Economic Performance of a Liquid-Based Solar Photovoltaic/Thermal (PVT) System Over Large Geographical Cities Around the World

Master Level Thesis European Solar Engineering School No. 264, June 2020

Digital Mapping of Techno- Economic Performance of a Liquid-Based Solar Photovoltaic/Thermal (PVT) System over Large Geographical Cities Around the World

Master thesis 15 credits, 2020 Solar Energy Engineering Author: Santhan Reddy Penaka Supervisors: Puneet Kumar Saini Xingxing Zhang Dalarna University

Examiner: Solar Energy Ewa Wäckelgård Engineering Course Code: EG3022 Examination date: 2020-06-17

i Abstract

Photovoltaic thermal (PVT) collectors are widely used to harness a large fraction of the solar spectrum to generate electricity and heat from a single collector. The circulation of the working medium will pass through the collector which cools down the PV cell temperature and also increases the water temperature, which will increase the electrical and thermal performance at the same time. PVT is an emerging technology and is demonstrated for domestic and industrial applications. There has also been a major gap for the techno- economic analysis of PVT system in different climatic conditions and further developing reliable financial models that can be applied in different regions. This thesis paper presents a techno-economic evaluation of a liquid-based PVT collector system developed by Abora Solar, Spain across a wide range of climatic conditions and contexts. The various performance indicators are visualized by digital mapping approach for 86 different locations all over the world. The databank obtained from the analysis is further used to establish a general correlation between collector performance and meteorological parameters such as Global horizontal irradiation and ambient temperature. The collector energetic performance is simulated using a validated and proprietary simulation tool developed by Abora Solar company. The complete energy system consists of a PVT collector, a water storage tank, and the associated DHW demand simulator. The collector energetic performance has reflected following the analysed Global horizontal irradiation and ambient temperature trend. The highest and lowest energy utilization ratio of the collector has been recorded in Reykjavik, Iceland (63%) and Medina, Saudi Arabia (54%) respectively. The highest and lowest exergetic efficiency of the collector has been recorded in Reykjavik, Iceland (23%) and Medina, Saudi Arabia (17%) respectively. The exergetic efficiency collector has shown better performance with the less ambient temperature and less quality of work in high ambient temperatures. Furthermore, the energy utilization ratio and exergetic efficiencies of collector production are analysed. The economic analysis is carried out in realistic approach using two different financial scenarios: mode (1) The total system cost is capital investment in the first year; mode (2) Only 25 % of total system cost is a capital investment and remaining 75 % investment is considered with financing period with certain interest rate. The economic performance of the collector has been decided mainly based on the Net Present Value per unit collector area, whereas it expressed high dependency on thermal energy savings. The average NPV per unit collector area of 86 geographical cities for first financial model 1 and financial model 2 are 1886€ and 2221€ respectively. Besides, the Payback Period has also been estimated for the first financing model in all selected locations. The first financial model (1) has shown better results in locations with a high interest rate and highly recommended for the locations with interest rate. The significant work of understanding of PVT components behaviour at the system level, the collector energetic and economic performance at different climatic conditions across the world have been highlighted which reflects the concrete developments to this research subject area and helps market decision-makers for market penetration.

Keywords: PVT, Liquid-based, Techno-economic analysis, Digital mapping, Large geographical cities

ii Acknowledgement

It has been my pleasure to contribute to the Dalarna University-Abora Solar collaboration. I would like to begin this acknowledgement by thanking Solar Energy Research Centre (SERC)-Dalarna University for offering me a motivating platform with technical expertise, database to carry out my research.

I would like to thank my Supervisors Mr Puneet Kumar Saini, Dr Xingxing Zhang for continuous support and encouragement during research. My special thanks to Dr Alejandro del Amo, CEO of Abora Solar, Spain for giving access to their valuable database mainly solar PVT collector and Abora simulation tool, and valuable feedback until the end of this research.

