculated. Daily profiles of heat energy demand have been created for an ‘average’ day of each month. Six house types were considered within the pilot area of the site, with assumed occupancies of 3 or 4 persons depending on the number of bed spaces present. Overall the pilot area contains 58 dwellings and 212 assumed occupants. The typical daily distribution of heat demand per month is shown in Figure 1, with monthly and annual totals provided in Table 1. Note that here the means of generating the heat have not been considered, hence no

14 heating system efficiency factors have been applied. In site scenarios where the heat is assumed to be delivered via a gas boiler, it is taken this has an efficiency of 90%. Where heat is assumed to be delivered via a heat pump, the relevant coefficient of performance (CoP) is applied. The annual heat energy demand for the pilot site (independent of chosen heating system efficiencies) is forecast at approximately 324 MWh per year. The main demand peak occurs around 8am, with a secondary peak around 7pm. These peaks arise from the hot water demand; the heating demand shows much less differential across a typical day, since it is assumed that the heat is supplied on demand to achieve a set internal temperature of 20°C, rather than operating to a set schedule, which would lead to higher variability.

Half hourly site heat energy demand per month 1400

January 1200 February

1000 March

April 800 May 600 June July 400

Heat demand, kWh August 200 September October

0 November 0 4 8 12 16 20 24 December Time over typical day

FIGURE 1: DAILY DISTRIBUTION OF HEAT DEMAND PER MONTH, FOR PILOT SITE

TABLE 1: MONTHLY TOTAL HEAT DEMAND FOR PILOT SITE

ELECTRICAL ENERGY DEMAND Forecasts of electricity demand are based on occupancy levels assumed in each dwelling. This considers all electricity demands, including lighting, cooking, appliances, etc, but does not include any allowance for the provision of heating or hot water, which is separately forecast. Note however that some allowance for the use of electrical showers (i.e. separate from any centrally generated hot water) is included within the data that is used to derive the estimates. Daily profiles of electricity demand have been created for an ‘average’ day of each month.

The typical daily distribution of electricity per month is shown in Figure 2, with monthly and annual totals provided in Table 2. The annual electricity demand for the pilot site is forecast at approximately 314 MWh per year. The main demand peak occurs around 7pm with a secondary peak around 8am. The average electricity demand per dwelling (approx. 5400 kWh) is higher than currently assumed as typical household consumption by BEIS (3800 kWh). This is discussed in more detail in the relevant appendix, but is largely the result of a higher occupancy assumption for dwellings on the site (4 and 5 occupants) compared to the dominant occupancy rates assumed in the BEIS data due to 2 and 3 occupant dwellings.

Half hourly site electricity demand per month 1400

1200 January February

1000 March

April 800 May 600 June July

400 August

Electricity demand, kWh 200 September October

0 November

0 4 8 12 16 20 24 December Time over typical day

FIGURE 2: DAILY DISTRIBUTION OF ELECTRICITY DEMAND PER MONTH, FOR PILOT SITE

TABLE 2: MONTHLY TOTAL ELECTRICITY DEMAND FOR PILOT SITE

ESTABLISHING ELECTRICAL GENERATION As with energy demands, each of the homes on the pilot site has undergone an extensive assessment of the likely potential energy generation. For brevity, this is summarised here, however, full details of the data sources and calculations that have been used to estimate electricity generation discussed here are given in Appendix B. The size of PV system that will fit on the roof of each house type has been determined based on the Minus7 integrated PV panels and some rules relating to exclusion zones from roof edges and obstacles, etc. Estimates of PV generation capacity have then been derived based on the Standard Estimation Method adopted by the Microgeneration Certification Scheme (MCS), utilising irradiation data for Cardiff. The most prevalent orientation and inclination for each particular house type has been chosen to be reasonably representative of the pilot site. Details for individual house types and the pilot site as a whole is set out in Table 3.

TABLE 3: SOLAR PV CAPACITY AND YIELD FOR INDIVIDUAL HOUSE TYPES

The pilot site of 58 properties will provide 164kW of solar PV capacity and generate approximately 130 MWh electricity per year. Photovoltaic Geographical Information System (PVGIS) data has been used to create daily profiles of electricity generation at half hourly intervals according to the solar irradiance for the location of the site and the derived site yield. This has been used to provide a 12-day-year PV system yield (kWh) for each house type, which is then multiplied by the number of instances of each house type on the site to give a combined overall site profile, as illustrated in Figure 3.

Average Daily Solar PV System Yield (kWh) per Half-Hourly Period 35

January 25 February March 20 April May

15 June July

August Yield (kWh/half hour) (kWh/half Yield 10 September

October

5 November

December 0 0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 0:00 GMT (HH:MM)

FIGURE 3: AVERAGE DAILY SOLAR PV SYSTEM YIELD (KWH) PER HALF-HOURLY PERIOD FOR PILOT SITE

The pilot site is dominated by house types HT1 at 18 units, and HT4v2 at 20 units, which are south facing. As such the aggregated generation profile peak is led by these dwellings and occurs around 12-1pm. Site generation peaks at 30.5kWh per half hour (i.e. 61kW). DETERMINING ELECTRICITY FLOWS FOR THE SITE Yield data can be used to determine net energy flows by subtracting generation data from demand data provided above. This has been done on a per-property basis and then scaled for the whole site to account for localised effects at a house level, rather than simply subtracting total site values. Negative values occur when solar generation is meeting all demands on site and excess is being exported back to the grid. Figure 4 shows the net energy flows of the FLATLINE site. The net demand does not vary significantly over the winter months due to low irradiance levels. However, this changes considerably as irradiation levels increase. At peak times of generation and low demand, site export can reach 15kWh per half hour (30kW). Figure 5 illustrates the significant impact that PV would have on overall electricity consumption across the FLATLINE site as a whole if compared with equivalent dwellings without PV. From April through August grid electricity consumption is reduced by more than 50%.

Average Daily Electricity Flows (kWh) per Half-Hourly Period 50.0

40.0 January

February 30.0 March

April

20.0 May

June 10.0 July August

September 0.0 October 0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 0:00 ElectricityFlow (kWh/half hour) November

-10.0 December

-20.0 GMT (HH:MM)

FIGURE 4: AVERAGE DAILY ELECTRICITY FLOWS (KWH) PER HALF-HOURLY PERIOD FOR FLATLINE SITE

Total Average Daily Electricity Flows with and without PV (kWh) 1400.0 1176.9 1202.5 1200.0 987.6 1000.0 893.6 933.6 842.4 751.9 788.3 800.0 671.2 708.3 695.7 667.8

600.0 1160.4 1047.0 906.1 400.0 686.3 699.3 521.1

Electricity (kWh) 200.0 453.6 351.6 291.6 311.7 330.2 0.0 0.0 284.8 0.0 0.0 0.0 0.0 -63.6 -71.7 -200.0 -129.4 -140.1 -188.3 -204.8 -184.5 -400.0 Month

Import (no PV) Import (with PV) Export (with PV)

FIGURE 5: TOTAL AVERAGE DAILY ELECTRICITY FLOWS WITH AND WITHOUT PV (KWH) FOR FLATLINE SITE

Table 4 provides headline generation and demand figures for the FLATLINE site, where it is calculated that approximately 77% of solar PV generation will be used on site during the course of a year, thus reducing import requirements by nearly 100 MWh. This has the potential to save occupants more than £15,0003 per year on electricity 4 bills across the 58 properties. The annual PV yield would offset 45.6 tonnes of CO2 per year , compared to typical UK grid-fed electricity. With 30 MWh of excess generation per year there is scope to incorporate battery storage into the scheme to further increase utilisation of on-site solar PV generation. Excess generation could also potentially be exported to the grid for payment if market conditions allow, or diverted into resistive loads such as immersion heaters as a secondary form of energy storage.

TABLE 4: GENERATION AND EXPORT FIGURES FOR FLATLINE SITE

3 https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/719924/table_224.xls. BEIS figure of £0.151/kWh using south Wales average variable price (standing charge not included). 1,667kWh x £0.151 = £252. 4 https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/635632/Conversion_factors_2017_- _Condensed_set__for_most_users__v02-00.xls BEIS figure of 0.352kgCO2/kg for UK grid electricity. 129,697kWh x 0.352 = 45.6 tonnes.

19 TECHNICAL SOLUTION ANALYSIS

Based on the detailed technical methodology set out in the previous section, this now applies the identified demands and potential generation to understand how the application of the technologies proposed in the FLATLINE project will influence the impact of the houses on the relevant energy network. To appreciate the full potential impact of the FLATLINE system, this section outlines a sequence of logical progressions that start with the pilot site as a "standard" development and run through to the full FLATLINE operation and beyond. Comparable key graphs are given for each step that illustrate the pilot site development's impact on the energy network were it to be built out as described. The full sequence of progression is: 1. Baseline "Standard" House Builder homes 2. Enhanced Building Fabric lower energy homes 3. Enhanced Fabric, Renewables & Low Carbon Technologies in homes 4. Enhanced Fabric, Renewables & Low Carbon Technologies, and Energy Storage in homes These steps are then followed by a brief section on the potential of the FLATLINE solution to further extend performance through integrating additional systems. COMPARATIVE ENERGY COSTS The following four steps show the energy forecasts for the homes and each gives an estimated energy costs that the pilot site would incur. To help visualise this, the electricity price over 24 hours has been plotted as a second vertical axis (black, dashed line) on the graphs to show how the Pilot site’s energy demand varies in relation to this. For the estimations of costs, gas prices have been assumed to be a flat tariff of 3.64p/kW all day, all year. Electricity prices have been shown on the graphs as an annual average electricity price profile over 24 hour, since showing monthly price lines was too cluttered. However, this has been calculated for the actual cost estimates using a monthly average price profile over 24 hours, enabling the inter-seasonal variations to be captured. This average monthly price profile assumes a variable tariff, and the price used includes for the wholesale price as well as distribution, transmission and capacity charges. This does not allow for VAT, supplier margin or environmental policy obligations, though given these are excluded from all models the figures are comparable between themselves. Note the FLATLINE feasibility has not shown the energy costs on a current ‘standard’ residential energy tariff or ‘Economy 7’ model. The report seeks to make a comparison of the pilot site’s performance in a likely future energy scenario rather than against a baseline of today’s offerings. This is put forward in the light of the timescales for the Demonstrator and the anticipated changes in tariffs, but also to provide a conservative estimation of the opportunity FLATLINE presents: In both instances, using current tariffs increases the forecast cost of the homes’ energy. SEQUENTIAL ANALYSIS OF HOMES BASELINE "STANDARD" HOUSE BUILDER HOMES The starting case for investigating the impact of homes on energy networks is to understand the demands modern new homes would have. To undertake this, the 58 pilot homes from the site have been assumed to be built to be compliant with current (Welsh) Building Regulations. Their individual SAP (Standard Assessment Procedure) scores have been provided by the developers. The homes have been based on a gas condensing combi-boiler, 'compliant' levels of insulation and with no renewable energy generation on site. Using the methodologies defined in the previous section, the energy demand of this pilot site has been forecast for a typical, representative day of each month of the year. This demand represents the impact on the energy grids that the pilot site would have if it were built out to this standard – in this regard it differs from the 'pure' demand requirements identified in the earlier section as it factors efficiency. The baseline specification 58 homes can be shown to have the following predicted impact on the energy networks, in this instance impacting both the National Grid (for electric) and the national gas network (for heat):

As can be seen from this graph, the electrical demand from the pilot site when developed to the 'baseline' specification peaks during the evening, occurring slightly later during summer months and slightly earlier during the winter months. Higher demand is seen throughout the days in winter, whilst overnight is the lowest demand throughout the year. The price of electricity (dashed black line) generally reflects this usage pattern, spiking significantly with the evening demand and dropping modestly for the low overnight demand. Based on this forecast usage pattern, the 58 homes at the pilot site would require 313.8 MWh per year, which on a variable electrical tariff as shown would cost £31,300 per year.

The heating graph also shows the impact of the heat demand on the gas network, illustrating the morning heating peak primarily driven by hot water demands. This peak is largely independent of the month, but the overall line rises and falls to track the season, reflecting the underlying heating demand of the homes. Based on this forecast usage pattern, the pilot site would require 396.3 MWh per year, which on a fixed price gas tariff as shown would cost £18,600 per year. The total annual fuel cost of the site is therefore £49,900 per annum. ENHANCED BUILDING FABRIC LOWER ENERGY HOMES Progressing beyond the baseline case, we have next investigated the potential impact of reducing the demands that arise from the homes themselves – commonly called the "Fabric First" approach. This does not make any assumptions about behaviour change in the occupants of the homes (more of which later), but rather looks to improve the construction of the homes to ensure they require less energy to operate.

The Enhanced Fabric homes use a new SAP calculation based on improved constructional insulation (U-Value), thermal bridging (ψ-Values) and airtightness. These have been developed based on the specific site constraints, such as exposure, with an awareness of the restrictions of the site masterplan, and with a pragmatic view regarding what can be delivered by current contractors operating in the South Wales region. See the Appendix for further details and the methodology underpinning this work. The Enhanced Fabric homes, however, retain the condensing gas boiler of the baseline homes, and also do not have any on site renewable energy generation or notable low carbon technologies. Based on this, the 58 homes are forecast to have the following predicted impact on the energy networks:

As can be seen from the graph, the electrical demand from the pilot site does not change from that of the baseline development. This is because the thermal demand for these houses is met by the gas network, and no presumptions about behaviour change from the occupants have been made. As a result, almost all of the electrical demand arises from lighting and fans (regulated electrical demand) and small power usage by occupants (unregulated electrical demand). This graph therefore shows that, in terms of impact on the National Grid, the Enhanced Fabric homes perform similarly to the baseline. Based on this forecast usage pattern, the pilot site would require 313.8 MWh per year, which on a variable electrical tariff as shown would cost £31,300 per year.

The second graph also shows the impact of the heat demand on the gas network, illustrating that the Enhanced Fabric homes are reducing the overall heat demand that is passed through the gas network. The reduced heating

22 demands slightly accentuate the impact of hot water, meaning that the morning peak (and secondary evening peak) are both more prominent compared to the baseline specification. Based on this forecast usage pattern, the pilot site would require 359.5 MWh per year, which on a fixed price gas tariff as shown would cost £17,300 per year. This equates to the total annual heating costs of more than four dwellings when compared to the baseline specification. The total annual fuel cost of the site is therefore £48,600 per annum. ENHANCED FABRIC, RENEWABLES & LOW CARBON TECHNOLOGIES IN HOMES The pilot site homes under this iteration are built using the enhanced "Fabric First" approach outlined above, but are further improved by the addition of renewable and low carbon technologies. Photovoltaic (PV) electrical generation has been profiled for the 58 homes in the pilot site as set out in the earlier methodology, and including provision for orientation, roof pitch, solar roof panel arrangement and shading on a case-by-case basis (full details are given in the relevant appendix). The homes have also been switched to source their heat demand from the electricity National Grid rather than using gas by using an air source heat pump. For the purposes of this study, this is a hypothetical 'instantaneous' heat pump that is presumed to operate in-line with the homes thermal demand, and operates with a year-round Coefficient of Performance (CoP) of 2.9. Whilst it is acknowledged that all heat pumps available on the market work with a small thermal store in the form of the domestic hot water tank, including this small heat store in the modelling here removes the clarity of the analysis: Whilst 'real world' heat pumps will cycle on and off every few hours to recharge their thermal store, this operation is currently undertaken agnostic of its impact on the energy grid and is solely driven by the homes' thermal demands. The resultant graphs of this present more peaks and troughs, but ultimately track the identified thermal demands of the homes. Using the 'instantaneous' heat pump provides a representative view of how a large number of heat pumps would impact on the grid in aggregate, each cycling at slightly different times to meet unique demand profiles in each home, but ultimately trending to match thermal demand. Building the 58 homes at using "Fabric First" and with renewables and heat pumps can be shown to have the following predicted impact, now purely electrical demand impacting the National Grid:

As can be seen from this graph, the electrical demand from the pilot site has changed noticeably to previous versions. This results from the decrease in the nett energy required from the Grid due to the impact of photovoltaic generation on site, which predictably has greatest impact in the summer months and least impact during the shorter winter months with lower angle sun. Based on this forecast usage pattern, the 58 homes would require 184.1 MWh per year to meet its direct electrical demands, which on a variable electrical tariff as shown would cost £21,700 per year. Note that it has been assumed that any exported electricity is assumed to be sold at lower, wholesale prices.

This graph shows the heat demand for the site, and as with previous heat graphs illustrates the main morning peak driven by hot water demand with the secondary evening peak, all broadly adjusting in accordance with the seasonal heating demand (using the Fabric First specification). Differing from previous heat demand graphs, however, this has presumed an 'instantaneous' heat pump is used to meet the heat demand using electricity – the variable electricity price tariff is therefore shown instead of the fixed gas price. This increase in electricity required to provide heating and hot water to the site is forecast as an additional electrical demand of 111.6MWh per year, equating to £9,600 per year on the variable tariff shown. Given both thermal and electrical demands of the homes are now met by electrical energy from the National Grid (and to a less extent from on-site renewables), the impact of these homes can now be combined to illustrate their overall impact on the Grid:

The "fully electric" site shows a combined profile which reflects a morning rise in electrical demand that largely stems from hot water demands, with the highest overall peak occurring during the evenings as a combination of electrical demands and the secondary hot water peak. The total annual fuel cost of the site is therefore £31,300 per annum. This is based on the combined forecast usage pattern, totalling 295.7 MWh per year on a variable electrical tariff. ENHANCED FABRIC, RENEWABLES & LOW CARBON TECHNOLOGIES, AND ENERGY STORAGE IN HOMES The final step is to model the homes on the pilot site at as the full FLATLINE first generation specification. This builds from the previous specification for the homes but supplements the photovoltaic on-site generation with Sonnen's

24 battery storage, and replaces the 'instantaneous' heat pump with Minus7's solar thermal, mini-district heat pump system (which has a large thermal store integral to its operation). For both electricity and heat, this disconnects the demand of the homes from having a direct electrical impact on the National Grid - in effect the Sonnen battery and Minus7 thermal store become 'buffers' which supply the needs of the homes as required, and which then independently draw power to 'recharge' their reserves. This, of course, represents the essence of FLATLINE and the potential for domestic Demand Side Response. For the feasibility, the project team have developed a first version of a "FLATLINE Control Logic" to understand the practical operation of the FLATLINE homes on the site. This has been developed for both electrical and thermal aspects, and will be further developed, trialled and ultimately operated if the second phase of this project is successful. More details of the development and underpinning control logic can be found in the relevant appendix. Building 58 "FLATLINE" homes at , and implementing the Control Logic to optimise the operation and usage of the energy storage available, can be shown to have the following predicted impact on electrical demand to the National Grid (as before, there is no gas impact):

The electrical demand graph differs drastically from those of the previous specifications and shows peaks of electricity drawn from the National Grid. This is the Control Logic triggering battery charging. The Control Logic is simultaneously forecasting the future electrical demands of the home compared with the battery's available storage capacity, and for this specific period of time, the Control Logic is identifying the cheapest National Grid price, whereby the battery is triggered to recharge (if required). The graph therefore shows more spikes of demand, though it should be noted the Control Logic is also able to 'throttle' the pace of this recharging as needed (it is envisioned this will be a point for liaison with the District Service Operator). For eight months of the year, the electrical demand occurs entirely outside of the electricity price peak, with the Control Logic selecting to charge the battery store overnight during spring and autumn months, but balancing night- time charging with some daytime recharging during the summer months, the latter showing the impact of renewables both on-site and on Grid pricing. Winter months of November to February currently show unexpected battery charging at peak price rate; this is an unresolved anomaly in the feasibility Control Logic that may represent proper application of the ruleset, but will require further work in the Demonstration phase (if awarded) to fully understand, or alternatively may simply be a ruleset or system functional error yet to be identified. The working presumption is that further development work with a more sophisticated Control Logic will allow these four months to be shifted into off-peak times as well, since the battery is not at capacity outside these times. Based on the feasibility Control Logic (without yet assuming the four months can be shifted to off-peak), the pilot site would require 208.2 MWh per year to meet its direct electrical demands, which on a variable electrical tariff as shown would cost £20,300 per year.

The heat electrical demand graph also shows that the homes' actual heat demand is decoupled from when the electrical impact on the National Grid occurs. As with the electrical demand graph, the heat demand graph demonstrates peaks of electricity drawn from the Grid. This is the Control Logic triggering the recharging of the Minus7 thermal store. These peaks do not match the Sonnen battery peaks as the underlying Control Logic is different: For the battery, the Control Logic searches for the cheapest electricity in the forecast period. For the Minus7 system, the Control Logic is searching for the cheapest thermal energy for the forecast period. However, thermal energy is a factor of both the price of electricity from the Grid and the Coefficient of Performance (CoP) that transforms that electricity into heat within the Minus7 system. The CoP of the Minus7 system is highly variable, given the system uses both solar thermal, ambient and 'cold' store sources to derive the highest temperature source from which to run the heat pump (or in some conditions, bypass the heat pump altogether to feed solar thermal to charge the thermal store). The Control Logic is therefore using ½ hourly electricity pricing and ½ hourly CoP forecasting to reflect these variables. The result of this interaction is that it is possible for the Control Logic to select to charge the thermal store at a time with a high electricity price if the CoP is sufficiently high that this still generates 'best value' thermal energy. This Control Logic can be seen from the graphs: During winter, where the Minus7 system rarely achieves a CoP beyond 3, the impact of electricity price shows as the system night charges the thermal store. During summer, however, the Minus7 system achieves a CoP beyond 20 during peak sunlight hours. Here the CoP outweighs the price (which itself is lower due to off-site renewables), meaning that the Control Logic charges the thermal store during the day. Based on the feasibility Control Logic, the pilot site would require 140.3 MWh per year to meet its heating demands, which on a variable electrical tariff as shown would cost £8,800 per year. As with the previous specification, the "full electric" pilot site can now be expressed as an overall impact on the National Grid:

The total annual fuel cost of the site is therefore £29,100 per annum, based on this combined forecast usage pattern, with a total electrical demand of 348.5 MWh per year on a variable electrical tariff. It is anticipated that with more detailed development of the Control Logic under the Phase 2 Demonstrator, this total cost can be reduced by a further £11,100 (resulting from shifting the anomalous electrical charging in some peak months). Although this final iteration of the homes including energy storage lowers the cost (and is expected to lower the cost notably further with more developed Control Logic), the total electrical demand for the pilot site has actually increased from the previous version (384.5MWh from 295.7 MWh per year). This is largely as a result of the use of the storage itself. Since neither the electrical or thermal storage are 100% efficiency (sonnen’s battery, for example, achieves 88%), shifting the time of the electrical demand requires more energy has to be taken from the Grid (or the renewables) to ensure the demand can be met once system efficiencies are factored in. For example, 1kWh of demand can be passed through to the Grid as 1kWh, but would require around 1.13kWh to be drawn from the Grid into storage such that it could provide 1kWh at a later time. The prototype Control Logic is already factoring this system efficiency into the modelling, hence the increase in overall site energy demand. The 'default' setting of this Control Logic is to minimise the total cost of electricity purchased to run the site. Given cost is a primary means of signalling demand avoidance, this also means the 'default' Control Logic is delivering this. However, it is envisaged that active Demand Side Response calls can also be overlaid on the Control Logic, which will provide further flexibility and potential income/savings discussed in the next section. SUMMARY OF SCENARIOS The table below illustrates the impacts of the stepped improvement in the homes on the site through the application of improved fabric, renewables and low carbon technologies, and lastly using battery and thermal storage. It clearly shows the significant drop in energy cost for the whole site, which with further work to the Control Logic is likely to result in a 64% reduction from the baseline house design. It should also be emphasised, the baseline housing specification is already compliant with the latest Building Regulations for new homes, and these baseline homes therefore has a significantly lower energy demand than the majority of UK homes (these baseline homes would achieve an Energy Performance Certificate rating of “A” or “B”, the UK average rating is “D” or “E”).

TABLE 5 – SUMMARY OF ENERGY COSTS IN EACH SCENARIO

MWh MWh MWh

CONTROL SYSTEM FLEXIBILITY

The rules for which the aggregated network of homes are driven by the following scenarios which occur at different times of the day. The homes have been modelled to self-consume energy and import from the grid at the cheapest periods of the day. This represents a ‘central case’ scenario for demonstration, there will be times of the day or year that offer varying levels of flexibility and spare capacity. There are a large number of permutations of the rules mentioned above, the purpose of this report is to demonstrate that capacity in the system is available and when they typically may occur. The Phase 2 demonstration project will monitor, pattern and analyse the data so that the system has the information it needs to identify forecasted flexibility in the system based on real time data. The homes in ‘default’ operation already offer DSR by operating at the lowest cost for the consumer. In the process of searching out the best period in which to purchase electricity, the system naturally avoids the peak periods (see Network Avoidance) with high wholesale costs and network charges. This has the advantage of complementing the network whilst reducing costs as much as possible for consumers, in practice the system will respond to electricity pricing forecasts that will change with weather and network conditions. Note that the majority of DSR capability modelled in this section has no effect on the consumer experience, with the exception of appliance cycle intervention. RESERVE CAPACITY OR ‘TURN DOWN’ AVAILABILITY This means less demand and/or more generation impacting the grid. 1. All solar generation is exported to the grid, the house electricity demands are met by the battery provided there is capacity. 2. Heat pumps, if running are turned off and the home runs off the heat store. 3. Immersion heaters are paused. 4. Smart appliances if running are paused. (not modelled) 5. Electric vehicles if charging are paused. (not modelled)

The system has been modelled on a half hourly basis by looking at the ‘default’ operation and identifying spare capacity as a combination of demand reduction/generation and storage in using the rules above in that period. These individual elements have then been combined to produce the aggregate graph shown above. Offering reserve capacity is more challenging for homes as the grid needs typically align with the demands of the home and the technology serves the consumer as a priority (assuming that’s the lowest cost option). The graph demonstrates a varying amount of Capacity5 available to the network, it mirrors the heat pump running periods which mainly coincide with periods of low demand on the grid. Reserve Capacity (including Capacity Market) is most often required during morning and evening peak windows, there is potential during the summer months to offer an increased export by switching to energy storage for the house demands. There are a number of options in enhancing the Reserve Capacity; 1. Model in the effect of Smart Appliance operation, typically consumers will choose to run appliances whilst at home which aligns with periods of peak demands. These demands may be met by the battery however an ability to pause for a period of time will offer additional Reserve Capacity. 2. It is intended that the project will install EV charging points for all residents, assuming moderate take up of electric vehicles on site. The charging of these vehicles can be paused provided it still reaches the desired charge level on time, this will offer significant turn down in demand. 3. Enabling battery export at peak times – Currently, grid connection policy prevents the storage assets from exporting to the grid at peak times. Batteries are restricted through software to export to the needs of the home only or self-consume solar energy. As part of a Virtual Power Station, the ability to export spare capacity from the battery will enable an increase in Reserve Capacity available. INCREASED DEMAND OR ‘TURN UP’ This means more demand and/or less generation impacting the grid. 1. The home consumes all the PV generation so that there is no export, this requires ‘dumping’ of the loads into hot water, EV’s or pending appliances. 2. The battery charges at full capacity provided storage is available. 3. The inline immersion for the Minus7 heat pump is activated to provide heat to the store provided storage is available. 4. An immersion in the internal hot water tank is turned on (not modelled as assumed to be the dump load in 1) 5. Plugged in vehicles that are pending charge are charged at full power. (not modelled) 6. Appliances pending operation are started.(not modelled)

5 The capacity show in the graph is available for at least 2 hours.

Increasing the demands on site offers much greater potential for the project, due to the nature of the stored energy capacity in the homes as electricity and hot water. Contrary to the Reserve Capacity scenario, the homes are able to offer demand to the grid at various times of the day and typically when the demand is needed most. A likely scenario, as a result of intermittent renewable energy on the grid is that demand will be needed during the day or overnight. The graph shows a baseload turn up capacity of 150kW due to the permanent ‘head room’ in the heat storage, this demonstrates the ability for the hot water store to accept higher temperatures at any time of the day or year. The summer months show a reduced turn up capacity, this is due to the energy stores being saturated by solar thermal and electrical generation. There is also peaks in demand turn up that follow the typical house demand peaks, this is because the stores are depleted after serving the home during times high cost and network charging. There is an opportunity to increase Demand Turn Up significantly by adding additional headroom storage to both the battery and heat store, this would need to be considered against the additional CAPEX required. Smart appliances and Electric vehicles could significantly increase the turn up potential for the aggregated community. FLATLINE – THE NEXT EVOLUTION

Electric Vehicles – The host project will feature electric vehicle chargers and Sero Energy will encourage tenants to switch to EV’s with cheap off peak (smart) charging tariffs6. The pattern of electric vehicles will be dependent on 1) take up amongst tenants and 2) work & social life patterns. As part of the Phase 2 project, FLATLINE will consider the potential to integrate the capacity offered (1 way charging) by controlling the charge period of the vehicles. The homes will be built with a 3 phase connection and the potential of charging each vehicle on demand at 11kW will be material in the total capacity and flexibility offered by the development.

Appliances – The host project will integrate a number of smart appliances in the homes as standard (to test the consumer response) and discounted appliances will be offered to new tenants or home buyers. Samsung is a key partner of the FLATLINE project and through the SmartThings application, there is the potential to engage consumers in appliance scheduling (i.e. finish by “X:X”). Sero Energy will offer consumers perks to encourage take up and for FLATLINE this means additional demand turn up and down.

The continued feasibility for both EV’s and appliances will be continued into Phase 2 however there is a reliance on consumer engagement.

30 SYSTEMS ANALYSIS

OVERVIEW This section looks at how the system is able to communicate between the technology, sensing equipment, the consumer User Interface (UI) and the control system or manager, to understand the options for the FLATLINE phase 2 system architecture and integration. The focus here is the IT systems supporting the project objectives utilising existing partner technologies and capability, with a view to identify a solutions that facilitate a level of vendor agnosticism, redundancy in the event of failures, compatibility between systems and the simplest development requirements for future scalability. Scalability is important as the contribution from dDSR will require large numbers of homes to participate at the lowest cost. The solution needs to be able to adjust as appropriate based on the Grid’s delivery of functionality supporting dDSR opportunities. As part of the study, two existing aggregation service providers (“Aggregators”) were consulted on the solution that they could offer the Project. Either company could fit into the FLATLINE Demonstrator phase effectively as a subcontractor to provide control of the grid / DSO requests and execution. EXISTING CONTROL SYSTEMS MINUS7 USER CONTROL Minus7 system has limited controls from a user perspective. Minus7 are developing an app view which gives basic information on the hot store temperature, system status and ability to turn the system on. The Solar Energy Processor (SEP) requires a demand signal to instigate heating, which is best triggered by a traditional third party thermostat or a smart thermostat with a manual temperature dial, hard wired to the HTU. A smart thermostat allows for control to be performed locally or remotely. Using a smart thermostat would mean the resident should have app access to control the heating and scheduling, via a third party app or integrated into the Samsung app. For efficiency purposes smart actuators should be used to provide zoning capabilities within the home for additional efficiency. MINUS7 SYSTEM CONTROL Minus7 system is controlled by the SEP, which connects to the Minus7 servers via a Global System for Mobile communication (GSM) connection. The SEP builds up the pattern of solar thermal generation and sends this information to the Minus7 servers, which then use their own algorithms to determine activation of the heat pump module to take heat out of the thermal panels. The system currently allows a third party to request heating or hot water turn on / off. A new feature for the purpose of FLATLINE is cloud to cloud services enabling the immersion heater to be enabled to heat the hot store when the grid requests additional demand. SONNEN USER CONTROL Sonnen gives the user to monitor, analyse and control the supply and demand of the household 24/7 through the sonnenPortal or sonnenApp on a smartphone or tablet wherever the user is connected to the internet. • Detailed data on PV production, charge/discharge power and home consumption. • How much of their energy usage is being covered by their PV and storage system combined. • Smart plugs can also be connected to enable the homeowner to remotely switch on/off appliances. SONNEN SYSTEM CONTROL Sonnen has an inbuilt control plane in their battery. This control plane acts as the master controller for intelligent energy management (it can also act as a local Z-Wave hub to control smart devices, although that isn’t necessarily required for this project). The control plane sends data to the Sonnen cloud service (e.g. state of charge, state of health, capacity, charge and discharge commands) to allow for intelligent management, control and patterning, this data is accessible via the Sonnen cloud. It also allows for scheduled DSR instructions to support the provision of energy services. Local API functionality gives access to control participation in energy services from a third party device within the home. Remote API gives access to control participation in energy services response from a third party such as the aggregation services provider ‘aggregator’ operating remotely to the home.

SAMSUNG USER CONTROL Samsung SmartThings provide an app which talks to the Samsung cloud and acts as a front end User Interface for third party system view and control. This means that the data available for the apps and systems provided by Minus7, Sonnen , thermostats (smart heating) provider and future smart appliance/EV charging is all visible via the Samsung app in one place. It also offers the ability to control the heating and any IoT connected devices, directly when OCF compliant, or via their SmartThings hub for Zigbee, Z-Wave or Bluetooth compatible. SAMSUNG SYSTEM CONTROL Samsung SmartThings connectors provides a platform for the cloud to cloud connectivity of the partner systems, simplifying integration between each individual service via API. This supports vendor agnosticism by creating a topology which facilitates simplistic individual element replacement. Samsung also offer data storage capabilities, which should be considered for the project if Sero Energy has the requirement to store their own data for future use. All API calls for data between vendors would traverse the Samsung SmartThings cloud. Samsung SmartThings can also be used to support IoT connected devices, directly when OCF compliant, or via their smartthings hub for Zigbee, Z-Wave or Bluetooth compatible. SMART THERMOSTAT USER CONTROL The smart thermostat is an internet connected device which can be controlled remotely using an app or web portal or locally using a thermostatic dial. The thermostat supplier maintains scheduling functionality so that the user can set “on” periods or “away” periods etc. The app and thermostatic dial synchronize via the internet connection, so the latest change is reflected on both interfaces. The smart thermostat should be mixed with smart actuators to support zoning for additional efficiency, all of which is integrated into the app view. SMART THERMOSTAT SYSTEM CONTROL The thermostat simply sends a demand signal to the Minus7 SEP when heating is required, i.e. target temperature is above current temperature during an “on” schedule within the relevant zone. The patterning of the demand requests is performed on the Minus7 system. USER INTERFACE

Suggested app attributes for user: Sero Energy is looking to provide a ‘clean’ and simple single UI which gives the user the control they need. Feedback through the UI should be basic with separate portals (web based) for prosumers to obtain detailed information on the system performance. The SmartThings platform enables integration of other devices such as voice assistants etc. Control – Heating schedules by zone, hot water scheduling, EV charging preferences. View – System status, i.e. room temperatures, hot water temp. To accommodate the shift to a low temperature heating system the user will set a heating schedule of when they want the system to reach temperature, rather than come on. ADDITIONAL DEVICE USER AND SYSTEM CONTROL Any additional devices or features which need to work as part of the Sero solution will need to either have: Their own cloud services with standard API access (SOAP, REST) allowing integration to the aggregator for system control, or a local interface with relevant data access for the aggregators hub to control. In some cases there may also be the requirement to add a new hub if the local interface is not via standard communication methods (i.e. wifi or Ethernet).

CONNECTING THE SYSTEM OPTION 1. USING AN INTEGRATOR WITH DEDICATED UI

This option uses the Samsung cloud as an integrator in the system, this could also be performed by a Sero Energy cloud if required. This option would complement the use of the SmartThings UI and provide a single interface for the Aggregator. The Minus7 SEP continuously collects data, stores it locally and sends it the Minus7 cloud via GSM7. The Sonnen Batterie collects data every second and sends the data every 5 minutes to the Sonnen cloud via the ethernet/ISP. The Samsung cloud is used to connect all the cloud services and allow full 2 way communication, could also be used to store data so the aggregator could query directly from the Samsung cloud. The Aggregator connects to the Samsung cloud to obtain the required data from sonnen, Minus7 and Samsung. OPTION 2. USING A STAR MESH WITHOUT INTEGRATOR.

7 Minus7 are considering to use ISP to match the other systems.

This options relies on cloud to cloud interfaces between the Aggregator and the technology providers and each interface will require the necessary development of API connections. In this option, there is no integrated app view, so customer user interface provided by the individual technology providers or the Aggregator SYSTEM CONTROL (ALL DEVICES) SONNEN AGGREGATION CAPABILITY sonnen operate an intelligent VPP platform through which they can offer energy sharing and energy services to residential homes by aggregating sonnenBatteries and other small-scale assets, and balancing supply and demand within a community of battery owners - ‘the sonnenCommunity’. sonnen has successfully developed several VPP strategies and applications using the sonnenBatterie units in different markets, including Italy and Germany. Sonnen has adopted different approaches to meet regulation requirements and business models including demand response, frequency control, Blockchain, (scheduled) dispatch, as well as local production/consumption optimization by using the energy prediction engine in each sonnenBatterie. All sonnenBatterie units operate with a local RESTful API. Each user can opt-in to manually control the battery system. This enables individual applications where an external hardware controller extends the sonnenBatterie’s functionality. sonnen also offer commercial customers the opportunity to control charge/discharge of the battery system through their cloud API. sonnen offers a full range of control and VPP applications, from (a) local single-unit live charge/discharge control via a RESTful API, to (b) control of a medium-sized pool of aggregated batteries over our backend, to (c) a virtual energy storage system in the Megawatts capacity with centralised parametrization and offline scenario. sonnen have successfully designed, implemented and tested several applications in the field for scheduled dispatch/charge. Each sonnenBatterie comes with a predictive controller that optimizes production, consumption, charge and discharge. The sonnenBatterie controller uses self-learning algorithms and weather data to forecast likely consumption and generation for the days ahead. For frequency response sonnen use the integrated inverters’ internal measurement and control to respond to changes in the grid’s frequency. Sonnen’s local system controller can adjust the parameters and power output to meet local regulation requirements. Aggregation Services As there is a number of technologies to control in the homes, there is a need for a top level aggregator to take the overall lead in the system control process. It is responsible for building the commitments, auctioning and executing in relation to the grid requirements. The means of doing so is by the aggregator building a plan based on the data received from the vendor systems (via Samsung) and any other sources they require. They then build up a picture of the energy capacity and availability within each home, aggregate it to a higher level and take that data into the DSR auctions to form a basis for commitments. The plan accounts for redundancy within the commitments before being finalised. The Aggregator cloud servers run self-learning algorithms to optimise the system and build a plan for the homes, it queries Minus 7,Sonnen and others for data (via Samsung or locally) and uses data to calculate the plan requirements. The Aggregator sends the plan to a local hub / Sonnen control plane every 24 hours with incremental updates as the plan changes, If a plan is sent successfully then commitment to the grid is made for up to a 24 hour period.

The Aggregator cloud or the “controller” cloud should be built-up using open standards, this will allow it to work with other loads when they are added. For example https://www.eebus.org/en/ which will be made compatible with OCF later this year. DATA EXCHANGE/PROCESSING & STORAGE

The data rates for the energy management are designed to be minimal. Sonnen and Minus7 both sample down to the second on site, but only transmit every 15 and 5 minutes respectively. This means that internet bandwidth is not a cause for bespoke design, however reliability is required for optimal efficiency. Given the potential needs for immediate power release requests alongside the scheduled DSR windows, implementing a backup solution would be beneficial for the internet connectivity. This could be in the form of a GSM solution on site, or else dual connected internet. SONNEN GATHER AND STORE: Solar generation and consumption data, location data, Weather data, AC voltage, current and frequency, DC voltage and current of each battery module, Temperature, State of charge of the battery, State of health of the battery MINUS7 GATHER, STORE AND USE IN THEIR PATTERNING: Current KW heat from condenser, hot and cold collection, combined condenser and Roof duty, temperature differentials across exchangers, rate of heat flows, daily and total view of Kwh supplied and used by SEP, cold, hot store and roof temperatures, flow meters, home energy demands and usage Sero only needs data storage in this solution if they want to keep ownership of data related to usage and generation. Each system performs their own data gathering and will give access to that data for Sero throughout the use of their equipment and services. Having the data collated into one store would give Sero long term data ownership for future modelling and patterning etc. SYSTEM REDUNDANCY

Redundancy covers multiple facets. Home to internet connectivity, Cloud to Cloud services, User experience, plan execution. Home to internet connectivity is covered in the recommendations section under Internet Connectivity. DSL with 3G backup for retrofit and dual connected ISP extended LAN for new builds. Cloud to Cloud services are resilient by design. The Aggregators use AWS additional ECB service to provide extra intra-cloud resilience. User experience is provided by the individual system’s ability to run autonomously, even when communication is out of service. Minus7 is fully controlled by the on-site SEP, so in the event of a communication failure, continues to serve the homes demand for heating but would not receive instructions to participate in DSR. Sonnen reverts to self-consumption mode, so much in the same way as Minus7, the system would continue to manage local power needs intelligently in the event of an internet failure, and can continue participating in any predefined DSR plans.

CYBER SECURITY

Cyber security has comprised an important consideration for the work underpinning this feasibility report, though given the stage of the development this is necessarily focused around understanding the risks and challenges as much as identifying solutions. Should the Demonstrator phase proceed, this work will become the basis for the

35 detailed development undertaken once the solution for implementation has been finalised. However, some key elements or principles of cyber security have already been identified that are agnostic of the control system configuration (and can therefore be set out at this Feasibility stage), and these are summarised below CLOUD AND CONTROL LEVEL SECURITY The precise nature of cyber security for cloud operations can vary on the implementation, however some key principles can be applied across all of these, which include: • Appropriate firewall topology / rules in place to protect the cloud based services. This helps prevent hackers accessing the system at a control level. • Randomization for asset identification. This limits any impact should a hacker access at the control level by reducing the ability to identify and therefore attack all assets by identifying one. • Intrusion Detection. The system will have intrusion protection protecting the control level. This offers the ability to identify malformed or malicious packets targeting the control system and block those packets before a stream manages to either compromise security or availability (i.e. offers protection against hackers and those wishing to block the systems uptime with denial of service attacks) • Strong Passwords: We will ensure any passwords used for system control are at least 12 characters and a mixture of alpha, numeric and special characters. • Best practice TLS. It is like that device controls will continue to uses TLS. The project will ensure all TLS encryption should follow best implementation and management practices. All companies should maintain a process of firmware updates and security patches as vulnerabilities are identified / exposed, and all communication by selected vendor equipment to and from the internet and cloud to cloud is secured by way of TLS encryption, providing the current industry standard for secure communications. The FLATLINE project uses a number of new technologies combined into the novel solution proposed here. Each of these systems have acceptable internet security standards inherent to their designs, though through the ongoing project each partner will also be maintaining their own software testing and update processes to fall in line with best practice (and BEIS mitigation requirements). Additionally, the FLATLINE project includes close collaboration with Samsung and their SmartThings platform. This provides a further robustness for cyber security (as well as the future potential expansion to home appliances). In order to use the Samsung SmartThings platform, a device manufacturer must submit their device for a security review based on the security requirements developed in OCF (“Open Connectivity Foundation”, an/the Internet of Things standard):This effectively means that the other FLATLINE partner system security will be reviewed by Samsung. The goal for the OCF security architecture is to protect the resources and all aspects of hardware and software that are used to support the protection of resource, which in our case includes the FLATLINE control system. From OCF perspective, a device is a logical entity that conforms to the OCF specifications. In an interaction between the devices, the device acting as the server holds and controls the resources and provides the device acting as a client with access to those resources, subject to a set of security mechanisms. The platform, hosting the device may provide security hardening that will be required for ensuring robustness of the variety of operations described in this specification. 1) The client establishes a network connection to the server (device holding the resources). The connectivity abstraction layer ensures the devices are able to connect despite differences in connectivity options. 2) The devices (e.g. server and client) exchange messages either with or without a mutually-authenticated secure channel between the two devices. PHYSICAL AND USER LEVEL SECURITY The physical FLATLINE system represents one possible route for the cyber security of the control network to be compromised in its entirety, or to a local level (such as an estate of homes or group of devices), as well as to interfere with the operation of the individual property. This represents both a cyber security threat in general, but specifically

36 a threat to both the optimal performance of the FLATLINE system and the provision of dDSR services to the Grid over and above this baseline. This report covers below (and also under “Building Communications”) the options around delivering connectivity for the homes, however the final resolution to these in the Demonstrator phase will reflect the benefits to cyber security. In this regard, this feasibility has been identified that the following are preferable security solutions for FLATLINE’s operation: • A dedicated, independent internet connection to each home to a secured termination in the property, • A physically separate, dedicated Local Area Network (LAN) to a secured termination in the home, • A Virtual Local Area Network (VLAN) with all internet physical and logical ports locked down aside from those required for FLATLINE, thereby segregating occupant and system traffic within the home. Each of these options reduces the risk of the user compromising the connectivity manually or by way of an infected device, since accessing the system will be restricted to prevent either users or infected devices doing so. Each of these approaches would also ensure that the current lack of authentication on the local API of the sonnen battery would be resolved (though this is also being resolved by them and likely to be in place for the Demonstrator). CYBER SECURITY VALIDATION The specific cyber security solution to be implemented will be developed under the Demonstrator phase with an awareness of the specific implementation site and its restrictions or opportunities. In order to ensure the resultant system is robust and secure, prior to “active control” operation, the FLATLINE project will look to convene a “hackathon” event or mini-event. These bring together relevant experts and provide them with an understanding of the system, before then challenging them to try and compromise (hack) the system operation. Whilst not categorical proof of security, hackathons are therefore accepted as a useful tool to trial a system’s security, and FLATLINE will adopt this as part of the project’s wider cyber security measures. INTERNET CONNECTIVITY OPTION 1 Install a Sero Energy dedicated internet connection per home. The devices should be in a secure and accessible (for maintenance) location that the resident does not have access to. The bandwidth requirements are minimal as there is no requirement for real time delivery and transmission intervals are 5 minutes minimum. The recommendation would be for a 2Mbps service with an optional 3G/4G backup solution. The resident would need to request their own internet connection as per normal. OPTION 2. Install a Sero Energy dedicated internet connection per home. The devices should be in a secure and accessible (for maintenance) location that the resident does not have access to. The bandwidth requirements are minimal as there is no requirement for real time delivery and transmission intervals are 5 minutes minimum. The recommendation would be for a 2Mbps service + customer bandwidth requirements, with an optional 3G/4G backup solution. The resident would piggyback off the Sero connection, with traffic segregated on the home router. Sero and resident would have different IP ranges and VLAN allocations. Sero would act as the ISP for any customer requirements such as bandwidth upgrades or internet outages etc.