I would also like to convey my wishes to my family and friends for being my personal support, I believe that this research would not have been completed in time without them.

iii Contents

1 Introduction ...... 1 2 Aims and objectives ...... 2 3 Methodology ...... 3 4 Previous work ...... 5 Solar PVT collectors 5 Abora liquid-based hybrid PVT collector 6 Techno-economic analysis of PVT systems 8 5 Abora Hybrid Solar simulation tool ...... 9 Location and detailed demand analysis 9 System modelling and configuration 10 Output results from tool 10 System pricing and Optimization 11 6 Results and Discussion ...... 14 Boundary conditions 14 Energy performance evaluation of PV/T panel 15 6.2.1. Collector thermal and electrical production 15 6.2.2. Collector energy utilization ratio 19 6.2.3. Collector exergetic efficiency 21 Economic performance evaluation of PVT collector 22 6.3.1. Collector economic performance in Financing model 1 23 6.3.2. Collector economic performance in Financing model 2 25 Uncertainty analysis 27 7 Conclusions ...... 29

iv 1 Introduction In today’s world, global warming is being a severe hazard to the human beings and other living creatures because of polluting emissions exposed by fossil fuels in order to meet the significantly increasing energy demand which is leading to the destruction of the ecosystem and economic growth in many regions. Solar energy is one of the reliable sources in renewable energy sources which is an adequate solution and alternative to fossil fuels[1]. However, there is an urgency to take required measures to control global warming which is helping solar energy to grow rapidly mainly solar photovoltaic(PV) technology[2]. PV technology will generate DC electricity using sunlight where it’s been an interesting subject area for many researchers, global leaders, manufacturers because of its reliability, sustainability, easy installation and economic feasibility[3]. Due to these facts, solar markets are being shifted to solar photovoltaic technology whereas solar thermal technology is beneficial in terms of efficiency and storage. There is huge potential for properly designed systems by combining both solar photovoltaics and thermal technologies. An innovative hybrid solar technology which can achieve the electrical and thermal energy demands together has been emerging in recent years is known as solar photovoltaic/thermal(PVT) technology[4]. International Energy Agency (IEA) has initiated a task 60 part of Solar Heating and Cooling Programme (SHC) named as ‘PVT Systems: Application of PVT Collectors and New Solutions in HVAC Systems’. The target of the task is to discover current existing PVT solutions and encourage the developments of new PVT solutions whereas it intends to improve safety, reliability, economic feasibility and energy yield of PVT systems[5].

From a technical point of view, PVT technology has been well developed and it can be coupled with various energy systems. However, according to the IEA SHC task 60, the main barriers currently in PVT development and deployment are international standards, uncertain financial rules and business models across different regions in such a niche market for PVT technology. Therefore, the potential of PVT solution is not explored although it can be a breakthrough for the current heating industry markets such as Building Integrated PV and Façade Integrated PV in all type buildings and also go hand-in-hand with the emerging awareness of heat pump technology with also borehole storage[6].

There are several studies concerning the techno-economic analysis of PVT collectors with a focus on the component and system design[4], [7]–[10]. However, most of the studies are focused on one particular climate and with the simple economic analysis. Furthermore, complicated procedures or expensive software are used to estimate the performance of PVT collectors, where it lacks a comprehensive simulation of PVT’s techno-economic performance through a common tool over a large geographic area, aiming for application feasibility and potentials.

1 2 Aims and objectives This study aims at simulation and mapping of the energetic and economic indicators of a typical liquid-based PVT system over different regions, in order to establish a digital performance database for various key performance indicators (KPI). The economic feasibility of the PVT collector is obtained using financial models based on capital investment and energy performance basis. The data obtained from simulations are used to establish a simple correlation between several performance indicators of the PVT system.

The main objectives of this paper are to: (1) Assess the thermal and electrical performance of a typical PVT system [6] in 86 large geographical cities using a verified simulation tool; (2) measure the economic performance (i.e. NPV, payback) of the PVT system using two financial models; (3) analyse and digital mapping of the energetic/economic results.

The significance of this paper lies in (1) understanding of typical PVT components behaviour at system level, (2) mapping of the collector energetic and economic performance at different climatic conditions across the world. This research results would reflect the concrete developments to this subject area and helps promotion of the potential markets, e.g. discovering economic feasibility of PVT system around the world, and feasible financial solutions to PVT system in different regions.