OPTION 3.

For new builds or retrofit estates only. Install a Sero dedicated internet LAN per estate. There will be a requirement for dual ISP routers and switches external to the homes providing resiliency. There would also need to be a router/switch within each home which should be in a secure and accessible (for maintenance) location that the resident does not have access to. This would be in the form of a redundant star topology, between each home and the two separate ISP connection points. Each ISP connection point should connect to a diverse exchange for the purposes of redundancy. In this instance, the physical medium would be shared between the user and Sero internet connectivity. Traffic would be segregated on the home router to ensure that the user traffic does not meet or interfere with the Sero Energy traffic. Sero Energy and resident would have different IP ranges and VLAN allocations. This would place Sero in full control of internet security and reliability, thereby reducing risk of DSR commitment failures. It does mean Sero are effectively acting as a local ISP for the estate, allowing for connectivity cost offset by charging the individual homes for their internet connectivity. CONSTRUCTION & POST OCCUPANCY

CONSTRUCTION REQUIREMENTS

This section investigates the changes required to the physical construction of the homes in order to implement Sero's energy management system to provide occupants with fixed, low monthly fuel bills and undertake domestic Demand Side Response to the National Grid. This section therefore identifies the key changes to fabric, services and connectivity that would enable the optimum implementation of the FLATLINE model. It should be noted that these requirements are envisaged as the best requirements for new build properties; lesser specifications for new build or that may be achievable for refurbishment properties will still be viable for FLATLINE, but will deliver reduced benefits. FABRIC PERFORMANCE A performance specification has been created for the site to ensure that the homes fully satisfy the developers and Sero Homes’ desire to deliver a ‘fabric first’ approach to construction, and to underpin this with clear, measurable requirements that can be included in the relevant construction contracts and sub-contracts. The overall intent is not necessarily to raise the bar for the homes’ overall energy performance; the obligation remains simply to achieve Building Regulations compliance. The specification is not the most ambitious that can be achieved for any of the building elements or junctions, but represent a good level of realistically deliverable performance adhering to the following key criteria:

1. Standard must be achievable in a number of different ways or construction types (masonry, timber etc.) 2. Have achievable solutions for any exposure zone, specifically including using a masonry inner and outer wall leaf 3. Not require materials which are not believed to be readily available to the construction supply chain in the UK (transient stock issues excepted) 4. Not require site skills that are significantly more complex/unusual than properly implemented good practice on site by the relevant trades 5. Have examples of construction build-ups or details that illustrate compliance, or that are highly comparable and would illustrate the compliance with minor modifications 6. (For walls) Be achievable using a masonry inner and outer wall leaf construction and at least one other form of construction (such as timber frame) 7. (For walls) Be achievable within an approximately 350mm total wall thickness, even in exposure zone 4 The resulting fabric performance specification is summarised in Table 6.

TABLE 6: FABRIC SPECIFICATION FOR DWELLINGS AT THE SITE

BUILDING SERVICES As highlighted in the Technical Analysis section, the FLATLINE pilot project homes will be "all electric" and no gas installation is required to the site. The key building services for the pilot project will comprise: 1. Minus7 mini-district solar thermal linked heat pump with mini-district heat store, 2. Minus7 integrated photovoltaic panels and associated electrical inverter, 3. Sonnen electrical storage battery (with integral inverter), sized between 2.5 and 7.5kWh, 4. Domestic consumer unit with metering as noted below, 5. 125-210 litre hot water tank with back-up immersion heater feeding heating and hot water supplies, 6. 'Wet' heating distribution network (mix of underfloor heating and low surface temperature radiators), 7. In-line heat meters on hot water pipework as noted below, 8. Mechanical fan extraction from 'wet' rooms, with individual heat recovery where possible, 9. LED lighting will be used throughout the homes, except where not permitted, Finally, in line with Welsh Building Regulations; 10. Domestic sprinkler system with either pressurised mains or tanked water reservoir. Further details on the Minus7 and Sonnen systems can be found in the relevant appendices to this report. Additional details on the remaining building services are not appended at this stage as they comprise 'typical' construction systems in widescale use, and the final selection of the specific products has not yet been made for the pilot site.

BUILDING COMMUNICATIONS The System Analysis section details the complexities and options for connectivity to the homes and how these will network together. For the physical construction, each of the homes on the pilot site will be built beyond compliance with the recent Building Regulations Part R. This will provide for the homes which are to be sold on the open market to have their own internet connection installed (and associated WiFi) and to ensure they have the freedom to switch their service provider as they wish. To achieve this, a separate/partitioned high speed wired connection will be installed into the open market sales home that is dedicated to the core FLATLINE systems within the house - this will be terminated separately to avoid confusion or interference with the Network Termination Point provided under Building Regulations for the occupants' use. Homes intended for rental use will either be installed with the dedicated FLATLINE connection and capacity for the residents to install their own choice of internet service provider via the provided Access Point and Network Termination Point in the same fashion as open market sales homes, or will have a high speed internet provision 'bundled' with their overall tenancy rental. If the 'bundled' route is selected, the FLATLINE core systems will be partitioned from the occupants' access and will be controlled with dedicated bandwidth assigned to it. This will achieve a similar separation to the home market homes and provides for confidence in the robustness of the network to be able to deliver FLATLINE control messages and receive data as required. SENSORS & MONITORING A range of monitoring equipment is intended to be installed in the homes to measure their energy usage, to assess the operation of the FLATLINE concept at Demonstration stage, and perhaps most critically to gather data for the future iterative development of the Control Logic that underpins the Sero Energy model. The following sensing and metering equipment is therefore proposed – further information on the individual need for these as been included in the relevant appendix rather than expanded upon here: 1. Weather/External Environment, all half hourly data (or less): a. Wind speed average for period (mph) b. Wind speed maximum in period (mph) c. Wind direction (min. 16 point compass), d. Rainfall (mm) e. Temperature (˚C) f. Relative Humidity (%) g. Dew Point (˚C) h. Atmospheric pressure (hPa) i. Solar irradiance (including cloud cover) (W/m2) 2. Internal Environment metering, all half hourly data (or less): a. Living room internal temperature (˚C), b. Living room internal relative humidity (%) c. Living room carbon dioxide levels (PPM), 3. Renewables metering, all half hourly data (or less): a. Total energy generated (kWh or kWht) b. Electricity export meter (kWh) 4. Electricity Usage, all half hourly data (or less): a. Total electrical energy used (kWh) b. Regulated electricity usage (kWh) c. Unregulated electricity usage (kWh) 5. Water Usage, all half hourly data (or less): a. Total water usage (litres) b. Hot water usage (litres), 6. Occupant Information* a. Basic Occupant Information including; i. Number of occupants ii. Number of occupants typically away from home in the daytime (i.e. at work) iii. Age groups of occupants b. Survey response(s) from Occupant Surveys

*Occupant Information may be subject to GDPR/data privacy and might require their consent.

40 INNOVATION AND TECHNOLOGY READINESS The FLATLINE project uses a combination of new technologies in a novel combination, with the object of providing low, fixed fuel bills to residents whilst providing domestic Demand Side Response to the Grid. Overall, the FLATLINE approach is moving between TRL Level 3 and 4 with the work undertaken in (and in parallel with) this feasibility study. These levels are defined as the “Analytical & Experimental Proof of Concept” Level, which is TRL 3, and “Technology…sub-system validation in a laboratory” as TRL4. These are summarised as: “TRL3: Analytical studies and laboratory studies to physically validate analytical predictions of separate elements of the technology are undertaken. Examples include components that are not yet integrated or representative.” “TRL4: Fidelity of sub-system representation increases significantly. The basic technological components are integrated with realistic supporting elements so that the technology can be tested in a simulated environment. Examples include “high fidelity” laboratory integration of components.” FLATLINE has undertaken analytical predictions of the separate technologies based on detailed, modelled examples (TRL3), but has also undertaken work to link the supporting elements to test the integrated technology in a simulated environment using “higher fidelity” models than earlier investigative works (TRL4). As such, the overall FLATLINE concept could be considered to be at TRL3½. Underpinning the FLATLINE Technology Readiness Level is the readiness of the new technologies that are being applied in this novel approach, which broadly comprise the sonnen battery system, the Minus7 heating system, and the control aggregation system. Each of these supporting technologies are new and developing, but are also commercially available. The sonnen battery has a significant number of installations beyond the UK and a growing number here, hence the battery technology is as TRL9 (“…System qualified through reliability and maintainability demonstration in service”), whilst the sonnen control and clustering system (one of the aggregator options) has not been deployed ‘live’ in the UK, and is therefore closer to TRL7. Minus7 also have operating systems in the UK that can demonstrate TRL9, however they are actively engaged in developing an enhanced control system that will be capable of optimising performance based on more than just heat pump coefficient, and this development is closer to TRL6. Finally, energy aggregation platforms such as those provided by PassivSystems and others (see “System Analysis” section for more detail) are also providing commercial services commensurate with TRL9, though for some providers this are only now approaching the residential/domestic market and have more provision for industrial and in these instances (varying by provider) they are at TRL6 to TRL8. FLATLINE as it stands therefore represents a novel application at approximately TRL3½, which is based on individual elements of new technology that have proven performance (TRL9) but that are also innovating (TRL6-8). The Phase 2 Demonstrator will allow the FLATLINE project to move from this level to a forecast TRL8 during the project duration, and TRL9 subsequently. TRL8 is “Actual technology system completed and qualified through test and demonstration”, and is defined as: “Technology has been proven to work in its final form and under expected conditions. In almost all cases, this TRL represents the end of Demonstration. Examples include test and evaluation of the system in its intended … system to determine if it meets design specifications, including those relating to supportability.” The Demonstrator will see the implementation of the FLATLINE proposal on a live site in South Wales (this may not be since a number of options are available). The project will develop the Sero Energy control system and integrated the individual new technologies and communication requirements into the construction of the new homes (themselves funded outside of the demonstrator). These homes will be completed, commissioned and occupied during the FLATLINE phase 2 project. As highlighted in the project programme, the system will run in “learning” mode for approximately six months before switching to active “control” operation: At this point, the FLATLINE system will achieve TRL8. The homes will, however, continue to be occupied after the end of the Demonstrator project and therefore over a period of time the system will accumulate information on its reliability and maintainability. Whilst envisaged as occurring after the end of the Demonstrator, this represents Technology Readiness Level 9 – “Actual Technology System qualified through reliability and maintainability demonstration in service”. In accordance with the business and exploitation plan, the intention is that the FLATLINE system will also be operating on other sites by this point, which will further bolster this evidence in operation.

41 MARKET POTENTIAL AND EXPLOITATION PLANS OVERVIEW OF DSR REVENUES

The energy system is changing, there is a decreasing number of generators at the transmission level and increasing number of renewable generators on the distribution network. National Grid needs to manage the system to ensure the UK has sufficient capacity to meet demand and also ensure that its operated within optimum parameters. Renewable energy has experienced significant growth since the turn of the century as a result of policy drivers and incentives such as the Feed In Tariff and Renewables Obligation. This raises the increasing need for capacity mechanisms and balancing services to effectively manage the electricity system of today. Flexibility in the system has historically been the ability for large generation plant to curtail or turn up generation. In recent years, large consumers and industrial users have participated in balancing services and there is now potential for residential and small business. This evolution has been driven by advances in software and artificial intelligence that allow a large number of small devices to offer capacity in aggregate. The Project will model the flexibility in the pilot site and compare that to the current balancing services market, which have been outlined below. It’s important to note that this area of is undergoing significant change across three main areas; 1. DSO Services – Due to the increase in embedded generation and self-generation it is becoming more difficult for National Grid to balance the system as it has no view of the generators connected to the Low Voltage (LV) and High Voltage (EV) network. The Distribution Network Operators are in a transition to become Distribution System Operators and take responsibility for balancing the network. This is at pilot stage for most DNO’s, Western Power Distribution are running a number of trials8 such as the Flexible Power9 program in the midlands. This change to a DSO led services model is considered to be a positive change for the FLATLINE Project. This should enable lower minimum capacity thresholds for DSR to enter the market. 2. System Needs and Product Strategy (SNaPS)10- The large number of balancing providers has led to a complicated system with many products offered by National Grid. This has led to a strategy of rationalising and standardising the products to simplify the process and therefore enabling more entrants and greater competition. The changes to National Grids balancing services is seen as a positive change for the residential sector as it reduces complexity and will enable greater participation of DSR. 3. Regulatory change – In 2017, Ofgem released the Smart Systems and Flexibility plan which sets out a number of actions to reduce regulatory barriers for smart technologies. Particularly relevant is Action 2 which focuses on barriers to Smart Homes and Businesses.

8 At the time of writing there are no trials located in Wales. 9 https://www.flexiblepower.co.uk 10 https://www.nationalgrid.com/sites/default/files/documents/8589940795- System%20Needs%20and%20Product%20Strategy%20-%20Final.pdf

All of the points above show an encouraging direction of travel for policy and incentives, the following section looks at the current balancing market however its anticipated that there will be more options going forward. CAPACITY MARKET

The Capacity Market (“CM”) is one of the policies introduced under the Governments Electricity Market Reform programme. This policy is designed to ensure that capacity is available to meet demand and prevent blackouts, this is typically achieved by Generators offering additional capacity for a period of time or a turn down in demand. Two auction processes are run, one secures demand four years ahead of time (T-4) and the other one year ahead of time (T-1). The descending clock or ‘Dutch-Style’ auction starts with an oversubscribed capacity at a high clearing price, as the price drops then capacity falls away until the remaining capacity meets the target capacity. Contracts for Capacity Market are available up to 15 years which makes the CM the most appealing balancing service to investors. In order to participate in the Capacity Market auction, the contracting party or Capacity Market Unit (CMU) will need to prequalify and comply with the CM Rules. DSR is eligible to enter the CM and is placed into two categories of ‘Proven DSR’ and ‘Unproven DSR’. Proven DSR has completed tests to demonstrate that the level of DSR capacity is deliverable. The minimum entry requirements for DSR is 500kW having been reduced from 2MW to encourage a greater number of DSR entrants to the CM. The most recent auction on the 8th February 2018 (T-4) cleared at a price of £8.40/kW per year, securing 50GW of capacity. In total, 67.9% of bidders secured Capacity Agreements for delivery in 20/21. DSR makes up very small but increasing proportion at 2.39% of the capacity secured, nearly all Unproven DSR. The auction on the 1st February 2018 (T-1) cleared at a price of £6.00/kW per year and secured 5.8GW of Capacity for delivery in 18/19. DSR made up a slightly larger proportion of the secured capacity at 6.47% in the year ahead auction. Failure to deliver capacity results in a penalty, this project will look at how the portfolio of homes may at all times provide Capacity for the required duration of up to 4 hours. The most likely occurrence of a CM event would be on a weekday evening peak during the winter months. Availability: at all times Utilisation: up to four hours as per guidance Minimum Entry Capacity: 500kW for DSR Most Recent Price : £6/kW per year (T-1), £8.4/kW per year (T-4) NETWORK & POLICY CHARGES

This consists of a series of charges placed on suppliers in recovering system costs and policy costs such as the CM charges. There is incentives for flexibility by avoiding periods of peak demand on the network and therefore avoiding the charges. Distribution Network Use of System (DUoS) charges – DNO’s assign weekday and weekend windows for Green, Amber, Red and Super Red rates for consumers. These rates are determined by the DNO and change based on the type of consumer, connection (LV,HV or EHV) and the region. Capacity Market Supplier Charge (CMSC) – Suppliers are charged on metered volumes between 4pm and 7pm on weekdays between November and February. Transmission Network Use of System (TNUoS) – Chargeable on consumption during the ‘triad’ periods, the three periods of highest demand separated by 10 days between November and February. Triad periods are not notified and some suppliers attempt to predict their occurrence however this is becoming increasingly difficult. Triad payments are also one of the ‘embedded benefits’ that is planned to reduce up until 2021 to almost zero. Network avoidance charges provides great opportunity for the FLATLINE project. The model used to naturally avoids the network charging periods as part of a default operating strategy to run the homes at the lowest costs. South Wales charges: DUoS – 10.56p/kWh (red), 2.15p/kWh (amber) 1.57p/kWh (green) TNUoS – 5.55p/kWh (weekday peak times).

WHOLESALE MARKET

Electricity is traded for each half hourly Settlement Period based on the framework of the Balancing and Settlement Code (BSC) that suppliers adhere to. The difference between the Credited Energy Volume (i.e. the meters) and the Contracted Energy Volume (i.e. the trading) is the Imbalance Energy Volume (i.e. the system). The Balancing Mechanism administered by National Grid is used to balance the system and ensure security of supply. A supplier is exposed to ‘Imbalance Risk’ if they need to settle volumes within the Balancing Mechanism, this can expose them to high clearing prices. DSR is not eligible for entry into the Balancing Mechanism however the flexibility can be sold on the wholesale market ahead of time in order to reduce the suppliers exposure to imbalance. This could offset the imbalance risk and create value for both the DSR provider and the supplier. NG doesn’t have view of generators <100MW and there is no grid code requirements to submit Final Physical Notification of generation in the Balancing Mechanism, i.e. their output isn’t fixed 1 hour before gate closure. These generators have an opportunity to respond to the System Prices or cash out prices in real time and generate at the higher system price. The Net Imbalance Volume (NIV) is a feature of imbalance pricing, generally the larger the NIV then the greater the price. Parties with live access to Bids and Offers can see NG accept in real time and dispatch embedded generation to capture the spill prices. This is referred to as ‘NIV chasing’ and is often utilised by DSR operators. This approach however can be risky as the clearing price can vary and that volume of flexibility may be better traded prior to the gate closure. For the FLATLINE project, the opportunities for wholesale/trading revenues will be dependent on the agreement and relationship with the licensed supplier. At this stage it is difficult to predict the value streams with the supplier however the trading of flexible volumes will be investigated further as part of a demonstration project. This report has used the 2017 Day Ahead Wholesale Prices from 2017 (Nordpool, GB) BALANCING SERVICES

NG as System Operator has the responsibility of balancing the system on a second by second basis, there is an obligation to maintain the system frequency at 50Hz +/- 1Hz. Although in reform at the moment under the SNaPS review, there is a number of services applicable to this Project. FREQUENCY RESPONSE As generation drops off then the System frequency starts to drop and likewise if the demand drops off then System frequency starts to increase. Frequency response products help maintain and regulate the frequency and different assets are used to provide different solutions depending on the speed of response. Dynamic Response – Rapid responding assets such as batteries respond to frequency variations in less than a second to help mitigate the change. Static Response – Full response is required by slower responding assets (i.e. pumped hydro) when the frequency deviates by a set amount. As this project uses battery assets that are virtually aggregated together, subject to inbuilt metering equipment it will be possible for a frequency response service. Batteries are able to respond in very short time frames and potentially <1second which means that they are ideally placed to provide Dynamic Response or Firm Frequency Response. Tenders for frequency response are run on a monthly basis in an auction process. Successful bidders are paid an availability fee and a number of fees based on utilisation. Availability: Ability to choose windows for service provision Minimum Entry Capacity: 1MW FFR value:£11-15 /MW/h

SHORT TERM OPERATING RESERVE STOR is NG’s service for ensuring there is enough Reserve Capacity to meet demands. Whilst appearing similar at first to the Capacity Market, STOR is more of an operational requirement whilst the Capacity Market issues long contracts to encourage investment in new capacity. There has not been a CM event to date however STOR utilised >100,000MWh of reserve response from March 2016 to April 2017l. STOR requires that response be held for a minimum of 2 hours. Availability: Morning and evening windows Minimum Entry Capacity: 3MW STOR Value: £1-2/ MW/h, £100-150 /MW/h for utilisation. DEMAND TURN UP The growing proportion of intermittent renewable energy on the grid has created periods in which the generation is high (i.e. windy nights or sunny days) and demand is low on the network. To reduce generation is difficult as this may require wind farm operators to turn off which can be an expensive method or lowering the imbalance. These operators are paid ‘constraint payments’ which can be higher than the lost revenue to account for wear and teareaear, etc. In 2017, £100m was paid by National grid to turn off wind generation at periods of low demand. DTU allows NG to call on demands that can increase consumption to meet the generation at a lower cost. This typically occurs during the night or on afternoons at the weekends, in 2016 the service procured 309MW and was used 323 times for a total of 10,800MWh. Availability: Ability to choose windows of availability Minimum Entry Capacity: 1MW DTU Value: £3-4 /MW/h availability, ~£60/MW/h utilisation REVENUE STACKING DSR operators typically ‘stack’ balancing services revenue streams as it is possible to enter multiple services simultaneously. There are some restrictions however and the right strategy for entering the various markets can be challenging for operators and investors. CAPITAL COSTS HOUSING DELIVERY Residential development has reached a difficult position where the ‘business as usual’ approach leaves little room for innovative solutions that come at a premium. Land availability and value is by far the most prohibitive barrier in building new housing, especially for smaller developers looking to push the boundaries of energy efficiency and go beyond regulation. On average an Energy Positive home comes at a 15-20% premium on a ‘traditional’ home with no generation and a gas heating system. Sero Homes is targeting sites that are below market levels, either through Local Authority partnership where the environmental and social benefits are realised or because the sites are outside the Local Development Plan and a ‘green agenda’ is favourable with planning departments. This approach is designed to ensure that the short term ‘premium’ associated with Energy Positive homes is accounted for in the financial viability of the project. The homes being developed by Sero will compete with the existing market and seek to offer a net saving when all living costs are considered i.e. rent, bills, transport and through life servicing costs. Where this approach is not possible, there is opportunity for initial projects to rely on Government subsidy such as the Welsh Government Innovative Housing Programme or the Renewable Heat Incentive. However, subsidy is short lived and additional value streams associated with Energy Positive homes need to be realised in order to make future developments viable in the absence of regulatory change. It is anticipated that there will be a number of external factors affecting the feasibility of Energy Positive homes in the future; 1. A continuing decline in technology costs driven by global markets, 2. Consumer interest, following the trend of electric vehicles,

3. Financial incentives i.e. taxation relief, green mortgages, borrowing incentives, affordability definition (see below) 4. Regulatory change i.e. building regulations and new ‘net zero’ energy policies, 5. Additional value such as DSR capability. Affordability is currently considered in one dimension, energy costs are inherently linked to the building and currently not considered in the affordability definition. If living costs were considered in aggregate then a proportion of the energy saving could be used to pay back capital costs for those technologies that brought the benefit. As outlined in the Phase 1 application, the host project does not seek funding for the technology which is being installed to reduce bills, improve air quality and carbon emissions. It is important however that the importance of the additional value being investigated in this report is recognised, this has the potential to tip the balance of feasibility and accelerate the transition to sustainable housing delivery. The Phase 2 application of the FLATLINE project has two potential host projects each with funding secured outside of this Domestic DSR demonstration. The project (modelled in this report) will start construction at the end of the year and the Sero Homes project with NPTCBC is anticipated to start construction in Q2 2019. Each of these projects provides a suitable host project for the demonstration of FLATLINE. ENERGY MANAGEMENT SYSTEM The requirement for this project is to demonstrate that further investment in a smart energy management system is a feasible business plan. The Project utilises a mix of established and emerging technologies in a system that has not been combined previously. Therefore there will be investment required in order to provide the optimum system required to be simple for consumers, enable DSR and scale efficiently. It is worth noting that there is significant economies of scale with creating a system that can be expanded in future to actively manage thousands of homes across the country. Capital costs for the FLATLINE project and requirement of the Phase 2 demonstration project centre around the system of communication and control required to use the assets in the homes for DSR (See Financial Information). This involves development of API and control methodology to enable the hardware to exchange information on the system and for the platform to analyse, optimise and issue control signals. This development is ultimately scaleable with the same technology partners, additional costs will be incurred when new technologies are brought into the platform. CONCLUSIONS

- Wholesale market and imbalance market trading has not been considered in this report and will be investigated further in Phase 2 through a relationship with the Licensed Supplier. - Network Avoidance offers significant savings to the consumer that can offer returns to the operator through a benefit sharing mechanism. The table above proposes that the majority of the savings (95%) are passed through to the consumer to reduce energy costs however this could be shared with the ‘funder’ of the technology (i.e. the developer or Energy as a Service provider). - Frequency Response currently offers good potential for income as batteries are able to respond instantly, the short periods of utilisation correlate well with these types of residential storage. Care will need to be taken to choose windows of availability carefully to avoid peak periods and cross overs with other balancing services such as DTU. - The system as modelled in this report is less compatible with Reserve/Turn Down products as the homes are already turned down and periods of high demand to benefit from Network Avoidance. - Demand Turn Up offers a good opportunity in the scaling up of the FLATLINE project, there is good opportunity to further increase capacity for minimal additional capital cost (i.e. extra Lithium Ion storage, larger heat stores and integration of EV’s). - The portfolio of homes will need to exceed 1000 homes in order to enter DSR markets without sharing revenue with external aggregators. - There is an enormous efficiency of scale possible with digital systems, on its own the FLATLINE demonstration project would not be a viable investment however at 1000 homes there is justification to spend £800k-£1m in CAPEX to enable the DSR should the system prove to be successful in demonstration.

The tables above demonstrate that there is considerable scope for additional value in home energy generation and storage systems beyond decarbonisation and cost savings. OPERATIONAL COSTS The DSR system will mainly consist of a virtual platform that receives inputs from various sources, determines a response and issues control signals to deliver an outcome. Much of the system uses Artificial Intelligence and is largely machine driven, once operational and with large amounts of historical data to reference it is anticipated to run with minimal operator supervision. The operational costs largely sit as licensing/services costs with the aggregation provider for the homes. At this time it is difficult to foresee the revenue potential for homes, therefore it is likely that the costs will be linked to revenue with the aggregation services provider taking 10-15% of revenue to provide the service. Other operational costs include data storage costs, customer service (catered for through the licensed supplier), usual business overheads and costs associated with a working capital requirement (i.e. to provide any bid bonds etc.). It is anticipated with the current understanding of the revenues/costs that 1000 homes in management offers a viable business proposition to offer DSR.

SYSTEM COSTS AND CYCLE LIFE

48 UK & INTERNATIONAL MARKET SIZE AND JOB CREATION

The FLATLINE project focuses on extracting maximum value from a changing residential sector and new housing models. The UK has fixed targets to reach net zero emissions by 2050 and the residential sector makes up 23% of the carbon emissions, to reach our goal then housing will need to change rapidly as 80% of the homes to exist in 2050 have already been built. Decarbonisation of homes will undoubtedly feature generation at source, most likely through rooftop building integrated PV. The mismatch between generation and demand, demonstrated clearly in this report will lead to a growing requirement for energy storage in various forms. The business exploitation model for the FLATLINE approach of using new housing models to also provide DSR means that its directly linked to the growth of zero carbon or ‘net zero’ housing in the UK and heat decarbonisation strategy. The housing crisis has also driven a new agenda to enable more homes to be built each year, the Government expect 300,000 new homes a years is required to meet the UK’s growing population. Linked to this is both the growth of the Build to Rent sector and a rise in institutional investment into housing and an exponential growth in electric vehicles. This project has an opportunity to create new value streams for homes with integrated renewables that will help enable the transition that’s needed in housing. Based on the findings in this report, 64,000 homes could offer the entire Demand Turn Up volume procured in 2017, this is 6.4% of the Governments targeted 1 million homes in 5 years. On top of the flexibility offered by the system, these homes could offset the need to generate by 200-250MW by not placing any peak energy demands on the network. The solution being delivered for FLATLINE is also retrofittable to existing homes, where their typically lower fabric performance presents higher demands and hence greater potential for shifting of energy out of peak times. The UK Government’s BEIS “Clean Growth Strategy” published in October 2017 sets an aspiration that all fuel poor homes (and as many privately owned homes as possible) are upgraded to EPC “C” or better by 2030, which includes the 850,000 homes not currently connected to the gas network. FLATLINE presents an opportunity initially to these off- gas homes, and subsequently to the 23.4 million homes as part of wider energy refurbishment works, to deliver not just lower cost bills, but through matching demand to generation, lower carbon and better Grid integration. Sero Energy’s USP is firstly that it forms relationships with partner organisation to help enable the technology solution during the design & build stages of the project (supported by Sero Homes). These projects will then go on to be managed by Sero Energy or the homes will be sold with the Energy Service offering as a pre-installed service. The energy service offering is also an innovative approach, customers will see a joined up approach to a User Interface and have the ability to learn more about the technologies, if they wish. The strategy from the Sero team is to approach this new housing model and energy solution on all fronts by developing projects and attracting institutional investment into Energy Positive homes. Energy and housing have spent too long being considered as separate areas of the market and this project shows that innovative new thinking can achieve targets on both sides whilst ultimately benefitting the consumers. Competition in this space will come in slightly different forms; Suppliers will expand their service offering to include supply of technology once the additional value is realised in the wholesale market. Aggregation services providers will diversify into energy supply and develop customer offerings and renewable energy developers such as those developing commercial scale battery storage will diversify into more decentralised opportunities. Sero Energy however through its relationship with Sero Homes will have one foot in the door of the housebuilding ng industry which will give it commercial advantage. The project offering is able to offer additional growth by working with a number of technology providers. There is opportunity for Sero Energy to expand its services into the Electric Vehicle market and offer a suite of home charging options including the emerging ‘Vehicle to Home’ (V2H) technology. In the longer term, there is also scope to better match new and existing generation projects (through relationship with Eco2) to the demand of the housing. This approach will increase the feasibility of renewables projects and reduce costs for consumers with Sero Energy acting as the link between the two sides. The FLATLINE solution is exportable to any country in the world, even if the system conditions change.

49 CONCLUSIONS & NEXT STEPS KEY RECOMMENDATIONS

The key finding of this report is that the FLATLINE proposal can be evidenced through a detailed, modelled feasibility assessment to be a viable business case. FLATLINE has been shown to be capable of delivering fixed, low bills to occupants through grid dDSR services, based on the detailed work undertaken. This work has included consideration of the legal and regulatory barriers, the energy generated and demanded by a typical site, what controls and components will be required, and finally how a secure, safe system can be constructed. The key recommendation of this report is therefore that the proposal is supported to deliver a real-world demonstrator of the FLATLINE proposal, enabling the detailed feasibility model to be developed in a large scale proof-of-concept.. WIDER CONCLUSIONS

There is a considerable volume of detailed work underpinning this feasibility report and the conclusion that FLATLINE presents a viable solution to a cheaper and more harmonious use of homes and the Grid. This work has made a contribution to the more detailed understanding of this interaction that should inform future residential development and refurbishment as well as how the energy networks engage with them. These include: STORAGE INCREASES TOTAL ENERGY DEMAND Whilst the use of residential storage allows for demand shift and other Grid services, reduces energy costs and (through carbon intensity on the Grid) reduces carbon emissions of the homes, compared to an ‘instantaneous’ all- electric home the energy demand is modestly higher (c.10-15%). This is primarily the efficiency of the storage. The conclusion is that maximising the reduction in energy demands from homes is now too crude as a measurement for their optimisation: A more sophisticated awareness of when energy demands arise can yield lower carbon emissions, lower costs and better Grid interaction, but until storage efficiencies improve this will result in what appears to be a sub-optimal reduction using the crude measure of total energy demand. MASTERPLANNING NEW HOMES Demand profiles for homes regardless of occupancy clearly demonstrate peaks typical peaks for morning (around 8am) and evening (5-7pm), yet normal practices for the installation of renewable generation looks to achieve a South facing orientation, and some ‘low energy’ housing schemes have oriented their homes to enable this. The conclusion here is that orienting homes with East-West facing renewables (and most likely therefore East-West facing roofs) allows the likely demands to be better matched to the renewable generation. Whilst total energy generation will be lower than a South facing system, the energy that is generated will have a better alignment to the on-site demand. More investigation may well illustrate that aligning supply and demand is more beneficial than simply achieving the maximum energy generation (again, the akin to the previous point, the more sophisticated understanding may show that “maximum” isn’t necessarily the best). Future energy scenarios from National Grid suggest that energy pricing could go negative during the middle of the day as soon as 2025. The project must consider that midday generation (from the grid) may be better stored by the battery, leaving a west facing roof with a later peak to help pick up the higher demands of the home later in the day (or to offset from the midday peak).

APPENDIX A THE FLATLINE PROJECT PARTNERS & ASSOCIATES

Sero homes is a new residential development company dedicated to delivering ‘Energy Positive’ homes, this is a business driven by; 1. An overall need for housing delivery to meet the demands of a growing population, 2. A need for better quality and energy efficiency in new build housing, 3. Fuel poverty and rising energy costs, 4. New residential scale and building integrated clean energy solutions, 5. A down turn in the commercial scale renewable energy sector, and 6. An opportunity to create decentralised assets that can support the grid. The team behind Sero Homes has a long‐standing history in renewable energy through our successful company Eco2 Limited with over 300MW of renewable energy projects delivered in the UK. Energy Positive homes feature building integrated low carbon technologies that generate the demands of the home on an annual cycle. The approach to design an technology typically consists of the following; 7. Fabric first approach, improving the building fabric beyond building regulations to reduce the demand but remaining agnostic to construction method. Initial projects will vary from traditional construction to offsite construction. 8. Generation of heat and electricity through combined solar thermal and photovoltaics (PVT). 9. Storage of heat in common heat stores, immersion tanks and phase change batteries. 10. Storage of electricity in Lithium Ion batteries. 11. Smart appliances, heating controls and user interfaces 12. Electric vehicle charging, and 13. A ‘flexibility first’ approach to technology selection. The housing delivery model will initially follow the emerging ‘Build to Rent’ model. This delivers high quality homes to the Private Rental Sector with investment by institutional funds. The Sero Homes team has considerable experience in delivering projects for pension fund investors in renewable energy projects and targets the same success in housing. There are many benefits to sustainable housing delivery, the investors typically have environmental and social obligations in which Energy Positive homes fit well. This delivery model will also give Sero Homes long term ownership of the energy generation and storage assets required to deliver additional services to the grid. Sero Homes has secured its first ~50 home project working in collaboration with Neath Port Talbot County Borough Council (NPTCBC) and the Swansea Region City Deal (‘homes as power stations’). Sero Homes has established a Joint Venture with Edenstone Homes, an SME housebuilder based in South Wales to attract investors into larger projects (consented) and work with Edenstone on Energy Positive homes for private sale. Sero Homes is securing a pipeline of projects, initially in South Wales that will provide 1000 homes under management in 5 years. Sero Homes, working closely with Sero Energy and other developers is targeting delivery of unprecedented levels of Energy Positive homes. Sero Energy is an Energy Service Company dedicated to managing decentralised assets within the residential sector and to provide complementary services to the Sero Homes development business. The business will focus on a new consumer offering, selling comfort and not kWh. As we move towards new housing models the ‘kWh’ becomes more complicated with 4+ potential sources i.e. grid, PV, battery, car etc. Sero Energy has three main priorities; 14. Creating an energy service offering that allows the consumers to get the output they desire at the lowest cost whilst benefiting the wider network. 15. Collaborating with other developers (i.e. housing associations) to deliver Energy Positive housing to bring an increase in scale of delivery. Sero Energy would subsequently manage the partner developments in addition to the Sero Homes portfolio.

16. Building an energy management system, working with key service providers to create a Virtual Power Plant consisting of pooled energy assets.

The energy service offering would allow consumers fixed bills for energy, inclusive of heat and electricity. The aim following successful demonstration of the FLATLINE project is to reduce bills further by using the homes for Domestic DSR.

BRE is part of the BRE Trust, which uses any profits made to fund new research and education programmes to support the improvement of the built environment. BRE itself is an innovative group of researchers, scientists, engineers and technicians who share a common goal – to make the built environment better for all, and we've has been raising the standards of the built environment since 1921. Our multi-disciplinary teams include leading experts in virtually every element of the built environment, and together we generate new knowledge through independent research and advisory services. This is used to support clients, create the products, standards and qualifications that help to ensure buildings, homes and communities are safe, efficient, productive, sustainable and enjoyable places to be. Our clients use our expertise and services to deliver their social, environmental and economic goals. BRE have worked closely with Sero Homes & Sero Energy for several years, providing supporting expertise across the aspects of sustainability, construction, renewables, low carbon technologies, building monitoring and building energy modelling. This provides Sero with a trusted, independent review of systems and construction opportunities and provides a third-party 'critical friend' to the growing overlap between construction and energy systems. MINUS7 Minus 7 is a technology company that has developed a unique integrated hybrid heat and power system for buildings, using low temperature ambient and solar energy. The technology was first developed in mid 1980s, but commercial development did not properly begin until 2008 when the current company was formed and capitalised by the founding directors. In 2016, the management was strengthened and the first EIS investment round was completed with an angel investor. To date, £2.9m has been invested. Since then the company has further developed the initial technology to incorporate PV into the roof collector, and advanced the control system design. Alongside the technical development the company has developed a number

52 of relationships with key clients and conducted further pilot projects. The technology is fully certificated, and is operating in 70 locations in the UK ranging from private houses, social housing and swimming pools. The Minus 7 system is a unique, innovative, hybrid renewable energy harvester that harnesses ambient and solar energy to provide a complete energy solution for buildings providing heating, cooling and electricity. Solar thermal, Photovoltaics (‘PV’), a heat pump and energy storage are seamlessly integrated into a single hybrid system managed by an advanced proprietary controller. The system comprises of the following core components: 1.The Roof:The primary collector of heat is the roof. This is designed as a complete weather-tight structure made up of interlocking tile planks, made from aluminium extrusions which are powder coated or anodised to given a highly durable finish. These are coupled together and flooded with an environmentally benign heat transfer fluid, which absorbs heat from both ambient energy endothermically and from direct solar radiation. Thus it can collect heat energy day and night, and is typically sized to provide enough heat for a dwelling at midnight, mid-January. The endothermic process alone can absorb 130W/m2.

2.The Solar Energy Processor (SEP):At the heart of the system is the SEP. This contains a water-to-water heat pump, circulating pumps, heat exchangers, and transfer valves. In normal operation the heat pump takes energy from the roof circuit and cold store to a hot thermal store, which provides all the heat to the dwellings. This offers several critical differences compared with any other heat pump based system, namely; - The heat demand is met by the hot store not the heat pump, which means the running time can be optimised. - When the roof temperature is higher than the hot store temperature, the heat pump is taken out of the circuit and heat is passed directly to the hot store. This significantly increases the overall system performance. - The water-to-water heat pump is able to cope with high humidity and temperatures down to -7.0°C without ever having to ‘reverse cycle’, unlike air source heat pumps which have evaporators prone to icing up and therefore requiring energy to thaw. 3.Thermal Stores:It was recognised early on that the systems would require a means of heat storage in order to match optimum energy generation with energy demand, notwithstanding the fact that incorporating stores has a number of other advantages. The system has two stores: - A cold store of circa 500ltr (0.5m2), which is the energy source for the heat pump and is in circuit with the roof, as well as being directly coupled to the ground where it is buried. - An insulated hot store of circa 4000ltr (4.0m3) that takes energy from either the heat pump or the roof directly, and stores it ready for meeting the heat demand from the connected dwellings. The store can store 32kWh of heat in the temperature range 35-45°C. 4.Distribution:A typical system is a micro-district system in which one SEP provides heat to three properties, each of which has a Heat Transfer Unit (‘HTU’) installed to take heat from the heat main and distribute it into the property

53 as required. The HTU is the size of a standard wall mounted domestic boiler and comes in variants depending on the hot water demand of the property. 5.Smartswitch:Minus 7 has also developed a patented device called ‘Smartswitch’, which obviates the requirement for third party billing to run the central SEP. It takes an electric supply from each property’s distribution board and uses it to power the SEP according to the heat demand pertinent to the property. Thus the resident may select whichever energy provider they wish, with their heating bill effectively being a portion of their normal electricity bill. The system is illustrated diagrammatically on Figure 6 below:

Figure 6: System Overview

The Minus7 system turns a roof into an energy generating asset to provide heat (and potentially cooling) and electricity. The roof has a life expectancy of over 50 years, and the other components a minimum of 20 years. The heat generated is zero net carbon, insofar as the embedded PV generates more electricity than is needed to run the heat pump over a complete annual cycle. One system generates a maximum of 180kWh of heat per day and 9kWep11 of PV. This is sufficient capacity to provide heat to 3 or 4 standard two or three bedroom dwellings (or over 6 passivhaus properties). This defines the market for the technology as being in mini-district configurations, providing heat and electricity to terraces of houses or apartment blocks. Additional system features are as follows: - The technology is fully certified through BBA, BRE and MCS as both a renewable energy solution and roofing product. - The heat-pump charges thermal stores and is normally run in its optimal mode, minimising electricity usage. - Site data demonstrate that the annual yields from PV are increased by 25 – 30% through the use of the endothermic roof to provide cooling. This occurs predominantly during the spring and autumn months. - Minus7 provides a non-combustion, visually unobtrusive, whole-house heating solution, making it extremely attractive to those in urban areas looking to improve air quality. - The system is particularly advantageous to areas with restrictions on gas heating. - The system can be configured to provide cooling at minimal cost. - The flexibility of the system allows Minus7 to meet both the long term roofing needs of the clients, as well as providing low cost energy. Networked Systems and Demand Side Response

11 The unit kWep refers to the Kilowatt electric peak rating of a photovoltaic array

The Minus 7 systems are already remotely monitored, and the control software is being updated to provide suitable interfaces to the emerging Demand Side Management software and protocols. Intrinsically, the system is a micro district heating system and is designed for networked district systems.

SONNEN

The sonnen Group is one of the fastest growing companies in Germany and has lead the global residential battery storage market since 2010. sonnen is driven by a vision to achieve clean and affordable energy for all by harnessing the hugely disruptive potential of battery storage technology. The goal is to develop the best technology solutions to drive forward the move towards decentralized and digitalized electricity supply.

From the headquarters in Wildpoldsreid in Bavaria, sonnen has developed a proven and experienced management team, supported by over 400 employees worldwide. Well-financed, and with strategic investors including General Electric and Shell, sonnen is highly ambitious in its desire to further grow market share. With more than 30,000 sonnenBatterie systems installed in homes and businesses in diverse markets in the EU, the USA and Australia, sonnen is firmly established as the global market leader for battery storage units.