2 3 Methodology The simulation is carried using a validated tool developed by the manufacturer to map the performance across 86 large geographical cities shown in Figure 1. The locations were chosen based on large geographical cities in different countries around the world. The locations have also been restricted due to the availability of weather and GHI data in the simulation tool. The inputs to the simulation tool contain location and weather resources, electrical and thermal demands, local energy tariffs, specific volume, PVT panel and installation parameters, interest rate, and financing period etc. The interface of the simulation tool is shown in Figure 2, which has been validated by TRNSYS and real measurement in previous studies[11], [12].

Figure 1 The simulated 86 large geographical cities across the world

Figure 2 Interface of Abora PVT simulation tool The parametric study of components at system operation level and system configurations has been conducted according to the operation flow of Abora solar simulation tool in the flow chart shown in Figure 3.

Figure 3 Operation flow of Abora solar simulation tool The expected results are monthly electrical and thermal performances, energy savings, economic parameters such as NPV, payback period are determined for each location. This paper also considered the economic performance of the collector in two different financial models • Model 1: The total system cost is invested in the first year, • Model 2: Only 25 % of total system cost is a capital investment and remaining 75 % investment is considered with financing period with certain interest rate. The economic analysis results highlight the economic parameters such as NPV and payback period per unit collector area for all the locations. Furthermore, the uncertainty and sensitivity parameters are discussed and the strategy in decision-making for investing in PVT technology is recommended. Digital mapping method is applied to compile and format the techno-economic performance data into a virtual image, which is to produce a general map with KPIs of such PVT collector that gives appropriate representations of the dedicated areas.

4 4 Previous work This chapter consists of previous relevant work that has been done related to this paper study.

Solar PVT collectors The combination of solar thermal and photovoltaic technologies into one system is called photovoltaic/thermal hybrid system (PVT) which generate solar electricity and solar heat together at the same time. Apparently, the conventional PV panels have been able to only harvest approximately 16% of the solar irradiance spectrum and the remaining 74% of irradiance is getting dumped as heat losses as shown in Figure 4. The idea of integrating both PV and thermal technologies is to reduce the PV cell temperature and increase the overall efficiency of the collector, so that the dumped heat can be utilized for the thermal conversion.

Figure 4 Motivation for solar PVT technology The main types of PVT collector that have been explored, 1) Liquid-based PVT collector: which generates electricity hot water together as water circulates inside the collector which will gain heat. Furthermore, liquid-based PVT collector has been divided into covered and uncovered collector, whereas covered type will consist of extra glass layer which has been developed to reduce the ambient heat losses, 2) Air-based PVT collector: this generates electricity and space heating, here air will be circulating inside the collecting instead of water, 3) Concentrating PVT collector(c-PVT): this is used for reaching high desired temperatures[13]. However, these different collectors types have also been segmented based on the type of application with appropriate desired temperatures as shown in Figure 5.

Figure 5 PVT collector types division based on the type of application and ambient temperatures

It is widely used for the applications where the land availability is a challenge as this collector production is significantly higher per unit collector area compared with the major technologies. This technology can be applied for all type of buildings such as domestic and commercial sectors, which has high thermal and electricity demands. According to ‘IEA SHC Task 60 PVT systems’ survey on Solar Heat Worldwide 2019[14], this market has been strongly emerging in mainly European countries with an installed capacity of PVT collector area 675,427 m2 followed by Asia excluding China area 281,104 m2 and China with area 133,942 m2. The distributed global installed collector area worldwide that was recorded by the survey is shown in Figure 6.

Figure 6 Global installed PVT collector area by region[14]

Abora liquid-based hybrid PVT collector Among different types of PVT technology and several possibilities of system integration researchers were mainly focused on hybrid PVT liquid integration from the late 1980s [15]. The PVT liquid collector structured similar to the typical flat-plate collector as shown in Figure 7 and it is being popular because of high overall efficiency, reliable design and easy to build. The efficiency of collector increases when the pumped cooled water flows across the rigid series or parallel tubes under PV cells connected in series or parallel, and thus is an important factor to assess the performance of the PVT collector[16]. In addition to efficiency, hot water is produced with PV heat and absorber which can be used for several applications or keep circulating in the tubes to get extra heat. The electrical and thermal efficiencies of PVT liquid generally depends on PV type, water temperature, flow rate, water flow channel size and configuration, and ambient climatic condition and the performance can be measured in terms of energy utilization ratio and exergy efficiency[17]. 6

This thesis will focus on the liquid-based PVT collector developed by a Spanish company Abora solar shown in Figure 7. This PVT collector is a covered PVT collector which means that it will have an extra layer of glass on the top of the collector in order to reduce the heat convection losses. The rated power of the collector is 365 W at STC with a collector area of 1.96 m2 consisting of 72 mono-crystalline cells. The main specifications and characteristics of Abora PVT collector are shown in Table 1.