The sonnenBatterie is a complete, fully integrated energy storage solution with perfectly synchronized components including battery modules, integrated bi-directional inverter and smart energy management system – supplied in one easy-to-install box. Much more than just a battery, the sonnenBatterie enables users to change the way they manage and control their energy. sonnen designs, builds and controls both the hardware and software of the sonnenBatterie, an integrated approach which makes it easier to meet diverse business models, regulations and applications in different target markets. sonnen has lead the way in linking thousands of households and renewable energy producers to form the sonnenCommunity. This pion-eering energy sharing platform enables sonnen-Batterie owners to produce their own electricity and share it with others. sonnen operate an intelligent VPP platform through which energy sharing and energy services can be offered to residential homes by aggregating sonnenBatteries and other small-scale assets, and balancing supply and demand within the sonnenCommunity. Sonnen has successfully developed several VPP strategies and applications using our sonnenBatterie units in different markets, including Italy and Germany. We have adopted different approaches to meet regulation requirements and business models including demand response, frequency control, Blockchain, (scheduled) dispatch, as well as local production and consumption optimization by using the energy prediction engine in each sonnenBatterie. sonnen has been active in the UK market for over two years and has built up an installer network and customer base of sonnenBatterie owners. During this time sonnen has also been involved in various trial and pilot projects with DNOs, energy suppliers and social housing providers to prove and develop business models for the UK market.

SAMSUNG Samsung Electronics is committed to inspiring the world and creating the future through innovative technologies, products and design that enrich people’s lives and contribute to social prosperity. Samsung wants to democratise IoT by making all hardware IoT enabled by 2020. Samsung recently announced the unification of its IoT clouds into a single powerful platform called the SmartThings Cloud. As part of the world’s largest open ecosystem of IoT devices, the cloud will support partner company products that ‘Work with SmartThings’ or ‘Work as SmartThings Hub,’ and new services that are “Powered by SmartThings”. Samsung Research UK is one of 22 R&D centres around the world, and employs around 200 of Samsung Research’s 20,000 staff. The goal of Samsung research is to connect Samsung and partner technologies together to enable interoperability and simplicity for users, all powered by the latest in cutting-edge AI technologies.

APPENDIX B ESTIMATING OVERALL ENERGY DEMAND FOR DWELLINGS AT THE SITE

Three main components have been deemed to contribute to the overall energy demand for each dwelling, namely: - Space heating demand - Hot water demand - Electricity demand Each of these elements has used different sources of reference data, as detailed below. Dwelling occupancy has a notable effect on each aspect, so the assumptions used for occupancy are first discussed. OCCUPANCY ASSUMPTIONS Since dwelling hot water and electricity demand are recognised as varying according to occupancy, it has been necessary to make assumptions for the number of occupants that would be present in each of the houses. For these purposes, it has been assumed that each dwelling would have 2 people in the main bedroom and 1 person in each additional bedroom, i.e. occupancy = no. bedrooms + 1. It is acknowledged that SAP also makes assumptions for occupancy when calculating internal gains. This is based on a non-linear relationship with the building floor area that has been validated against large scale housing stock data. The relationship plateaus at around 3 occupants, even with very large floor areas. If dwellings have a higher occupancy in reality, there will be slightly higher internal heating gains in practice, which would proportionately reduce the space heating demand. It follows that assuming a lower occupancy for the heating demand in SAP provides a more conservative approach when considering heating energy. Although SAP will calculate hot water demand, for this study hot water demand has been calculated separately using the same occupancy assumptions as for electricity demand (i.e. no. bedrooms + 1). It is postulated that in rental properties households are less likely to rent additional unused bedrooms, since it is somewhat easier to move to another rental property if circumstances change and more/ less bedrooms are required, than to sell and buy a new house. Additionally, estimates based on higher occupancy would lead to higher hot water energy demand assumptions, which would again be more conservative in terms of storage sizing and load shifting capacities. SPACE HEATING DEMAND An accepted standardised way of calculating dwelling energy demand is by using the UK Government Standard Assessment Procedure (SAP) software. This is a regulatory compliance tool with the purpose of calculating energy demand based on the building fabric performance. Only ‘regulated’ energy is considered, i.e. that required for heating, hot water, lighting and any auxiliary demand for pumps and fans. All other energy uses are deemed ‘unregulated’, since they are highly variable and occupant specific, such as their use of appliances and other ad hoc devices. SAP has been used for part of the calculation process for heating demand; since it only calculates annual demand based on monthly average conditions, SAP alone would be insufficient to provide detailed daily and hourly profiles of heating energy demand. However, the tool incorporates sound assumptions for numerous other factors that there are no grounds to amend. SAP models were therefore created for each of the dwelling types on the proposed site in order to calculate: - The average heat transfer coefficient of the building fabric, based on the building geometry and the losses from the plane elements (walls, roof, etc), and from ventilation - Typical gains and losses that may offset heating energy demand to some extent - Utilisation factors for the usage of gains

Heat transfer coefficient The thermal performance criteria for the buildings was based on the enhanced elemental specification created for Sero Homes for the site, as set out in Table 8. The intention is that the dwellings take a fabric-first approach to energy efficiency, but that standards could still be achieved using traditional cavity masonry construction if desired, within the preferred nominal wall thickness of 350mm and with due consideration of the exposure requirements of the site. Minimum performance standards were also set for thermal bridging that are enhanced compared to the default values typically used in SAP. Ventilation loss assumptions were based on an assumed decentralised

57 continuous extract system. The resulting heat transfer coefficient is a single value that represents the overall rate of heat loss from the dwelling.

Table 7: Fabric specification for dwellings at the site

Element Maximum permissible values External walls U ≤ 0.17 W/m2K Floors U ≤ 0.10 W/m2K Roofs U ≤ 0.10 W/m2K Opaque doors U ≤ 1.00 W/m2K Windows U ≤ 1.20 W/m2K Roof windows U ≤ 1.40 W/m2K Air permeability ≤ 5 m³/h·m² at 50 Pa

Internal gains and losses For this modelling, no contribution has been assumed for solar gains since dwellings may have varying orientation. Any solar gains will reduce the overall heating energy demand. However, the model compensated for the lack of solar gains with an increased assumption for lighting energy. These effects would not be expected to balance each other out; calculations excluding solar affects would be expected to result in increased heating energy demand, and hence be more conservative overall. While the heating method used in the SAP models is largely irrelevant to fundamental heat demand of the building, SAP takes some allowance of gains from heated water. The exact location and extent of water storage is not known at this stage, but there will still be incidental gains from showers and hot taps, even if not from storage. SAP models therefore assumed traditional gas combi boilers for the purposes of calculating incidental gains from hot water used in the dwellings. The SAP model provides utilisation factors for gains that vary by month. These reflect the fact that gains are less useful over the summer months when ambient temperatures are higher. These utilisation factors have been applied to the internal gains assumptions from SAP in the subsequent analysis. Calculation of half hourly space heating demand The building heat transfer coefficient from SAP (effectively heat loss per unit of temperature difference across the structure) was applied to climate data for Cardiff that indicated the relative temperature differential between external conditions and a target indoor temperature over a typical year. Temperature data was provided in hourly time steps, so it is assumed that each half hour has the same average temperature as the respective hour. Climate data was based on a test reference year for Cardiff from Meteonorm software. The target internal temperature was taken to be 20°C year round. The overall heating demand to maintain this temperature was calculated per half hour by subtracting the useful gains per month from SAP, multiplied by the respective monthly gains utilisation factor, from the losses experienced in each time step. The calculation is described in detail below. This calculation approach results in slightly higher annual heating energy demand than is assumed by SAP, largely due to the exclusion of solar gains from the calculation. SAP also assumes that no heating would be delivered in summer months, regardless of external temperatures, whereas based on the local climate data and the target set temperature, this method assumes some minor heating demand over summer months. Note that the reported values represent absolute demand with no consideration of potential system losses, which in reality could increase the energy required to be delivered to a dwelling. Per half hour time step: External temperature - internal target temperature = ΔT, °C

Heat transfer coefficient x ΔT = heat loss rate through fabric, W/°C Incidental gains x utilisation factor = useful gains, W Heat loss through fabric – useful gains = space heating load, W Space heat load x 0.0005 = space heat demand per half hour, kWh

From this method, every day per year has a unique data profile. In order to provide example data for any given month, a single ‘typical day’ has been created based on the average demand for each respective hour in a given month. Monthly profiles of space heating demand are given for each of the dwelling types on the site in Figure 7. The profile shape in all cases is similar, since they are based on the same fundamental climate data. However the magnitude of the demand varies according to the size and design of each property. Figure 7: Monthly half hourly space heating energy demand for dwellings

HT1 ET Space heating demand, 77m2

0.600 January 0.500 February March

0.400 April

0.300 May June

0.200 July

Heat demand, kWh 0.100 August September

0.000 October

0 4 8 12 16 20 24 November

Time over typical day December

HT1 MT Space heating demand, 77m2

0.600 January 0.500 February March

0.400 April

0.300 May June

0.200 July

Heat demand, kWh 0.100 August September

0.000 October

0 4 8 12 16 20 24 November

Time over typical day December

HT10 SD Space heating demand, 71m2

0.600 January

0.500 February March

0.400 April

0.300 May June

0.200 July

Heat demand, kWh 0.100 August September

0.000 October 0 4 8 12 16 20 24 November

Time over typical day December

HT2G ET Space heating demand, 88m2

0.600 January

0.500 February March

0.400 April

0.300 May June

0.200 July

Heat demand, kWh 0.100 August September

0.000 October 0 4 8 12 16 20 24 November

Time over typical day December

HT4v2 SD Space heating demand, 104m2

0.600 January

0.500 February March

0.400 April

0.300 May June

0.200 July

Heat demand, kWh 0.100 August September

0.000 October 0 4 8 12 16 20 24 November

Time over typical day December

HT12 SD Space heating demand, 89m2

0.600 January

0.500 February March

0.400 April

0.300 May June

0.200 July

Heat demand, kWh 0.100 August September

0.000 October 0 4 8 12 16 20 24 November

Time over typical day December

HOT WATER DEMAND As discussed above, SAP is able to calculate hot water demand in dwellings. However, for the purposes of this study it was preferable to create hot water demand profiles over a 24 hour period, rather than simply monthly values. The number of occupants also varied compared to those assumed by SAP. The calculation was therefore carried out separately, but based on the calculation procedures used in SAP.

In 2008, the Energy Saving Trust, working on behalf of the Department for Environment, Food and Rural Affairs (DEFRA), published results of a comprehensive monitoring study of 120 homes12. The aim of the study was to directly measure hot water consumption, identify heating patterns and where/ how the water was being used. The findings of this study led to updates in the SAP methodology for calculating water consumption that aligned with the usage trials.13 Water consumption is based on the key assumption of 25N + 36 litres per day, where N is the number of occupants in the dwelling. Two monthly factors are subsequently applied to the water volume. The first is a monthly water utilisation factor that was determined from the EST study data, as it was found that proportionately more water was used over colder months than hotter months. The monthly water factors assumed in the calculations are given in Table 9. The study also showed that there was a notable difference in the incoming mains temperature across a year, which will subsequently effect the heating energy required to raise the temperature to the intended set point. Table 9 also shows the monthly temperature rise that is used to calculate the heating energy demand for hot water. Table 8: Monthly factors used in water consumption calculations

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Monthly water 1.10 1.06 1.02 0.98 0.94 0.90 0.90 0.94 0.98 1.02 1.06 1.10 factor Monthly 41.2 41.4 40.1 37.6 36.4 33.9 30.4 33.4 33.5 36.3 39.4 39.9 temperature rise, °C

12 EST, ‘Measurement of domestic hot water consumption in dwellings’, Energy Saving Trust, 2008. Available at: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/48188/3147-measure- domestic-hot-water-consump.pdf 13 Shorrock. LD, ‘Analysis of the EST’s domestic hot water trials and their implications for amendments to BREDEM and SAP’, Technical Paper supporting SAP 2009 – STP09/DHW01, BRE, June 2008. Available at: https://www.bre.co.uk/filelibrary/SAP/2012/STP09-DHW01_Analysis_of_EST_DHW_data.pdf

Monthly values are adequate for the requirements of SAP calculations. However, the EST study also determined typical daily profiles of usage, per hour. It was found that usage was generally increased for users of combi boilers due to the need for water to run for longer before hot water reached the outlet. Since it is expected that water storage will be provided to the dwellings, the hourly profile for a regular boiler is considered in this study, which is replicated in Figure 8. It is evident that the main peak for water usage is around 8am, with a secondary peak around 7-8pm. Applying these ratios to the general calculation method used by SAP allows hourly water consumption over a whole year to be estimated. To maintain a half-hourly data profile, it is assumed that each half hour has half the water consumption of the respective hour. It is acknowledged that using this method will still effectively produce data that is averaged monthly (i.e. each day of a given month will be the same), but allows a half hourly profile to be applied to each day, which can be used to determine the scope of demand shifting and potential storage requirements. The calculation is described in detail below. Per half hour time step: 25N + 36 litres per day x monthly factor = daily water volume, litres/day Daily water volume x half hour consumption ratio = hh water volume, litres/hh Energy required to heat hot water, Q (J) = Vol x ρ x c x ΔT … where ρ = density of water = 1kg/litre c = specific heat capacity of water = 4190 J/kg°C ΔT = temperature increase, °C Heat energy, Q ÷ 3600000 = heat demand for hot water, kWh

Figure 8: Ratio of daily water usage based on EST monitoring study, 2008

0.050

0.040

0.030

0.020

0.010 Ratio of daily hot water use water hot daily of Ratio

0.000 0 4 8 12 16 20 24 Time over typical day, h

Monthly profiles of hot water heating demand are given for various occupancy rates in Figure 9.

Figure 9: Monthly half hourly hot water energy demand according to dwelling occupancy

2 occupant water heating demand

0.350 January 0.300 February 0.250 March April 0.200 May

0.150 June 0.100 July

Heat demand, kWh August 0.050 September

0.000 October

0 4 8 12 16 20 24 November

Time over typical day December

3 occupant water heating demand

0.350 January 0.300 February 0.250 March April 0.200 May

0.150 June 0.100 July

Heat demand, kWh August 0.050 September

0.000 October 0 4 8 12 16 20 24 November

Time over typical day December

4 occupant water heating demand 0.350 January

0.300 February 0.250 March April 0.200 May

0.150 June

0.100 July

Heat demand, kWh August

0.050 September 0.000 October 0 4 8 12 16 20 24 November Time over typical day, h December

COMBINED HEATING AND HOT WATER ENERGY DEMAND The heating energy demand for a given dwelling is combined with the appropriate hot water energy demand according to its occupancy for each of the dwelling types on the site in Figure 10.

Figure 10: Monthly half hourly total heating energy demand for dwellings

HT1 ET Total heating demand, 77m2, 3 occupants

0.800 January

0.700 February

0.600 March 0.500 April 0.400 May June 0.300 July 0.200

Heat demand, kWh August

0.100 September

0.000 October

0 4 8 12 16 20 24 November

Time over typical day December

HT1 MT Total heating demand, 77m2, 3 occupants

0.800 January

0.700 February 0.600 March 0.500 April 0.400 May June 0.300 July 0.200

Heat demand, kWh August 0.100 September

0.000 October 0 4 8 12 16 20 24 November

Time over typical day December

HT10 SD Total heating demand, 71m2, 3 occupants

0.800 January

0.700 February 0.600 March 0.500 April 0.400 May June 0.300 July 0.200

Heat demand, kWh August 0.100 September

0.000 October 0 4 8 12 16 20 24 November

Time over typical day December

HT2G ET Total heating demand, 88m2, 4 occupants

0.800 January

0.700 February 0.600 March 0.500 April 0.400 May June 0.300 July 0.200

Heat demand, kWh August 0.100 September

0.000 October 0 4 8 12 16 20 24 November

Time over typical day December

HT4v2 SD Total heating demand, 104m2, 4 occupants

0.800 January

0.700 February 0.600 March 0.500 April 0.400 May June 0.300 July 0.200

Heat demand, kWh August 0.100 September

0.000 October

0 4 8 12 16 20 24 November

Time over typical day December

HT12 SD Total heating demand, 89m2, 4 occupants

0.800 January

0.700 February 0.600 March 0.500 April 0.400 May June 0.300 July 0.200

Heat demand, kWh August 0.100 September

0.000 October 0 4 8 12 16 20 24 November

Time over typical day December

ELECTRICITY DEMAND Various data sources for household electricity use have been considered, however most do not provide sufficient granularity of data (i.e. half hourly) and/ or it is not possible to align the data with particular housing characteristics, such as size, number of occupants, type of heating, etc. such that it can be applied to known house designs.

The most detailed data available at present is from the Household Electricity Survey carried out by Intertek Ltd for the Department of Energy and Climate Change (DECC), published in 2014. This study specifically identified and monitored end uses by electrical sub-circuits on consumer units at 10 minute intervals. A range of information was also collected about the dwellings and their occupants. It is therefore possible to obtain seasonal electricity consumption data at sufficient granularity according to the number of occupants within a dwelling. Data is available from a sortable spreadsheet tool.14 Data from the survey has been used for this study, but with any contributions from heating and hot water excluded, since these would be provided by a separate heating system in the dwellings. (Note that energy demand from electric showers has remained within the consumption data, as it is not known whether electric showers would be present or not within the dwellings). Although a sample of 250 dwellings was monitored, not all were monitored for a full year – only for a number of months to give indicative values and allow a wider sample of dwellings to be assessed using the same monitoring equipment. It follows that when monthly profiles of consumption are selected, the number of properties included in the sorted sample decreases. The monitoring also captured a range of occupancies, so when the data is sorted by occupancy the sample size also inevitably decreases. Table 10 shows the breakdown of sample sizes from the data set according to month and occupancy. It is apparent that for occupancies of 3, 5 and 6+ the data set is very limited. Table 9: Sample size of monitored dwellings according to month and occupancy

Whole Occupancy year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1 70 14 12 14 22 26 24 13 9 12 12 11 13 2 86 26 20 16 20 22 32 31 22 23 24 21 26 3 30 3 4 5 8 10 7 6 6 3 3 6 7 4 49 15 15 15 10 13 20 10 9 9 10 7 9 5 8 1 2 1 2 3 3 2 1 2 2 3 3 6+ 7 3 2 3 4 3 2 2 2 2 3 5 3

Where there are 3 or fewer properties making up the sorted data, the information is suppressed. Unfortunately this means there is very limited usable data for 5 or more occupants to the extent that it cannot realistically be used at a monthly level, and for 3 occupants some months are also suppressed (January, September and October). In order to create a complete month-by-month dataset for the 3 occupant case, data has been taken for the two adjacent months and averaged to effectively provide interpolated values. In the case of September and October, the values for August and November have been apportioned in a ratio of 2/3 to 1/3, in favour of the adjacent month. While there are relatively small sample sizes for all of the monthly data sets, data for 3 occupants should be treated with particular caution. The source data gives the electricity load in Watts at 10 minute intervals. This has been converted into equivalent kWh (per 10 minute interval) then summed to provide data half hourly. Note that as with the water heating demand data, data is averaged monthly (i.e. each day of a given month will be the same), but allows a half hourly profile to be applied to each day, which can be used to determine the scope of demand shifting and potential storage requirements. Monthly profiles of electricity demand are given in Figure 11.

14 DECC Household Electricity Survey spreadsheet tool. Available at: https://www.gov.uk/government/publications/spreadsheet-tools-for-users

Figure 11: Monthly half hourly electricity demand dependent on occupancy

Electricity demand, 2 occupants 1.000 0.900 Whole year average 0.800 January February 0.700 March 0.600 April

0.500 May

0.400 June 0.300 July August

Electricity demand, kWh 0.200 September 0.100 October 0.000 November 0 4 8 12 16 20 24 December Time over typical day, h

Electricity demand, 3 occupants 1.000 0.900 Whole year average January 0.800 February 0.700 March 0.600 April

0.500 May

0.400 June 0.300 July August

Electricity demand, kWh 0.200 0.100 September October 0.000 0 4 8 12 16 20 24 November Time over typical day, h December

Electricity demand, 4 occupants 1.000 0.900 Whole year average January 0.800 February 0.700 March 0.600 April

0.500 May

0.400 June 0.300 July August

Electricity demand, kWh 0.200 0.100 September October 0.000 0 4 8 12 16 20 24 November December Time over typical day, h

The total annual electricity demand indicated in these occupancy profiles is higher than average values currently assumed by BEIS in their reporting; BEIS use an average of 3800 kWh per year, whereas the totals from this data are: 2 occupants = 4090 kWh, 3 occupants = 5260 kWh, 4 occupants = 5489 kWh There are a number of reasons why this may be the case. Firstly, although the Household Electricity Survey data was published in 2014, the data was reportedly collected between 2010 and 2011. A Special Feature article issued by DECC in 201415 investigated how household fuel consumption had changed over recent years. Electricity consumption values are replicated in Table 11, where it is apparent that annual electricity consumption in households has been gradually decreasing since 2008. This represents an average of all households on all meter types. However, approximately 15% of households have Economy 7 tariffs, where electricity is also typically used for heating. When averaged, this has the effect of raising the overall typical consumption in Table 11. Splitting out the Economy 7 tariff contribution leads to the values reported in Table 12, which led DECC (and subsequently BEIS) to adopt 3800 kWh as a typical household electricity consumption. Table 10: Estimated mean household electricity consumption (DECC, 2014)

Temperature adjusted Unadjusted electricity Year electricity consumption, kWh consumption, kWh 2008 4,509 4,536 2009 4,443 4,480 2010 4,419 4,322 2011 4,126 4,231 2012 4,220 4,217 2013 4,136 4,119

15 DECC, ‘Revisions to DECC domestic energy bill estimates’, Special Feature article, Energy Trends, March 2014. Available at: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/ file/295244/Revisions_to_DECC_domestic_energy_bill_estimates.pdf

Table 11: Estimated mean household electricity consumption by type of tariff (DECC, 2014)

Standard electricity tariff Economy 7 electricity tariff Temperature Temperature Unadjusted Unadjusted Year adjusted adjusted consumption, consumption, consumption, consumption, kWh kWh kWh kWh 2008 4,113 4,158 6,429 6,468 2009 4,127 4,161 6,176 6,227 2010 4,092 4,002 6,229 6,092 2011 3,827 3,925 5,851 6,001 2012 3,886 3,883 6,088 6,083 2013 3,798 3,782 5,979 5,955

Data reported in the Household Electricity Survey included some households that utilised electricity as heating, and hence may be expected to align more with the higher unseparated average consumption values from Table 11 rather than the separated tariff values in Table 12. The average reported electricity consumption will also be skewed by the size of the households in the sample. For example, in 2017 the majority of households in the UK had only 1 or 2 occupants (63%), with only a little over a third of households having 3 or more occupants.16 When the Household Electricity Survey data for 2 occupants is compared with data for 2010 from Table 11, it is actually slightly lower but similar to the UK average at the time, i.e. 4090 kWh compared with 4419 kWh. It is therefore not unreasonable to assume that the Household Electricity Survey data is representative of the national sample when the ratio of occupants is considered, and that electricity demand for larger households would be higher. The overall size of the data sample will also be a notable variable. The survey data on which the ‘per occupancy’ values are derived is from a very small sample set (tens of properties) compared with an average of millions of dwellings used to create the national average values given in the tables above. Individual household behaviours in the smaller survey sample will therefore have a much greater effect on the quoted values than they would in the larger dataset. Overall, despite the energy demand values used for this analysis being higher than the average UK values quoted by BEIS, there are a number of reasons that confirm the values are likely to be representative for the time and circumstances under which they were collected. It seems likely that, in keeping with the UK average data, the per- occupancy total electricity demands will have decreased since the survey data was collected in 2010/11, hence they may now carry a positive error of at least 6%. This has not been seen as a major concern for this project, since it implies that any flexibility capacity that is determined from the study may in fact be greater in practice (i.e. the claimed flexibility estimates will be conservative) if the actual household electricity demand proves to be somewhat lower and the services have been specified to cope with a greater demand.

NOTES REGARDING DATA QUALITY For the purposes of this study we have used the most appropriate data at our disposal, although inherent variability in weather patterns and occupancy behaviours make any exercise of this nature an estimate at best.

16 ONS, ‘Households by size’, Labour Force Survey (LFS), Office for National Statistics, November 2017. Available at: https://www.ons.gov.uk/file?uri=/peoplepopulationandcommunity/birthsdeathsandmarriages/families/ datasets/familiesandhouseholdsfamiliesandhouseholds/current/familieshouseholds2017.xls

Heating energy demand – calculated heating demand is based on assumed construction quality, which could differ in practice, as well as a single target internal set temperature of 20°C. If users varied this temperature or chose to only heat the dwellings at set times rather than being permanently controlled by a thermostat, the demand would vary. The demand itself is based on a test reference climate year for Cardiff and the effects of real local climate conditions could cause significant variation in heating demand year-to-year. Exclusion of solar gains from the estimates means the forecasts calculated are typically higher than may be expected if solar gains were incorporated. Every day in the year is effectively unique. Where necessary, typical representative days have been derived for each month by averaging the demand for each respective hour per day within that month, giving each day in a month the same values. Hot water energy demand – while deemed to be largely dependent on occupancy, individual household behaviours can vary significantly. Forecasts fundamentally rely on an assumed occupancy for each dwelling type, which is unknown and may differ over time and from house-to-house. The sample size for the initial EST study on which the calculations are based was 112 viable properties. Each month is effectively represented by a typical profile of a day (i.e. each day in a month has the same values). Electricity demand – the house types on the site have been deemed likely to have 3 or 4 occupants. Based on the data collected for the DECC Household Electricity Survey, the sample sizes used to attribute monthly electricity demand to dwellings is variable. For 4 occupants, the sample ranges from as few as 7 dwellings up to 20. For 3 occupants, the sample ranges from as few as 3 dwellings up to 10. Overall, both are reliant on extremely small numbers of survey participants, and results should therefore only be deemed indicative. When the data is accumulated to provide averages for a whole year, the 4 occupant sample utilises 49 dwellings and the 3 occupant sample has 30 dwellings. In any case, the electricity demand estimates should be viewed as an insight into likely consumption patterns, rather than relied on explicitly. Each month is effectively represented by a typical profile of a day (i.e. each day in a month has the same values).

APPENDIX C ESTIMATING ENERGY GENERATION FOR THE SITE

METHODS OF ESTABLISHING SOLAR PV GENERATION In order to determine the potential for solar PV generation it is important to first create three-dimensional models of the properties so that roof properties can be quickly collected and appropriate PV system sizes drawn upon. The FLATLINE site comprises 58 dwellings using 6 unique house types, known as HT1, HT2G, HT4v2, HT10, HT12A, HT12B. The housing scheme uses four dormer profiles and two chimney profiles and as such, there are a considerable number of variations to take into account that could impact on the potential available roof space for solar PV installation. Every effort is made to ensure that the models best represent the plans provided. Each house type is modelled using Google SketchUp from plans provided by Hammond Architectural Ltd. Allowances are made for narrower semi-detached and terraced properties accordingly. The site plan is provided with a geo- location before each of the 58 houses are placed into a single model. FLATLINE considers plots 110-167 (inclusive) of the larger site. A three dimensional masterplan of the FLATLINE site is illustrated below in Figure 12. Figure 12: Masterplan of FLATLINE site consisting of 58 houses

There are a number of methods available to determine the amount of solar irradiance on a particular roof plane. Two methods are discussed in this report: SketchUp plugin (HTB2) and Standard Estimation Method (by MCS). SKETCHUP PLUGIN (HTB2) HTB2 is a certified dynamic simulation software tool that can be used in conjunction with SketchUp to perform solar modelling. The tool accounts for roof location, orientation, inclination and shading. As part of the modelling, annual solar irradiation totals (kWh/m²) taken from the dynamic simulation outputs are imported into the SketchUp model so that a colour scale can be applied to visually represent the range of annual solar irradiation totals on each roof plane across a site (blue representing low irradiation, through to red representing high irradiation). The output illustration provided by the tool for the FLATLINE site is shown in Figure 13. For FLATLINE, it can be argued that yield is not as important as the time of generation and the ability to increase/decrease site capacity. For example, an east/west

71 facing array may be more desirable than a south facing array if that better corresponds with offsetting occupant usage. Figure 13: Annual solar radiation for each roof on the FLATLINE masterplan, using HTB2

HTB2 is powerful software however its infancy means that it is time consuming and often difficult to yield successful datasets from. There are a number of ‘bugs’ that reduce its reliability. For example, the pair of adjacent plots circled in Figure 13 are identical, albeit with slightly different dormers. However, the software incorrectly suggests that the plots with flat dormers (red) have considerably higher annual solar irradiation compared to the plots with pitched dormers (green). Also, HT10 plots 120 and 148 show considerable solar resource however in practice, they are significantly shaded by nearby roofs and are deemed unviable. The software calculates shading masks (e.g. Figure 14) for each roof plane to determine solar irradiation totals. Whilst this is in itself very useful information, the determined solar radiation is averaged over the entire roof plane. Averaging in this way can be inaccurate; for example if only roof areas above and below dormers are utilised for PV installation (to avoid shading) then actual solar radiation will be higher than if shaded areas are included. The shading masks did however highlight the impact that the shading caused by chimneys could have on solar radiation, which in some cases is significant. HTB2 provides annual global tilted irradiation for each plane, in kWh/m2. This is raw data and must have a conversion factor applied to determine potential yield from a solar PV system. A conversion factor should account for all system efficiency losses, including those arising from modules and inverters. Whilst this is possible there are many factors to account for, which alter with module/inverter type and irradiance levels. Researching and/or calculating such factors is outside the scope of this report and indeed, is not be required if the Standard Estimation method is used instead, as described below.

Figure 14: Example annual solar irradiation and shading mask for Plot 162 (east-facing)

STANDARD ESTIMATION METHOD (BY MCS) For PV systems up to 50kWp, the Microgeneration Certification Scheme (MCS) standard currently applies. MCS provides a framework of design and quality control procedures for installers and key products of solar PV systems. The Standard Estimation Method included as part of this free-issue standard sets out a process for determining the performance of a solar PV system anywhere in the UK, without the need for third party software or efficiency assumptions. The approach as per the MCS standard is illustrated in Figure 15. Figure 15: Standard Estimation Method (MCS, 2012)

Establishing the potential electrical rating of PV arrays (1) for each house type is discussed below. The postcode region (2) of the site is 5W-Cardiff and as such this particular dataset is used for interpolation (5). For the purpose of this report it is assumed that Cardiff data will suitably reflect the likely performance of a PV system at the FLATLINE site, which is located 22km NNW of Cardiff airport (the data source). The MCS irradiance dataset for 5W Cardiff is given in Figure 16. Brighter green shows the highest yield (max 950 kWh) through to red representing lowest yield (221 kWh). The lookup table is simple in that the specific annual yield (kWh/kWp) of a PV system can be determined with only the roof inclination (degrees from horizontal, to nearest 1°) and orientation (degrees from south, to nearest

5°). For example, a south-facing house with a 38° inclination provides a specific annual yield of 950kWh/kWp, the highest possible in this location. A 4kWp PV system would therefore generate 950kWh x 4kWp = 3,800kWh per annum. BRE have developed an automated lookup tool to streamline this process. Figure 16: MCS specific yield (kWh/kWp) for 5W Cardiff

Orientation (variation from south),

Orientation (variation from south) Slope 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 105 110 115 120 125 130 135 140 145 150 155 160 165 170 175 0 803 803 803 803 803 803 803 803 803 803 803 803 803 803 803 803 803 803 803 803 803 803 803 803 803 803 803 803 803 803 803 803 803 803 803 803 1 809 809 809 809 809 809 808 808 808 807 807 806 806 805 805 804 803 803 802 801 801 800 800 799 798 798 797 797 797 796 796 795 795 795 795 795 2 816 816 816 816 816 815 815 814 813 812 811 810 809 808 807 806 804 803 802 801 799 798 797 796 795 794 793 792 791 790 789 789 788 788 788 787 3 823 823 823 823 822 821 820 819 818 817 816 814 813 811 809 807 806 804 802 800 798 796 794 792 791 789 788 786 785 784 783 782 781 780 780 780 4 830 830 830 829 828 827 826 825 823 822 820 818 816 814 811 809 806 804 801 799 796 794 791 789 787 785 783 781 779 777 776 775 774 773 772 772 5 837 837 836 835 835 833 832 830 828 826 824 822 819 816 813 810 807 804 801 798 795 792 789 786 783 780 777 775 773 771 769 768 766 765 765 764 6 843 843 843 842 841 839 838 836 833 831 828 825 822 819 815 812 808 804 801 797 793 789 786 782 779 775 772 769 767 764 762 760 759 758 757 756 7 849 849 849 848 846 845 843 841 838 835 832 829 825 821 817 813 809 804 800 796 791 787 783 778 774 771 767 764 761 758 755 753 751 750 749 748 8 855 855 855 854 852 850 848 846 843 839 836 832 828 823 819 814 809 804 800 794 789 784 780 775 770 766 762 758 754 751 748 746 744 742 741 740 9 861 861 860 859 858 856 853 850 847 843 839 835 831 826 821 815 810 804 799 793 787 782 776 771 766 761 756 752 748 744 741 738 736 734 733 732 10 867 867 866 865 863 861 858 855 851 847 843 838 833 828 822 816 810 804 798 792 785 779 773 767 762 756 751 746 742 738 734 731 728 726 725 724 11 873 872 872 870 868 866 863 859 856 851 846 841 836 830 824 817 811 804 797 790 784 777 770 764 757 751 745 740 735 731 727 723 721 718 717 716 12 878 878 877 875 873 871 868 864 860 855 850 844 838 832 825 818 811 804 797 789 781 774 767 760 753 746 740 734 729 724 720 716 713 711 709 708 13 883 883 882 880 878 875 872 868 863 858 853 847 840 834 826 819 811 803 796 787 779 771 764 756 748 741 734 728 722 717 712 708 705 703 701 700 14 888 888 887 885 883 880 876 872 867 862 856 849 843 835 828 820 812 803 795 786 777 769 760 752 744 736 729 722 716 710 705 701 698 695 693 692 15 893 893 892 890 887 884 880 876 871 865 859 852 845 837 829 820 812 803 794 784 775 766 757 748 739 731 723 716 709 704 698 694 690 687 685 684 16 898 898 896 894 892 888 884 880 874 868 861 854 847 838 830 821 812 802 793 783 773 763 754 744 735 726 718 710 703 697 691 686 682 679 677 676 17 902 902 901 899 896 892 888 883 877 871 864 856 848 840 831 821 812 802 792 781 771 760 750 740 731 721 712 704 697 690 684 679 675 672 670 668 18 907 906 905 903 900 896 892 886 880 874 866 859 850 841 832 822 811 801 790 779 769 758 747 736 726 716 707 698 690 683 677 672 668 664 662 661 19 911 910 909 907 904 900 895 890 883 876 869 860 852 842 832 822 811 800 789 778 767 755 744 733 722 711 701 692 684 676 670 665 660 657 654 653 20 915 914 913 910 907 903 898 893 886 879 871 862 853 843 833 822 811 800 788 776 764 752 740 729 717 706 696 686 678 670 663 657 653 649 647 645 21 918 918 916 914 911 907 901 895 889 881 873 864 854 844 833 822 811 799 787 774 762 749 737 725 713 701 691 681 671 663 656 650 645 642 639 638

22 922 921 920 917 914 910 904 898 891 883 875 865 855 845 834 822 810 798 785 772 759 747 734 721 709 697 685 675 665 657 649 643 638 634 631 630 23 925 925 923 921 917 913 907 901 893 885 876 867 857 846 834 822 810 797 784 771 757 744 730 717 704 692 680 669 659 650 642 636 631 627 623 622 24 928 928 926 924 920 915 910 903 896 887 878 868 857 846 834 822 809 796 782 768 755 741 727 713 700 687 674 663 653 643 636 629 623 619 616 614 25 931 931 929 926 923 918 912 905 897 889 879 869 858 847 834 821 808 795 781 766 752 738 723 709 695 682 669 657 646 637 629 622 616 611 608 606 26 934 933 932 929 925 920 914 907 899 890 881 870 859 847 834 821 807 793 779 764 750 735 720 705 691 677 664 651 640 630 622 615 608 604 600 598 27 936 936 934 931 927 922 916 909 901 892 882 871 859 847 834 820 806 792 777 762 747 732 717 701 687 672 659 646 634 624 615 607 601 596 593 591 28 939 938 936 933 929 924 918 910 902 893 883 871 859 847 834 820 805 791 775 760 744 729 713 698 682 668 653 640 628 617 608 600 593 588 585 583 29 941 940 938 935 931 926 919 912 903 894 883 872 860 847 833 819 804 789 774 758 742 726 709 693 678 662 648 634 622 611 601 593 586 581 577 575 30 943 942 940 937 933 927 921 913 904 895 884 872 860 846 833 818 803 787 772 755 739 723 706 690 674 658 643 629 616 604 594 586 579 573 569 567 31 944 944 942 939 934 929 922 914 905 895 884 872 860 846 832 817 802 786 769 753 736 719 702 686 669 653 638 623 610 598 588 579 571 566 562 560 32 946 945 943 940 936 930 923 915 906 896 884 872 859 845 831 816 800 784 767 750 733 716 699 682 665 649 632 618 604 592 581 572 564 558 555 552 33 947 946 944 941 937 931 924 916 906 896 884 872 859 845 830 814 798 782 765 748 730 713 695 678 660 644 627 612 598 585 574 565 557 551 547 544 34 948 947 945 942 937 932 924 916 907 896 884 872 858 844 829 813 797 780 763 745 727 709 692 674 656 639 622 606 592 579 567 558 550 543 539 536 35 949 948 946 943 938 932 925 916 907 896 884 871 858 843 828 812 795 778 760 742 724 706 688 670 652 634 617 601 586 573 561 551 542 536 531 528 36 949 949 947 943 938 932 925 916 907 896 884 871 857 842 826 810 793 776 758 739 721 702 684 666 647 629 612 596 580 566 554 544 535 529 524 521 37 950 949 947 944 939 933 925 916 906 895 883 870 856 840 825 808 791 773 755 737 718 699 680 661 643 625 607 590 574 560 547 537 528 521 516 513 38 950 949 947 944 939 932 925 916 906 895 882 869 854 839 823 806 789 771 753 734 714 696 676 657 638 620 602 585 569 554 541 530 521 514 509 506 39 950 949 947 943 939 932 925 916 905 894 881 868 853 837 821 804 786 768 749 731 711 692 672 653 634 615 597 579 563 548 535 523 514 507 502 498 40 949 949 947 943 938 932 924 915 904 893 880 866 851 836 819 802 784 765 747 727 708 688 668 649 629 610 592 574 557 542 528 517 507 499 494 491 41 949 948 946 942 937 931 923 914 903 892 879 865 850 834 817 799 781 763 744 724 704 684 664 645 625 606 587 569 552 536 522 510 500 492 487 484 42 948 948 945 942 937 930 922 913 902 890 877 863 848 832 815 797 779 760 740 721 701 680 660 640 620 601 582 564 546 530 516 503 493 485 480 477 43 947 947 944 941 936 929 921 912 901 889 875 861 846 829 812 794 776 757 737 717 697 677 656 636 616 596 577 558 541 524 509 497 486 478 473 470 44 946 945 943 940 934 928 920 910 899 887 873 859 843 827 810 792 773 754 734 714 693 673 652 631 611 591 572 553 535 518 503 490 480 471 465 462 45 945 944 942 938 933 926 918 908 897 885 871 857 841 824 807 789 770 750 730 710 689 668 648 627 606 586 567 548 530 512 497 484 473 465 458 455 46 943 942 940 936 931 924 916 906 895 883 869 854 839 822 804 786 767 747 727 706 685 664 643 622 602 581 562 543 524 507 491 477 466 458 451 448 47 941 941 938 935 929 922 914 904 893 880 867 852 836 819 801 783 763 743 723 702 681 660 639 618 597 576 556 537 519 501 485 471 460 451 445 440 48 939 939 936 932 927 920 912 902 891 878 864 849 833 816 798 779 760 740 719 698 677 656 634 613 592 571 551 532 513 496 479 465 454 444 438 434 49 937 936 934 930 925 918 909 900 888 875 861 846 830 813 795 776 756 736 715 694 673 651 630 608 587 566 546 527 508 490 473 459 447 438 431 427 Inclination (variation from horizontal) 50 935 934 932 928 922 915 907 897 885 872 858 843 827 809 791 772 752 732 711 690 669 647 625 604 582 561 541 521 502 485 468 453 441 431 425 420 51 932 931 929 925 920 913 904 894 882 869 855 840 823 806 788 768 749 728 707 686 664 642 621 599 577 556 536 516 497 479 462 447 435 425 418 414 52 929 928 926 922 917 910 901 891 879 866 852 836 820 802 784 765 745 724 703 681 660 638 616 594 572 551 531 511 492 473 456 441 429 419 412 407 53 926 925 923 919 913 906 898 888 876 863 848 833 816 799 780 761 741 720 699 677 655 633 611 589 567 546 525 505 486 468 451 436 423 413 405 401 54 923 922 920 916 910 903 894 884 872 859 845 829 812 795 776 756 736 716 694 672 650 628 606 584 562 541 520 500 481 463 445 430 417 407 399 395 55 919 918 916 912 906 899 891 880 869 855 841 825 808 791 772 752 732 711 690 668 646 623 601 579 557 536 515 495 476 457 440 424 411 401 393 389 56 915 915 912 908 903 896 887 876 865 851 837 821 804 786 767 748 727 706 685 663 641 619 596 574 552 531 510 489 470 452 434 419 405 395 387 383 57 911 911 908 904 899 891 883 872 860 847 833 817 800 782 763 743 723 702 680 658 636 614 591 569 547 525 504 484 465 446 429 413 400 389 381 377 58 907 906 904 900 895 887 879 868 856 843 828 812 795 777 758 739 718 697 675 653 631 609 586 564 542 520 499 479 459 441 424 408 394 383 376 371 59 903 902 900 896 890 883 874 864 852 838 824 808 791 773 754 734 713 692 670 648 626 603 581 558 536 515 494 474 454 435 418 402 389 378 370 365 60 898 897 895 891 886 878 870 859 847 834 819 803 786 768 749 729 708 687 665 643 621 598 576 553 531 509 488 468 449 430 413 397 383 372 364 359 61 893 893 890 886 881 873 865 854 842 829 814 798 781 763 744 724 703 682 660 638 616 593 570 548 526 504 483 463 443 425 407 392 378 367 358 354 62 888 888 885 881 876 868 860 849 837 824 809 793 776 758 739 719 698 677 655 633 610 588 565 542 520 498 478 457 438 419 402 386 373 361 353 348 63 883 882 880 876 870 863 854 844 832 819 804 788 771 753 733 713 693 671 650 627 605 582 559 537 515 493 472 452 432 414 397 381 367 356 348 343 64 878 877 874 870 865 858 849 839 827 813 798 782 765 747 728 708 687 666 644 622 599 577 554 531 509 488 467 447 427 409 391 376 362 351 342 337 Inclination (variation from horizontal), ° 65 872 871 869 865 859 852 844 833 821 808 793 777 760 742 722 702 682 660 639 616 594 571 548 526 504 482 461 441 422 404 386 371 357 346 337 332 66 866 865 863 859 854 847 838 827 816 802 787 771 754 736 717 697 676 655 633 611 588 566 543 521 498 477 456 436 416 398 381 366 352 341 332 327 67 860 859 857 853 848 841 832 821 810 796 782 766 748 730 711 691 670 649 627 605 582 560 537 515 493 471 450 430 411 393 376 360 347 336 327 322 68 854 853 851 847 841 834 826 815 803 790 775 760 743 724 705 685 665 643 622 599 577 554 531 509 487 466 445 425 406 387 371 355 342 331 322 317 69 847 846 844 840 835 828 819 809 797 784 769 753 737 718 699 679 659 637 615 593 571 548 526 503 482 460 439 419 400 382 366 350 337 326 318 313 70 841 840 838 834 828 822 813 803 791 778 763 747 730 712 693 673 652 631 609 587 565 542 520 498 476 454 434 414 395 377 360 345 332 321 313 308 71 834 833 831 827 822 815 806 796 784 771 756 741 723 705 687 667 646 625 604 581 559 537 514 492 470 449 428 409 389 372 355 340 327 316 308 303 72 827 826 824 820 815 808 799 789 778 764 750 734 717 699 680 661 640 619 597 575 553 531 508 486 464 443 422 403 384 367 350 335 322 311 303 298 73 819 819 816 813 808 801 792 782 771 757 743 727 711 693 674 654 634 613 591 569 547 525 503 480 459 437 417 397 379 361 345 330 317 307 298 294 74 812 811 809 805 800 793 785 775 764 750 736 720 704 686 667 648 627 606 585 563 541 519 496 474 453 432 411 392 374 356 340 325 312 302 294 289 75 804 804 801 798 793 786 778 768 756 743 729 713 697 679 661 641 621 600 578 557 535 512 490 469 447 426 406 386 368 351 335 320 308 297 289 285 76 796 796 794 790 785 779 770 760 749 736 722 707 690 672 653 634 614 593 572 550 528 506 484 462 441 420 400 381 363 346 330 315 303 293 285 280 77 788 788 786 782 777 771 762 753 741 729 714 699 683 665 646 627 607 587 565 544 522 500 478 457 435 415 395 376 358 341 325 310 298 288 280 276 78 780 780 777 774 769 763 755 745 734 721 707 692 675 658 640 620 600 580 559 537 516 494 472 450 430 409 390 370 352 335 320 306 294 283 276 271 79 772 771 769 766 761 754 747 737 726 713 700 684 668 651 633 614 594 573 552 531 509 488 466 445 424 403 384 365 347 330 315 301 289 279 271 267 80 763 762 761 757 753 746 739 729 718 705 692 677 661 643 625 607 587 566 545 525 503 481 460 439 418 397 378 359 342 325 310 296 284 274 267 263 81 755 754 752 749 744 738 730 721 710 698 684 669 653 636 618 599 580 560 539 518 497 475 454 433 412 392 372 354 337 320 305 291 279 270 263 258 82 745 745 743 740 735 729 721 712 701 689 676 661 645 628 611 592 572 553 532 511 490 469 447 426 406 386 367 349 331 315 300 287 275 265 258 254 83 736 736 734 731 726 720 713 704 693 681 668 653 637 621 603 585 565 545 525 504 483 462 441 420 400 380 361 343 326 310 295 282 270 261 254 250 84 727 727 725 722 717 712 704 695 685 673 660 645 630 613 596 577 558 538 518 498 477 456 435 415 394 375 356 338 321 305 290 277 266 256 249 245 85 718 717 715 713 708 703 695 687 676 664 651 637 622 605 588 569 551 531 511 491 470 449 429 408 388 369 350 332 316 300 285 273 261 252 246 241 86 708 708 706 703 699 693 686 677 667 656 643 628 613 597 580 562 543 525 504 484 464 443 422 402 382 363 345 327 311 295 281 268 257 248 241 237 87 698 698 696 694 689 684 677 668 659 647 634 620 605 589 572 554 536 517 497 477 457 436 416 396 376 357 339 322 306 290 276 264 252 244 237 233 88 689 688 686 683 680 674 668 659 649 638 626 612 597 581 564 547 528 509 489 470 450 430 410 390 371 352 334 317 300 285 271 259 248 239 233 229 89 678 678 677 674 670 665 658 650 640 629 617 603 589 573 556 539 521 502 482 463 443 423 403 384 365 346 328 311 295 281 267 254 244 235 229 225 90 668 668 666 664 660 655 649 640 631 620 608 595 580 565 548 531 513 495 476 456 437 417 397 378 359 340 323 306 290 276 262 250 239 231 225 221

All 58 properties on the FLATLINE site are on a fixed axis and therefore have a total of four potential orientations. Only 3 different roof angles apply. This provides 12 variations of performance, as per Table 13 below. Table 12: Specific Annual Yield variations for FLATLINE (kWh/kWp)

Orientation (° from south) Inclination (°) S-113° (67°) S-23° (157°) S+67° (247°) S+157° (337°) ENE SSE WSW NNW 35° 670 932 843 551 45° 627 916 824 484 50° 604 897 809 453

For the purposes of this report, shading is excluded and a shading factor (6) of 1 applies. Consideration for the position of PV modules, discussed below, minimises shading as far as practically possible. In addition, the developer of the site has also suggested that indicated chimneys are for aesthetic purposes only and can potentially be removed where they are proven to have a detrimental impact on PV performance.