Figure 7: Abora Solar PVT panel (Abora AH72 SK)[18] (with permission from Abora solar company)

Table 1 Abora PVT collector specifications and characteristics Parameter Description Length * width * thickness 1970 * 995 * (85+22) mm Total area 1.96 m2 Number of cells 72 Cell type Mono-crystalline Rated power 365 W Combined efficiency (Electrical + 87% (70+17) Thermal) at STC conditions Temperature coefficient of Pmpp -0.41% /˚C Optical performance 0.7 Coefficient of thermal losses, a1 5.98 W/m2 .K Coefficient of thermal losses, a2 0.00 W/m2.K2 Internal liquid capacity 1.78 Litres

7 Techno-economic analysis of PVT systems More researchers are focusing on the techno-economic analysis of hybrid PVT types due to its eminent features and the most common way of doing is to assess the energy performance first and then economic evaluation based on dependent variables[4], [7], [8], [10], [19]–[22]. For instance, Fudholi et al.[19] has researched determining electrical and thermal performances on PVT water-based collector by testing PV and thermal efficiency individually and together with specific inputs parameters 500-800W/m2 solar irradiance and mass flow rate 0.011 kg/s to 0.041 kg/s. The test has recognized that absorber performed more at a mass flow rate of 0.041 kg/s and under 800 W/m2 irradiance whereas PV efficiency of 13.8%, the thermal efficiency of 54.6% and hybrid PVT collector efficiency of 68.4%[19].

Gu et al.[4] developed an analytical model on basis of combinations of Monte Carlo method to analyse techno-economic performances of solar PVT concentrator for building an application in Sweden which considered several essential input uncertainties whereas economic variables were assessed initially. The obtained results for a capital cost of 4482- 5378 SEK/m2 and system size of 10.37 m2 during the lifespan of 25 years are LCOE of 1.27 SEK/kW h, NPV of 18,812.55 SEK and payback 10 years. It concluded that the most important sensitivity factor is average daily solar radiation followed by debt to equity ratio, capital price, regional heating price, and discount rate.

Herrando et al.[23] determined energy performance of hybrid PVT systems for electricity and DHW demand for a typical house in London using techno-economic analysis whereas it’s concluded that with such system 51% of electricity demand and 36% of Domestic Hot Water (DHW) demand is covered in low solar GHI and ambient temperatures. In the economic aspect, it’s also concluded that hybrid PVT technology has a huge scope of competing with PV systems except that the fact of high cost if the national energy policy is committed towards CO2 emissions reduction.

Riggs et al.[8] developed a combined LCOE techno-economic model for different types of hybrid PVT technology which helps to develop feasible option in solar market alternative to competing for low-cost natural gas for process heat application in the United States. The sensitivity analysis of parameters affecting the levelized cost of heat generation(LCOH) was determined using technical, financial and site-specific variables.

Ahn et al.[24] studied the importance of energy demands, solar energy resources and economic performances of hybrid PVT systems at different PV penetration levels using Monte Carlo method whereas the study found significant understanding such as, irrespective of PV penetration levels the uncertainties in energy demands and solar irradiance influencing the energy performance of PVT systems.

Heck et al.[25] conducted Monte Carlo method for LCOE probability distributions as the approach determined that this method provides more realistic information on risk, uncertainty and gives more scope of potential investments on electricity generation however this method is complex slightly than using point values.

8 5 Abora Hybrid Solar simulation tool This section will elaborate on the Abora Hybrid Solar simulation tool and will also highlight the main internal calculations of the simulation tool. This simulation tool is developed by Abora solar company[26] to evaluate the energy performance of solar PVT systems for the company products such as solar hybrid PVT panel (Abora AH72 SK) at several locations.

Location and detailed demand analysis The Abora simulation tool considers uses the databases like Meteonorm to determine the values such as solar radiation, ambient temperatures, altitude, latitude and also supply water temperatures for specific location etc. as shown in Figure 8, which are needed for designing the system. The thermal and electrical demands with different categories of applications i.e. single and multifamily house, tertiary building such as hospitals, hotels and gyms etc., specific key parameters like type of demand, current auxiliary source of electricity and DHW/ heating/ swimming pool in the location of the system installation. Further, the tool will assess the total monthly and annual total demand. The monthly energy load (L) needed to raise the temperature of supply water to the desired hot water temperature is calculated using the Equation 1 whereas the ‘m’ indicates the amount of hot water required per person in a day, ‘Cp’ is the specific heat capacity, ‘N’ is several days in a month, ‘Td’ is desired water temperature and ‘Ts’ supply water temperature.

퐿 = 푚 ∗ 퐶푝 ∗ 푁 ∗ (푇푑 − 푇푠) Equation 1

The monthly demand can also be customized based on consumer utilization in that specific month. For a single-family house, the amount of Domestic Hot Water (DHW) for one person in a day is automatically considered 28 litres/person/day. But in tertiary building, it considers a different consumption depending on specific building as it can be industrial and commercial applications.

Figure 8 Location and weather data in the Abora Simulation tool This simulation tool offers to choose an auxiliary heating system from several thermal auxiliary systems with individual pricing of conventional heating and electric energy sources. However, it also accommodates that the total collector electricity generation can be utilized for self-consumption or if there is excess electrical energy, it can be sold to the conventional electricity grid.

9 System modelling and configuration This simulation tool is designed for the calculation of the hybrid solar collectors which produces thermal and electrical energy. It consists of several PVT collectors which are developed by the Abora Solar and appropriate date such as optimal performance, total collector area, aperture area etc., will be defined as shown in Figure 9. Further, it recommends the number of collectors that would be optimistic to cover the total demand and the storage tank capacity can be customized according to the appropriate specific volume capacity (v/a ratio).

Figure 9 System modelling and configuration in the Abora simulation tool This simulation tool allows to include the shading losses manually and default 20% albedo effect is automatically considered. For the applications where the electrical demand is significantly higher than thermal demand, the PVT collectors can be sized based on the total thermal demand and the extra electrical demand that can’t be covered by the PVT collectors, this tool gives an option that it can be covered by including additional Photovoltaic(PV) panels.

Output results from the tool This simulation tool also optimizes the collector and installation parameters based on the demand, availability and location conditions based for a particular location. After that, it simulates the system and generates the results specifically highlighting essential parameters GHI, radiation on a tilted surface, thermal demand, thermal production, thermal solar coverage, electrical production, total electric and thermal savings, environmental impact calculations shown in Figure 10.

GHI is extracted from the weather database Meteonorm and radiation on the tilted surface will be calculated using the standard calculation equations i.e. the sum of direct radiation on the tilted surface and diffused radiation on the tilted surface.

Figure 10 Results analysis summary of Abora simulation tool

The maximum power point Pm that is generated by the photovoltaic cell is obtained by using Equation 2 for the falling global irradiance value on the surface of the module G, ambient temperature Ta, cell temperature Tc, nominal power of photovoltaic collector Pn, GSTC is irradiance under STC conditions i.e. 1000 W/m2, the temperature variation coefficient of power (훾),

퐺 Equation 2 푃푚 = 푃푛 ∗ (1 − 훾(푇푐 − 25)) 퐺푆푇퐶

Thermal solar coverage is calculated using Equation 3 in this simulation tool,

푇표푡푎푙 푐표푙푙푒푐푡표푟 푡ℎ푒푟푚푎푙 푝푟표푑푢푐푡𝑖표푛 Equation 3 푇ℎ푒푟푚푎푙 푠표푙푎푟 푐표푣푒푟푎𝑔푒 = × 100 푇표푡푎푙 푡ℎ푒푟푚푎푙 푑푒푚푎푛푑

System pricing and optimization After technical results summary, the detailed system cost of the PVT system will be defined by customizing each component such type flat or tilted mounting structure, single-phase or three-phase inverter, material marginal rate, electrical and combustible price escalation rate, annual maintenance cost etc., shown in Figure 11.