DETERMINING PV SYSTEM CAPACITY PER HOUSE TYPE Determining the potential PV capacity for each roof has allowed the total annual yield to be calculated for each house type on the FLATLINE site. The Sketchup models mentioned above were used to help determine this. Minus7 have provided indicative data on the specification and performance of their integrated PV product. In essence, solar PV cells can be laminated onto standard Minus7 tiles so that the product can produce both heat and electricity. One of the potential benefits of combining these technologies is improved PV performance: PV power is indirectly proportional to temperature and temperature is reduced within the panel by heat being conducted away for beneficial thermal use in the property. It also means that neither technology (PV or solar thermal) needs to be sacrificed to provide space for the other, allowing larger areas for electrical and thermal energy generation respectively. Figure 17 is an example of an existing Minus7 installation with integrated PV. Figure 17: Existing Minus7 installation with integrated PV (Minus7, 2018)

Minus7 have previously estimated potential PV capacities on some roofs for the FLATLINE site however these calculations assumed an efficiency of 150W/m2, in line with the solar cell efficiency quoted in data sheets supplied by GBSol. In practice, the 170mm-high cells are laminated onto a 203mm-high tile, which reduces efficiency per unit area. It is calculated that a single Minus7 tile will have PV capacity of approximately 26.1W, as per Figure 18 below, which equates to 128W/m2. Figure 18: Assumed Minus7 tile specification

In their high level estimations, Minus7 also assumed that entire roof areas could be covered, which in practice is not possible due to proximity to obstacles. Both assumptions suggest that an overestimation of potential PV capacity has been made at the site to date, hence new calculations have been made for the purposes of this study that have taken account the effect of these various factors. Minus7 have suggested that a 203mm and 400mm buffer should be included at the ridge/gutter and eaves respectively. In addition, a 400mm buffer is included at property boundaries (semi-detached/terraced) to avoid ownership issues, although this may not be required if the site is under single ownership, as would be expected for FLATLINE. Each house type has been modelled to determine the potential PV capacity using the Minus7 system. Layouts aim to minimise significant shading. Every roof area is considered in this

75 instance, but due to the bespoke nature of the product, small arrays (<1kWp) may prove uneconomical. Multiple small arrays may also prove difficult to connect to inverters. Figure 19 illustrates the potential PV capacity on each house type.

[Type here]

Figure 19: Potential solar PV capacity on each house type

HT1 DP1 CH1_HT12B DP2 CH1 HT1 DP1 CH1_HT2G DP0 CH1 HT1 DP2 CH0_HT2G DP0 CH1 HT1 DP2 CH1 HT12B DP2 CH1

D D D D

C E C E C E C E

B A B A B A B A

Roof Area (m2) Angle (°) Minus7 kWp Roof Area (m2) Angle (°) Minus7 kWp Roof Area (m2) Angle (°) Minus7 kWp Roof Area (m2) Angle (°) Minus7 kWp A 27.5 35 74 1.93 A 27.5 35 74 1.93 A 25.6 35 48 1.25 A 25.6 35 48 1.25 B 25.7 35 78 2.04 B 25.7 35 78 2.04 B 25.7 35 78 2.04 B 25.7 35 78 2.04 C 10.8 50 22 0.57 C 10.8 50 22 0.57 C 10.8 50 22 0.57 C 10.8 50 22 0.57 D 44.1 50 137 3.58 D 46.7 50 180 4.70 D 46.7 50 180 4.70 D 44.1 50 137 3.58 E 12.3 50 26 0.68 E 44.1 50 26 0.68 E 44.1 50 26 0.68 E 12.3 50 26 0.68

HT4v2 DP3 CH2 HT4v2 DP4 CH2 HT10 DP2 CH0 HT10 DP2 CH2

B B

A A

Roof Area (m2) Angle (°) Minus7 kWp Roof Area (m2) Angle (°) Minus7 kWp Roof Area (m2) Angle (°) Minus7 kWp Roof Area (m2) Angle (°) Minus7 kWp A 34.2 45 40 1.04 A 34.2 45 64 1.67 A 49.4 35 77 2.01 A 50.6 35 70 1.83 B 32.9 45 140 3.65 B 32.9 45 140 3.65 B 47.6 35 187 4.88 B 48.7 35 183 4.78

[Type here]

For each house type, the area, inclination, number of Minus7 tiles and potential system capacity for each roof is noted. BRE then determined the feasibility of PV for each of the 58 FLATLINE properties, prioritising less northerly- facing and unshaded aspects, to determine potential system capacities (kW) for each. Due to variations of house types, orientations, roof angles and PV capacities, providing accurate yield data for each plot would require considerable analysis that falls outside the scope of this initial feasibility study. Indeed, a tool to help speed up this process is a natural progression of this work. Instead, the average PV capacity for each house type is derived, along with the most prevalent orientation and inclination for a particular house type. This provides a reasonable representation of potential PV capacities/ yields whilst also demonstrating the performance of PV systems at different orientations/ inclinations, and thus the potential for capacity increase/decrease. Details for individual house types and the FLATLINE site as a whole is set out in Table 14 below. The FLATLINE site of 58 properties will provide 164kW of solar PV capacity and generate approximately 130 MWh electricity per year. Table 13: Solar PV capacity and yield for each house type

Specific House House FLATLINE House Contribution Orientation, Inclination, Annual No PV, yield, site yield, type to site, kWp ° ° Yield, kWp kWh/year MWh/year kWh/kWp HT1 18 2.73 49.23 S+67 35 843 2,305 41.5 HT2 5 4.26 21.30 S-23 50 915 3,898 19.5 HT4v2 20 2.34 46.77 S-23 45 926 2,165 43.3 HT10 2 1.65 3.30 S+67 35 843 1,391 2,8 HT12A 9 2.69 24.22 S+157 50 453 1,219 11.0 HT12B 4 4.83 19.31 S-113 50 604 2,916 11.7

Total 58 164.13 129.8

DETERMINING DAILY GENERATION PROFILES FOR EACH HOUSE TYPE The FLATLINE project requires the determination of how the calculated annual yields for each property type are proportioned over the year in short timescales (e.g. half-hour). Being able to predict generation from a PV system at a particular time on a particular day will allow for a more robust model with improved accuracy. Photovoltaic Geographical Information System (PVGIS) is a free online tool that can be used to determine irradiance data anywhere in the world. Daily irradiance data from this source provides irradiance (W/m2) that falls on a fixed plane at 15-minute intervals for a typical (average) day of each month. Whilst data is available for individual years, irradiation profiles can vary considerably on a monthly/weekly/daily/hourly basis from one to year to the next and therefore it is more appropriate to use average profiles. Daily global irradiance data for each house type has been downloaded using the exact site location (51° 34’ 42 14 N, 3° 27’ 13.99 W) and is used throughout the calculations. Figure 20 illustrates the typical daily global irradiance in June for HT4v2 (S-23°, 45°), HT1 (S+67°, 35°) and HT12B (S-113°, 50°). It can be seen that HT4v2 has a typical bell-curve profile with its peak around midday, as would be expected for a south-facing array. HT1 is more westerly facing and hence its peak shifts to later into the afternoon. HT12B is easterly facing with a steeper pitch and hence its peak is lower and shifts to earlier in the morning. Such information is crucial in helping to determine site energy flows and potential capacity upturn/downturn opportunities. A daily profile has been created for each month for each house type, to produce a 12-day-year of global irradiance for each. It is assumed that each day of each respective month is the same and once extrapolated, a total annual global irradiance can be derived. Each 15-minute interval can then be divided by the total to provide an annual proportion (as a percentage) of irradiance (W/m2) that falls on a plane in any given 15-minute period. These percentages are multiplied by the predicted annual yield (kWh) of a PV system to determine generation yield from a system in a 15-minute period. This data is aggregated into half-hourly bins in line with traditional grid services to provide a 12-day-year PV system yield (kWh) per half-hour period for each house type. Figure 21 illustrates the 12- 78 day year generation profile for each house type. The changes to the traditional bell curve profiles in the winter months are caused by horizon lines obscuring the low sun. Figure 20: Average Daily Global Irradiance on a Fixed Plane (June)

Average Daily Global Irradiance on a Fixed Plane (June) 600 ) 2 500

400

300

200

100 Global irradiance (W/m 0 4:07 4:37 5:07 5:37 6:07 6:37 7:07 7:37 8:07 8:37 9:07 9:37 10:07 10:37 11:07 11:37 12:07 12:37 13:07 13:37 14:07 14:37 15:07 15:37 16:07 16:37 17:07 17:37 18:07 18:37 19:07 19:37 20:07 Time (HH:MM)

HT4v2 (S-23°, 45°) HT1 (S+67°, 35°) HT12B (S-113°, 50°)

Figure 21: Average Daily Solar PV System Yield (kWh) per Half-Hourly Period for each house type

HT1 Average Daily Solar PV System Yield (kWh) per Half-Hourly Period 1.1 1 0.9 January

0.8 February 0.7 March April 0.6 May

0.5 June 0.4 July August Yield (kWh/half hour) (kWh/half Yield 0.3 September

0.2 October 0.1 November December 0 0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 0:00 GMT (HH:MM)

79 HT2G Average Daily Solar PV System Yield (kWh) per Half-Hourly Period 1.1 1 0.9 January

0.8 February 0.7 March April 0.6 May

0.5 June 0.4 July August Yield (kWh/half hour) (kWh/half Yield 0.3 September

0.2 October 0.1 November December 0 0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 0:00 GMT (HH:MM)

HT4v2 Average Daily Solar PV System Yield (kWh) per Half-Hourly Period 1.1 1 0.9 January

0.8 February 0.7 March April 0.6 May

0.5 June 0.4 July August Yield (kWh/half hour) (kWh/half Yield 0.3 September

0.2 October 0.1 November December 0 0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 0:00 GMT (HH:MM)

HT10 Average Daily Solar PV System Yield (kWh) per Half-Hourly Period 1.1 1 0.9 January

0.8 February 0.7 March April 0.6 May

0.5 June 0.4 July August Yield (kWh/half hour) (kWh/half Yield 0.3 September

0.2 October 0.1 November December 0 0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 0:00 GMT (HH:MM)

HT12A Average Daily Solar PV System Yield (kWh) per Half-Hourly Period 1.1 1 0.9 January

0.8 February 0.7 March April 0.6 May

0.5 June 0.4 July August Yield (kWh/half hour) (kWh/half Yield 0.3 September

0.2 October 0.1 November December 0 0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 0:00 GMT (HH:MM)

81 HT12B Average Daily Solar PV System Yield (kWh) per Half-Hourly Period 1.1 1 0.9 January

0.8 February 0.7 March April 0.6 May

0.5 June 0.4 July August Yield (kWh/half hour) (kWh/half Yield 0.3 September

0.2 October 0.1 November December 0 0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 0:00 GMT (HH:MM)

DETERMINING ELECTRICITY FLOWS FOR EACH HOUSE TYPE Figure 22 illustrates the 12-day year overall electricity flow profile for each house type. Note that negative values occur when solar generation is meeting all demands on site and excess is being exported back to the grid. Figure 22: Average Daily Electricity Flows (kWh) per Half-Hourly Period for each house type

HT1 Average Daily Electricity Flows (kWh) per Half-Hourly Period 1.0

0.8

January 0.6 February 0.4 March April 0.2 May June

0.0 July

0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 0:00 August -0.2 September

October

ElectricityFlow (kWh/half hour) -0.4 November

-0.6 December

-0.8 GMT (HH:MM)

82 HT2G Average Daily Electricity Flows (kWh) per Half-Hourly Period 1.0

0.8

January 0.6 February 0.4 March April 0.2 May June

0.0 July

0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 0:00 August -0.2 September

October

ElectricityFlow (kWh/half hour) -0.4 November

-0.6 December

-0.8 GMT (HH:MM)

HT4v2 Average Daily Electricity Flows (kWh) per Half-Hourly Period 1.0

0.8

January 0.6 February 0.4 March April 0.2 May June

0.0 July

0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 0:00 August -0.2 September

October

ElectricityFlow (kWh/half hour) -0.4 November

-0.6 December

-0.8 GMT (HH:MM)

83 HT10 Average Daily Electricity Flows (kWh) per Half-Hourly Period 1.0

0.8

January 0.6 February 0.4 March April 0.2 May June

0.0 July

0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 0:00 August -0.2 September

October

ElectricityFlow (kWh/half hour) -0.4 November

-0.6 December

-0.8 GMT (HH:MM)

HT12A Average Daily Electricity Flows (kWh) per Half-Hourly Period 1.0

0.8

January 0.6 February 0.4 March April 0.2 May June

0.0 July

0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 0:00 August -0.2 September

October

ElectricityFlow (kWh/half hour) -0.4 November

-0.6 December

-0.8 GMT (HH:MM)

84 HT12B Average Daily Electricity Flows (kWh) per Half-Hourly Period 1.0

0.8

January 0.6 February 0.4 March April 0.2 May June

0.0 July

0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 0:00 August -0.2 September

October

ElectricityFlow (kWh/half hour) -0.4 November

-0.6 December

-0.8 GMT (HH:MM)

From this data it is possible to determine total import and export electricity flows for the 12-day year with PV, which can then be compared with the demand profile for a scenario without PV. Figure 23 illustrates this for each of the house types. As expected, the reduction of imported grid power is most significant during months with higher irradiance (summer). HT12A shows virtually no export over the year, whereas by comparison HT2G shows export over nearly all months. This highlights the benefit that may be gained by potentially mixing dwelling types to balance out generation peaks at a site level. Figure 23: Total Average Daily Electricity Flows with and without PV (kWh) for each house type

HT1 Total Average Daily Electricity Flows with and without PV (kWh) 25.0

20.0

15.0

10.0

5.0 Electricity (kWh) 0.0

-5.0

-10.0 Month

Import (no PV) Import (with PV) Export (with PV)

85 HT2G Total Average Daily Electricity Flows with and without PV (kWh) 25.0

20.0

15.0

10.0

5.0 Electricity (kWh) 0.0

-5.0

-10.0 Month

Import (no PV) Import (with PV) Export (with PV)

HT4v2 Total Average Daily Electricity Flows with and without PV (kWh) 25.0

20.0

15.0

10.0

5.0 Electricity (kWh) 0.0

-5.0

-10.0 Month

Import (no PV) Import (with PV) Export (with PV)

86 HT10 Total Average Daily Electricity Flows with and without PV (kWh) 25.0

20.0

15.0

10.0

5.0 Electricity (kWh) 0.0

-5.0

-10.0 Month

Import (no PV) Import (with PV) Export (with PV)

HT12A Total Average Daily Electricity Flows with and without PV (kWh) 25.0

20.0

15.0

10.0

5.0 Electricity (kWh) 0.0

-5.0

-10.0 Month

Import (no PV) Import (with PV) Export (with PV)

87 HT12B Total Average Daily Electricity Flows with and without PV (kWh) 25.0

20.0

15.0

10.0

5.0 Electricity (kWh) 0.0

-5.0

-10.0 Month

Import (no PV) Import (with PV) Export (with PV)

12-day-year data can be extrapolated to provide a full annual half-hour dataset (17,520 data points) for both demand and generation. This allows for accurate headline figures to be drawn upon. Table 15 provides such figures for each house type and for the FLATLINE site as a whole. Table 14: Generation and export figures for each house type and the total FLATLINE site

Total House type HT1 HT2G HT4v2 HT10 HT12A HT12B site Total annual household 5,261 5,489 5,489 5,261 5,489 5,489 313,803 demand (kWh) Annual PV yield (kWh) 2,305 3,898 2,165 1,391 1,215 2,916 129,697 Annual self-consumption 1,595 1,975 1,667 1,213 1,606 1,765 99,647 (kWh) Annual export (kWh) 710 1,923 498 178 13 1,151 30,050 Grid household demand 3,665 3,514 3,822 4,048 4284 3,724 214,156 (KWh) Utilisation factor (%) 69% 51% 77% 87% 99% 61% 77%

88 APPENDIX D SYSTEM DESCRIPTIONS

SONNEN BATTERIES

MINUS7 SOLAR ASSISTED HEAT PUMP SYSTEM

89 APPENDIX E FLATLINE "CONTROL LOGIC"

In order to undertake the FLATLINE feasibility study, it has been necessary to develop as part of the work an early version of the decision-making processes that determines when the electrical and thermal storage is drawn from the National Grid. This is required since the provision of storage allows the electrical and heat demand from the homes to not simply be 'passed through' to the Grid, but for this demand to be decoupled and triggered at other times. This decoupling of when the demand impacts the Grid is a core goal of FLATLINE, but also necessitates a process to be put in place to decide when the demand should be triggered. This decision-making process is the nascent "Control Logic" for the FLATLINE energy management. For the purposes of this feasibility study, a basic control logic has been developed in a spreadsheet format. This receives the key input variables which have been calculated, namely: 1. ½ hourly electrical demand from the homes 2. ½ hourly thermal demand from the homes 3. ½ hourly renewable generation from the homes 4. ½ hourly CoP efficiency of the Minus7 system 5. ½ hourly market price forecast Using these input variables, each row of the spreadsheet assesses that ½ hour period, and reviews future ½ hourly timeslots (lower rows) to anticipate future variables up to the limit of the forecasting period or system's available storage capacity. The Control Logic principles (below) are then applied through multiple columns of formula, and the resultant impact on storage followed through to the following ½ hour period. This new row then uses that revised storage level as the starting point to repeat the calculations for the next ½ hour period. This spreadsheet has been constructed to model five identical representative days for each month of the year, equating to 2,880 rows that each calculate the Control Logic for that given ½ hour. For the graphed outputs used in this report, the third day of each month has been used; this reduces the change of the previous or subsequent month affecting the results. Whilst this tool has presented valuable results and patterns for the feasibility study, it is acknowledged that despite only being a prototype it is already functioning at the limits of what can be built within a spreadsheet, and that some aspects are not fully functional. If selected to proceed to the Demonstration phase, the FLATLINE team will use this basis as a starting point for development of a more sophisticated Control Logic. This will be developed as a 'machine readable' programme for integration into the system architecture. Given the presence of "big data" for the Demonstration, there is also the possibility of the application of Machine Learning to allow the initial Control Logic to be iteratively and automatically evolved as the dataset from the Demonstration homes becomes larger.