Figure 11 Cost optimization of PVT system in Abora simulation tool The simulation will consider the appropriate dynamic inputs and generate the report of assessment on the key economic performance indicators i.e. lifetime cash flow with appropriate total annual savings, Net Present Value(NPV), payback period, Internal Rate of Return(IRR) etc., shown in Figure 12.

Figure 12 Key economic performance indicators sample in Abora simulation tool

Abora simulation tool allows collector economic performance with several financing options shown in Figure 13 such as 1. The total system cost is invested in the first year as a capital investment. 2. The 100% of total system cost can be invested in several years with monthly payment at the certain open and fixed interest rate. 3. The 75% of total system cost can be invested in several years with monthly payment at the certain open and fixed interest rate and remaining 25% of total system cost is to be invested initially as capital investment.

Figure 13 Several financing options in Abora simulation tool This simulation tool also flexible in customizing the several real-time scenarios i.e. the number of payments in a single year, the total number of payments in entire financing period, the early cancellation interest rate can be applied when the system is to dismantle the system during financing period.

13 6 Results and Discussion This section pre-determines the boundary conditions for the simulation mechanism as shown in Table 2, then simulated results are analysed and discussed using digital visualization graphs and figures.

Table 2 Boundary conditions for Abora simulation tool Parameter Description Type of application Single-family house Thermal demand: Domestic hot water (DHW), Type of demand Electrical demand: 100% self-consumption Auxiliary system Electricity grid Auxiliary system energy price This has been selected for the appropriate location No. of people 5 people DHW temperature 60 Collector model aH72SK No. of collectors 1 Specific volume capacity 80 These were selected optimally for appropriate locations Inclination based on higher energy production. Tilted metallic structure for locations in the northern Type of mounting structure hemisphere, flat metallic structure for locations in the southern hemisphere Type of inverter Single-phase inverter Assumed that no maintenance is required for one Annual maintenance cost collector Electricity and combustible 6% is assumed for all the locations price increment System lifetime 25 years Interest rate This has been selected for the appropriate location

Boundary conditions First, the energy performance of Abora PVT collector has been performed in 86 different locations all over the world using Abora simulation tool. The locations were chosen based on large geographical cities in different countries. The locations have also been restricted due to the availability of weather and Global Horizontal Irradiation (GHI) data of Abora simulation tool.

As this project aims to evaluate the single collector performance consisting of 1.96 m2 collector area, the single-family house application with 5 people is considered whereas the load profile has been maintained very high in such a way that collector generation will not meet total demand at any point of time. The two type of demands that are being considered, domestic hot water and electrical energy which will be 100% self-consumed. In a thermal system configuration, the auxiliary source for the house is the conventional electricity grid with appropriate energy prices for every location. The generated DHW by the collector will be utilized for household purposes using storage tank connected to the auxiliary system which will deliver demand at the desired temperature of 60C as shown in Figure 14. It has been assumed that all heating loads like space heating are met by the electric heating system. The Abora simulation tool considers that excess collector thermal production i.e. generated thermal energy more than required demand will be dumped so that it will not affect the PV electrical production. For every location, the installed tilt and azimuth angles are taken 14 optimally based on estimated higher collector production. The specific volume capacity (v/a ratio) of the storage tank is increasing with the increase in collector production which is also directly proportional to the total system cost. The challenge has been to assume the optimal specific volume capacity which is also a main variable for the system feasibility, therefore it has been assumed 80 v/a ratio for all the locations which is equivalent to 150 litres of storage tank capacity.

Figure 14 Thermal and Electrical system configurations In electrical system configuration, the generated DC power will be converted to the AC power using an inverter and then it is utilized by household purposes and the remaining will be sent to the conventional electricity grid whereas the excess electricity demand is taken from the grid connection as shown in Figure 14. Since the power rating of the single collector is 365 W which is also the maximum system power rating, a single-phase inverter is chosen. As the tilt angle of PVT collector is key parameter which will also decides the collector production, an optimal tilt angle has been chosen based on higher production for every location, by checking the collector production at different tilt angles for each location.

This paper is also focused on the economic performance of the PVT collector. The total system cost is different for every location as the variables being system components, material margin etc., where it has zero maintenance cost considered. The electricity and auxiliary energy price escalation is assumed 6% per year for all the locations. This paper also considered the economic performance of the collector in two different financial models for 25 years system lifetime. • Model 1: The total system cost is invested in the first year, • Model 2: The total system cost is paid for 7 years with a certain variable interest rate with every location. As the interest rate has been selected appropriately for every location, for countries which has negative interest rate are being considered as zero interest rate.

Energy performance evaluation of PV/T panel Based on the above boundary conditions and assumed parameters, the energy performance has been simulated in 86 different locations using the Abora simulation tool.

6.2.1. Collector thermal and electrical production The simulation has been done for more than one city for many countries, then average thermal and electrical production is calculated in all countries and projected as the whole country thermal production. Figure 15 shows the annual average production of the collector.

Figure 15 Annual average collector thermal performance The thermal production is higher in countries such as Saudi Arabia, Algeria, Morocco, Brazil, Mexico, India etc., with the generation above 1800 kWh due to high GHI and annual ambient temperatures. The highest collector production resulted in Saudi Arabia with 1966 kWh. The least average collector production is performed in Iceland and Norway countries with 932 kWh and 981 kWh respectively, and likely lower production in Sweden, Finland, United Kingdom, Denmark etc., lower than 1000 kWh production. The collector shows better performance in countries such as Spain, Portugal in Europe and Australia with more than 1600 kWh production.

Figure 16 Correlation of collector thermal production with Global Horizontal Irradiation (GHI) and ambient temperature Figure 16 shows the correlation of collector thermal production with GHI and ambient temperature for all the monthly points that have been considered, and it indicates the positive correlation coefficient of 0.5331.

Figure 17 Annual average collector electrical performance Figure 17 represents the annual average electrical performance of the collector. The electrical production shows likely higher in countries such as Saudi Arabia, Algeria, Morocco, Brazil, India etc with the generation above 500 kWh due to high GHI, whereas electrical production is highest in Saudi Arabia with 540 kWh. The electrical production is very less in Iceland with 266 kWh due to less available GHI, And the collector has also performed lower than 300 kWh in locations such as Sweden, Finland, Denmark, Poland, United Kingdom etc., The collector performed slightly better in Spain, Portugal in Europe and Australia with more than 400 kWh annually. However, it shows there is no significant difference in thermal and electrical production trend. Furthermore, a correlation of collector electrical production with GHI and ambient temperature has been developed based on all points from chosen location, as it shows the positive correlation coefficient of 0.552 is realized as shown in Figure 18.

Figure 18 Correlation of collector electrical production with Global Horizontal Irradiation (GHI) and ambient temperature Although few cities in a particular country have more production due to available GHI, it’s not reflected in Figure 15 and Figure 17 because of the overall average is taken for each country. For example, although Las Vegas, United States of America (USA) has collector thermal and electrical potential of 1987 kWh and 545 kWh respectively which is higher than the production in Lisbon, Portugal, still the average thermal and electrical production for the USA remained less than Portugal. It is because the simulations were being done 9 cities in the USA and only 3 cities in Portugal due to large geographical space. However, this type 17 of variation would exist in countries with many simulated cities, the calculation has been done to define the uncertainty for each country in Figure 19.

Figure 19 Country-wise collector thermal performance uncertainty The minimum thermal production representing blue colour is the least production of the city inappropriate countries, maximum thermal production indicated with red colour represents the highest thermal production of a city in each country whereas the average production with green colour indicates the average production of all the cities in the country. The results show likely high uncertainty in Italy, Spain, USA and Australia as many cities were simulated in those countries, less uncertainty recorded in countries Denmark, Iceland, United Kingdom etc., due to less simulated cities. There is no uncertainty in Brazil, China, Chile, Colombia, Algeria, Egypt, Morocco, Luxemburg countries because, the simulation was for a single city.