90 BATTERY STORAGE CONTROL LOGIC – V1 The fundamental principle of the Battery Storage Control Logic is that, without any external influences (such as a response to a DSR call made by the system's controller), the automated system should endeavour to achieve the lowest possible price for the supply of electrical energy to the home. Working within the framework outlined above, a summary of the main battery operating rules is: 1. Renewable Generation is fed to meet Occupant Demand. Scenarios within this primary rule are: a. If Renewable Generation is less than Occupant Demand, Current Battery Storage Level is Discharged (and the percentage efficiency of battery system is applied to this discharge) b. If Renewable Generation is less than Occupant Demand and Battery Storage, Grid Power is used c. If Renewable Generation is greater than Occupant Demand, Battery Storage is Charged d. If Renewable Generation is greater than Occupant Demand and Battery Storage Capacity, Export is flagged (this is currently to grid, but more likely to heat store) 2. Grid Prices are Negative will trigger ‘buying’ electricity up to Maximum Battery Storage Capacity. Scenarios within this rule are: a. At the lowest forecast negative grid price within the user-determined forecast period, the system will ‘buy’ an amount of electricity that is the lesser of; b. The Maximum Battery Storage Capacity minus the Current Battery Storage Level. c. The Maximum Total Battery Charge Capacity 3. Demand is greater than Generation for the Total Forecast Period will trigger buying at the lowest price window. Conditions within this rule are: a. The forecast window is defined as the lesser of; b. The user-determined forecast period (which can be up to 24 hours) c. The period of time that the Available Battery Storage Capacity could meet the Forecast Excess Demand beyond the point that the battery is discharged THERMAL STORAGE CONTROL LOGIC – V1 The fundamental principle of the Thermal Storage Control Logic is that, without any external influences (such as a response to a DSR call made by the system's controller), the automated system should endeavour to achieve the lowest possible price for the supply of thermal energy to the home. Working within the framework outlined above, a summary of the main the thermal store operating rules is: 4. Thermal Storage Heat is fed to meet Occupant Demand. Scenarios within this primary rule are: a. If Thermal Storage Heat is greater than Occupant Demand, the thermal store feeds the demand, b. If Thermal Storage Heat is less than Occupant Demand, the Heat Pump is triggered to meet the excess demand (using the CoP and percentage efficiency of system applied to this. Note the CoP also captures the direct feed of solar thermal to meet demand via a very high CoP value). 5. Renewable Generation is greater than Occupant Demand. Scenarios within this rule are: a. If Renewable Generation is greater than Occupant Demand, excess generation is used to charge the Thermal Storage if the Battery Storage is already at capacity, b. If Renewable Generation is greater than Occupant Demand, excess generation is used transferred to the ground (Minus7 "cold store") if the Battery Storage and Hot Store are already at capacity, 6. Demand is greater than Generation for the Total Forecast Period will trigger the Heat Pump at the lowest value window for thermal energy. The thermal energy value is a calculated as 1/CoP multiplied by price: Conditions within this rule are: a. The forecast window is defined as the lesser of; b. The user-determined forecast period (which can be up to 24 hours), c. The period of time that the Available Thermal Storage Capacity could meet the Forecast Excess Demand beyond the point that the thermal store is discharged

91 APPENDIX F SENSORS & MONITORING SUPPORTING INFORMATION

As summarised in the main body of the report, a range of monitoring equipment is intended to be installed in the homes to measure their energy usage, to assess the operation of the FLATLINE concept at Demonstration stage, and to gather data for the future iterative development of the Control Logic that underpins the Sero Energy model. This appendix sets out further details that underpin the need for sensing and metering equipment that has been proposed for the pilot site. 1. Weather/External Environment, all half hourly data (or less): a. Wind speed average for period (mph) b. Wind speed maximum in period (mph) c. Wind direction (min. 16 point compass), d. Rainfall (mm) e. Temperature (˚C) f. Relative Humidity (%) g. Dew Point (˚C) h. Atmospheric pressure (hPa) i. Solar irradiance (including cloud cover) (W/m2)

External temperature is a key parameter for determining heating demand and/ or heat loss for a building. The dew point is used to calculate relative humidity (RH); dewpoint/ RH measurements can also be used to identify periods of rainfall (i.e. 100% RH). Solar irradiance informs of solar energy that may be available to PV and solar thermal systems, and may also give insight into potential solar gains for a dwelling (and subsequent risk of summer overheating).

2. Internal Environment, all half hourly data (or less): a. Living room internal temperature (˚C), b. Living room internal relative humidity (%) c. Living room carbon dioxide levels (PPM),

Internal temperature and humidity can reflect relative comfort factors for occupants. Building Regulations requires that RH should be controlled below certain levels with appropriate ventilation (typically below 65% for extended periods of time), as high RH can have health implications for occupants as well as potentially leading to condensation and damage to the building fabric at elevated levels. Temperature information is required to calculate RH and itself can indicate excessive heating or cooling beyond typical comfort ranges.

CO2 is also a measure of occupant comfort conditions and reflects the adequacy of ventilation. Occupants generate CO2 when they breathe and while elevated levels are not generally a threat to health, it can affect productivity and the impression of comfort within the environment. High CO2 concentrations are generally indicative of inadequate ventilation to displace the CO2 and provide fresh air. CO2 degradation rates (when occupants have left the room, but no windows have been opened to purge the space) can be an indicator of airtightness/ air permeability of the construction.

Measuring multiple rooms in a dwelling will indicate local conditions, but will increase the cost of monitoring exponentially. In addition, measuring wet rooms such as kitchens and bathrooms are likely to give misleading results, since these spaces are expected to experience peaks in temperature and RH that may temporarily go beyond typical comfort conditions. If adequately ventilated, this should have a limited effect throughout the rest of the property. Since occupants are generally expected to spend most time within the living room, this would be anticipated as the primary measurement point for a dwelling. Other rooms (e.g. bedrooms) may be monitored to confirm comfort conditions are met elsewhere in a property if budget allows. If only a single additional monitoring location is selected, a central circulation space (often a landing area) that experiences mixing of temperature and ventilation effects from surrounding rooms would be a useful secondary measurement source to provide an indication of likely conditions throughout the rest of the property.

3. Renewables, all half hourly data (or less): a. Total energy generated (kWh or kWht) b. Electricity export meter (kWh)

Electricity or heat generating technologies will invariably require a meter to log energy generation for billing/ incentive payment purposes (RHI, FIT). Regardless of this, understanding generation can help to understand the best times to offset consumption and to what extent, and will create a long term view of the scale of generation that

92 may be expected. It can also indicate if/ when a system is not performing optimally if generation stops or changes uncharacteristically.

Heat generating technologies will obviously require different metering systems than electricity generating technologies, as one will measure electricity and the other thermal energy. Export electricity meters would also be useful to install to understand to what extent any generated energy is used to offset instantaneous usage compared to what is ultimately exported to the grid.

4. Electricity Usage, all half hourly data (or less): a. Total electrical energy used (kWh) b. Regulated electricity usage (kWh) c. Unregulated electricity usage (kWh)

While total electricity usage can be measured by a single meter (usually for billing purposes), to understand usage that is related to the operation of the property (regulated usage – lighting, and auxiliary energy for pumps and fans) compared to that which is at the sole discretion of the occupants (unregulated energy – appliances and other small loads), it is necessary to carry out some degree of sub metering of separate electrical circuits. The extent of this may vary according to the arrangement of the electrical consumer unit. It may be possible to install a meter that reads only the regulated electricity circuits in combination, but it is more likely that a number of individual circuits will be metered. Theoretically, the unregulated usage can be calculated by subtracting the measured regulated circuits from the total electricity usage. However, variation in relative meter accuracy may introduce a level of error that may not be quantified unless all sub circuits are in fact monitored.

If the intention is ultimately to control specific appliances to actively shift loads to specified times of the day, it would be preferable to ensure that such appliances are measured via their own circuit on a consumer unit, so the extent and benefit from such actions can be monitored.

7. Water Usage, all half hourly data (or less): a. Total water usage (litres) b. Hot water usage (litres),

Although of most interest will be hot water usage, total water usage will need to be monitored from a billing perspective. In addition, hot water consumption should also be measured in order to create an accurate view of the associated heating energy demand. This will help to create a more accurate overview of occupant usage patterns and the capacity to potentially shift the associated energy burden.

3. Occupant Information* a. Basic Occupant Information including; i. Number of occupants ii. Number of occupants typically away from home in the daytime (i.e. at work) iii. Age groups of occupants b. Survey response(s) from Occupant Surveys *Occupant Information may be subject to GDPR/data privacy and might require their consent.

It will be necessary to collect additional information about the occupants/ occupancy of the dwellings via survey to give context to the physical monitoring that is proposed. At the design stage, it is necessary to estimate the number of occupants that may be present in each dwelling (based on bedrooms), and subsequent energy demand forecasts are based on these assumptions. However, actual occupancy numbers may vary and knowing this is important to assess how typical the measured energy usage patterns are of a house type and/ or occupancy profile. An appropriate survey will be developed to capture this information and other aspects that can help explain measured pattern of energy consumption.

93 APPENDIX G DEVICE LEVEL SECURITY FOR SAMSUNG APPLIANCES

SECURITY Security is key to Samsung’s business and Samsung is a leader in defence grade security which it initially developed for its mobile devices, but which is being extended across all IoT devices. Knox consists of a highly secure platform built into Samsung devices and a set of solutions that leverage this platform. Samsung's Knox Platform is fused into devices at both the hardware and software level, underneath the operating system. The description below refers to mobile device security, but the approach is being transferred across to all appliances: Hardware Root of Trust Three hardware components are the foundation of Samsung KNOX’s trusted environment. The Device Root Key (DRK) is a device-unique asymmetric key that is signed by Samsung through an X.509 certificate. This certificate attests that the DRK was produced by Samsung. The DRK is injected in the device during the manufacturing process in the Samsung factory, and is only accessible by specially privileged software modules within the TrustZone Secure World. Because the DRK is device-unique, it can be used to identify a device. For example, a certificate included with TIMA attestation data is signed by DRK (more precisely, through a key attested by the DRK), which proves that the attestation data originated from the TrustZone Secure World on a Samsung device. KNOX also uses device-unique hardware keys and keys derived from the hardware keys, which are only accessible in the TrustZone Secure World. Such keys can be used to tie data to a device. KNOX Workspace data, for example, is encrypted using such a key, and cannot be decrypted on any other devices.

The Samsung Secure Boot key is used to sign Samsung-approved executables of boot components. The public part of the Samsung Secure Boot key is stored in hardware at the time of manufacture in the Samsung factory. The Secure Boot process uses this public key to verify whether each boot component is approved. Rollback prevention fuses are hardware fuses that encode the minimum acceptable version of Samsung-approved executables. Because old images may contain known vulnerabilities that can be exploited, this feature prevents approved-but-old versions of boot executables from being loaded. SECURE BOOT AND TRUSTED BOOT The startup process for Android begins with the primary bootloader, which is loaded from Read-only Memory (ROM). This code performs basic system initialization and then loads another bootloader, called a secondary bootloader, from the file system into Random-Access Memory (RAM) and executes it. Multiple secondary bootloaders may be present, each for a specific task. The boot process is sequential in nature with each secondary bootloader completing its task and executing the next secondary bootloader in the sequence, finally loading the last bootloader (sometimes known as aboot), which loads the Android kernel. Secure Boot is a security mechanism that prevents unauthorized bootloaders and operating systems from loading during the startup process. Secure Boot is implemented by each bootloader cryptographically verifying the signature of the next bootloader in the sequence using a certificate chain that has its root-of-trust resident in hardware. The boot process is terminated if verification fails at any step. Secure Boot is effective in preventing unauthorized bootloaders (and sometimes the kernel when it is also applied to the kernel binary). However, Secure Boot is unable to distinguish between different versions of authorized binaries, for example, a bootloader with a known vulnerability versus a later patched version, since both versions have valid signatures. Samsung KNOX implements Trusted Boot (in addition to Secure Boot) to address this limitation. With Trusted Boot, measurements of the bootloaders are recorded in secure memory during the boot process. At runtime, TrustZone applications use these measurements to make security-critical decisions, such as verifying the release of cryptographic keys from the TIMA KeyStore, container activation, and so on.

94 Additionally, if the final bootloader is unable to verify the Android kernel, a one-time programmable memory area (colloquially called a fuse) is written to indicate suspected tampering. Even if the Android kernel is restored to its original factory state, this evidence of tampering remains. However, the boot process is not halted, and the final bootloader continues to boot the Android kernel. This process ensures that normal operation of the device is not affected. TRUSTZONE-BASED INTEGRITY MEASUREMENT ARCHITECTURE The system protection offered by SE for Android relies on the assumption of Operating System (OS) kernel integrity. If the kernel itself is compromised (by a perhaps as yet unknown future vulnerability) SE for Android security mechanisms could potentially be disabled and rendered ineffective. Samsung’s TrustZone-based Integrity Measurement Architecture (TIMA) was developed to close this vulnerability. TIMA leverages hardware features, specifically TrustZone, to ensure that it cannot be preempted or disabled by malicious software. TIMA PERIODIC KERNEL MEASUREMENT (PKM) TIMA PKM performs continuous periodic monitoring of the kernel to detect if legitimate kernel code and data have been modified by malicious software. In addition, TIMA also monitors key SE for Android data structures in OS kernel memory to detect malicious attacks that corrupt them and potentially disable SE for Android. REAL-TIME KERNEL PROTECTION (RKP) RKP performs ongoing, strategically-placed real-time monitoring of the operating system to prevent tampering with the kernel. RKP intercepts critical kernel events, which are then inspected in TrustZone. If an event is determined to have impact on the integrity of the OS kernel, RKP either stops the event, or logs an alert that tampering is suspected. This alert information is included in remote attestation results sent to the MDM for IT Admins to determine any further actions required by the enterprises security policies. This protects against malicious modifications and injections to kernel code, including those that coerce the kernel into corrupting its own data. RKP checks are performed in an isolated environment that is inaccessible to the kernel, so potential kernel exploitations cannot be extended to compromise RKP. Depending on the device model, this isolated environment can be in the TrustZone Secure World or the hypervisor extensions. REMOTE ATTESTATION Remote Attestation (sometimes simply called attestation) is based on Trusted Boot and used to verify the integrity of the platform. Remote attestation can be requested on-demand by the enterprise's Mobile Device Management (MDM) system, typically before creating the KNOX Workspace.

95 When requested, attestation reads the Trusted Boot collected measurement data and returns them to the attestation requestor. To simplify the handling in MDM servers, the attestation agent on the device produces a verdict indicating the overall status of attestation. It compares these measurements to the factory values inside the TrustZone Secure World. Trusted Boot measurement data includes a hardware fuse value that indicates if the device booted into an unauthorized kernel in the past. Trusted Boot measurement data, along with the SE for Android enforcement setting, forms the basis of the produced attestation verdict. This verdict, essentially a coarse indication that tampering is suspected, is returned to the requesting MDM. In addition to the verdict, the attestation data includes all the trusted boot measurements, RKP and PKM logs that can indicate the presence of malicious software in the device, and other device information that can be used to bind the attestation result to the device.

96 APPENDIX H ALL BEIS FUNDED “FEASIBILITY” PHASE PROJECTS:

No. Lead Partners Project Title Brief Project Description Company

D101 geo - Upside Energy Core4Grid Managed by geo, a rapidly growing tech business Green Ltd, National focused on the digitisation of consumer energy, Energy Energy Core4Grid will advance geo’s home energy management Options Foundation, system (Core) by embedding an automatic external grid Ltd UK Power signal response module, thus enabling domestic DSR for Networks affordable new homes.

D102 Upside EDFE, Procure TRADDAS: The TRADDAS project will explore options to trade Energy Plus, GMCA, Trading domestic DSR on energy markets, similarly to the way Ltd Salford Domestic commercial generation is currently traded. This opens a University Demand at much deeper market for domestic DSR, and thus the Scale ability to deploy it at scale.

D103 Energy NFPAS, The Flexibility The project enables communities to offer demand Local CIC Megni through flexibility and to be rewarded for participation. Key Parnership communities elements are already in place in a pilot community of 100 households. This includes: half-hourly settlement metering, time-of-use tariff, personalised web pages to help users match their demand to local generation or lowest tariff, back-office calculation of tariff and savings from local renewable power.

D105 Clean N/A Demand This project is testing the application of demand response Energy response technology and a new local supply business model to Prospecto within strategically control heat pumps and thermal storage r community across all homes on a single substation. heat+power microgrids

D108 Energy Choice Identification of There is a great untapped potential from DSR in the Trading Housing low cost, domestic market, however the volume and installation Ireland Association, reliable and costs required to provide reliable DSR capacity has Ltd Energy commercially meant aggregators have avoided this particular section of Systems viable the market, in favour of the larger industrial loads. By the Catapult, technology to end of the project, ETI will have developed a cost CSIT, PRR enable effective, controllable, site installation which will integrate Associates Ltd aggregated with and aggregate in SCADA system. The signals will be control and available to the DNO to provide control of diversity and or trading of network constraint management. domestic DSR

D109 Evergree SPECIFIC, Integrated and Evergreen Smart Power, Myenergi, Snowdrop Energy, n Smart Myenergi, co-ordinated SPECIFIC IKC and the Energy Systems Catapult propose Power Energy DSR control of to evaluate the potential to control domestic loads such Systems electricity as immersion heaters, heat pumps and EV chargers in an Catapult, hungry devices aggregated fashion such that they can address electricity Snowdrop and appliances generation fluctuations. Energy in the home.

D111 SmartKlu Smart The Smart “The Smart Prosumer” is a two phase project that will b Ltd Innovations Prosumer demonstrate how Demand Side Response works best by Grid Ltd, performing it at community level with community University of engagement. We will take two existing communities and

97 Nottingham, work with them to get the best financial results for them Limejump Ltd and the energy industry.

D113 Powervau Sustainable Whole house This project will undertake a Phase 1 feasibility study to lt Ltd Ventures energy establish the customer and commercial drivers for management adoption of domestic DSR, drawing on the energy for DSR consumption profiles of Powervault’s existing customer base. Phase 1 will also assess the macro-UK domestic DSR opportunity and draw conclusions on the appropriate business models.

D117 Energise Oxford DSR for homes This project aims to use the thermal stores installed in the Barnsley Brookes with air source homes with the air source heat pumps’ to shift the peak University, heat pumps in demand of the homes away from peak national electricity Sonnen, Barnsley demand, and to further flatten the profile spikes of Upside electricity demand from these houses, whilst incentivizing Energy, the tenants to react to a price based demand side response through the installation of a smart battery.

D118 Sunamp OVO Energy Micro- To develop a novel micro aggregator architecture that has Ltd Ltd Aggregator for easy deployment characteristics and can be built into Flexibility on every DER device at very low cost. To do this it leverages Thermal the “app” paradigm (one easy-to-develop app per DSR Energy Stores type) running on “SunampOS”, an extended Linux (or (MAFTES) possibly Android), within a sub-£5 Raspberry Pi Zero (separate from the DER’s own controller facilitating safety and security).

D119 Sero BRE Ltd, FLATLINE The project will deliver typical domestic energy Energy Minus7 Ltd, (Fixed Level consumers with set price heat and power fuel bills through Ltd sonnen GmbH Affordable an innovative integration and management structure Tariffs Led by between the collaborators’ systems. Stable Intelligently monthly bills will be possible by using a combination of Networked domestic Demand Side Response and demand shifting Energy) (for both heat and electricity) across networked districts of homes, operating to control domestic appliances, heating, photovoltaic generations and battery storage in combination.

D122 Boxergy Energy Boxergy Phase Boxergy is a start-up company inspired by the need to Systems 1 decarbonise domestic heating and make it more Catapult affordable for all. Our systems combine highly efficient electric heating with energy storage. They perform better than gas boilers, cost less to run and allow our customers to reduce their carbon footprint without compromising their comfort. Our business model means those in fuel poverty are just as able to access our services as anyone else.

D124 Levelise Baxi Heating Ubiquitous The Ubiquitous Storage Empowering Response (USER) Ltd UK Limited, Storage project will seek to widespread the prosumer role in the Ecuity Empowering domestic sector by means of AI-led hot water tanks. Consulting LLP Response Currently, there are 9 million hot water tanks, which if (USER) appropriately managed, represent realising a 27 GW demand response latent opportunity.

98 D125 PassivSy Energy No Regrets The No Regrets Renewable Responsive Heating Project stems Systems Renewable brings together PassivSystems, EDF Energy, Newcastle Catapult Responsive City Council and Energy Systems Catapult in a project Heating that seeks to test if new hybrid heating consumer Project propositions that incorporate value from DSR can find a viable high volume route to market.

D126 Electric Voltalis, Our Power of Power of HOMEs, a joint project between Voltalis Heating Power, Delta Home (European leader of residential Company EE Optimisation & demand-side management), Our Power (energy retailer), Management Electric Heat Company (manufacturer of electrical of Energy heating) and DeltaEE (consulting company), with (HOMEs) ambitions to show how domestic properties can deliver demand-side services capacities and contribute to energy efficiency and cost optimization for consumers.

D127 Gengame GridDuck, Nudge Nudge, GenGame, GridDuck, EnAppSys, Ecotricity Newcastle Ltd EnAppSys, Switch Switch - and Teesside Universities propose to evaluate the Newcastle Using potential for a holistic approach to domestic demand-side University, Gamification response. We will investigate whether state-of-the-art Teesside and techniques in digital marketing, consumer mobile University, Behavioural application development, big data analysis, IoT Ecotricty Economics to technology, behavioural science and gamification can be deliver combined to deliver a massively scalable and repeatable domestic DSR approach to deliver cost-effective DSR in the UK.

D131 Greater UKPN, Moixa, Home Home Response is led by the Greater London Authority London RE:Powering Response (GLA) and inspired by its project partners. This project Authority has identified a specific set of London properties that are suitable for trials of new energy demand side management. The project aims to make use of a range of existing innovative technologies and services that are deployed in households, such as battery storage, and configure them in new ways to unlock the Demand Side Response (DSR) potential. Doing so will cut bills, reduce energy demand and reward domestic energy users for their flexibility.

D132 CityWest Thames Heat Application of It has been estimated that immersion heaters in UK Homes & Power Demand Side homes have a total connected Ltd Response to load of 20GW and are installed in domestic hot water Domestic Hot (DHW) tanks offering an aggregated energy storage of Water Supplies 55GWh. On this scale domestic immersion heaters clearly offer an important opportunity for Demand Side Response (DSR).

D133 Carbon Community Developing an A partnership led by Carbon Co-op and Community Co-op Energy open and Energy Scotland (CES) will deliver ‘Open DSR’ a project Scotland, EV standards assessing the feasibility and demonstrating the real-world Parts Ltd, based potential for an open source, standards-based approach Megni approach to to demand side response (DSR) management services. DSR

D135 Mixergy N/A DDSR-HW A consortium covering an electricity utility, an aggregator Ltd and a technology provider are collaborating to refine their

99 market leading demand side response (DSR) smart home experience in 100 DSR enabled households. The key component within this system is Mixergy’s (technology provider/device aggregator) proprietary intelligent hot water tank, based on leading innovations from the University of Oxford. This grant will enable these parties to optimise its proposition to domestic users, specifically regarding, 1. smart home interoperability (a key element for household iteration with domestic DSR) and 2. the commercial proposition to households and other electricity market stakeholders.