Figure 20 Collector monthly thermal production variation Solar collector monthly production is an important key factor in the sizing of a solar system to match the monthly variation of energy consumption. Figure 20 and Figure 21 shows the collector thermal and electrical production respectively. The collector production was expected to vary according to the incoming GHI trend, and it has been identified that same trend in actual production. The thermal performance in April and July are relatively higher and less in January and October for the locations in the northern hemisphere such as Madrid,

18 Stockholm and Berlin. In Medina location, although GHI and ambient temperature are higher in July, yet the thermal production in October is likely higher than July. It is because since the thermal demand in July is less than the October, so in July month, due to high GHI and less thermal demand, the storage tank losses will be higher as the tank temperature increases. As the GHI trend in the southern hemisphere is quite opposite to the northern hemisphere, the production in January and October is likely higher than April and July months. In Stockholm location, the variation between the months is significant because of its latitude, and the monthly variation is very small in Medina due to its low latitude.

Figure 21 Collector monthly electrical production variation The electrical performance of collector is higher in July month due to high GHI for the locations in the northern hemisphere such as Madrid, Stockholm, Berlin and Medina, whereas it is likely opposite in southern hemisphere such as Melbourne production is high in January month. In the northern hemisphere, the monthly electrical production variation is higher in locations such as Stockholm with high latitude and less in less latitude locations such as Medina, it is notified that vice-versa in the southern hemisphere. In Medina location, the general trend is that PV collector production will be less in July than October due to high ambient temperatures, whereas PVT collector shows better performance in July. It can be due to a reduction of cell temperature due to circulating fluid inside.

6.2.2. Collector energy utilization ratio The performance of the collector is evaluated using standard key performance indicators as described in IEA SHC Task 60. The performance of a collector over a specified period can be quantified by means of the energy utilization ratio. However, a simple summing up of thermal and electrical energy doesn’t account for the potentially different values of heat and electricity. An option to account for this, with the drawback of being somewhat less intuitive, is to replace “energy” by “exergy”, i.e. to multiply the collector thermal output by Carnot efficiency 휂퐶푎푟푛표푡 which is defined between the inlet and outlet temperature of the collector field shown in the following expression,

푇푖푛 Equation 4 휂퐶푎푟푛표푡 = 1 − 푇표푢푡

Figure 22 Collector energy utilization ratio

Figure 23 Correlation of Energy utilization ratio with the annual average ambient temperature The energy utilization ratio of the collector for various locations is shown in Figure 22. The energy utilization ratio is higher in Davos and lower in Medina. The correlation trends between energy utilization ratio and annual average ambient temperature are also shown in Figure 23. Even though the electrical efficiency of the collector is positively affected by a decrease in ambient temperature, however, it shows an inverse relation with thermal efficiency due to an increase in convection losses at lower temperatures. The results have shown that Medina has high likely less efficient than Davos although Medina has high GHI and annual average ambient temperatures. This unusual difference is because of collector thermal production is directly proportional to the total thermal demand. According to the boundary conditions assumed, the total thermal demand has considered as a single-family house of 5 people in every location.

Figure 24 Total thermal demand of single-family house relation with the average ambient temperature However, it is observed that the total thermal demand for every location has been varying depending on the ambient temperature as shown in Figure 24. It is because of the temperature difference between annual average ambient temperature of each location and desired water temperature (assumed 60°C), that has to be covered by the collector thermal production. Since the total thermal demand of 5 people for a single-family house in Medina is less than the Davos location, so the energy utilization ratio is less in Medina than Davos.

Figure 25 Collector performance in Medina vs Davos with Thermal demand variable From Figure 25, it has been also observed that the collector energy utilization ratio in Medina is less in low thermal demand and higher at high thermal demand, vice-versa in Davos location. During low thermal demand situation, the storage tank convection losses are less in Davos than Medina due to the less circulating fluid temperature that is going through the storage tank and collector, which is why the energy utilization ratio difference between Davos and Medina is high. During high thermal demand situation, the energy utilization ratio difference between Medina and Davos as the storage tank convection losses are high in Medina due to high circulating fluid temperature.

6.2.3. Collector exergetic efficiency From the Carnot efficiency Equation 4, it can be that exergetic efficiency is a function of ambient temperature and thermal output of the collector (assumed that the desired output

21 temperature is fixed at 60°C). So it can be derived that locations with higher ambient temperature will result in less quality of exergy, and thus lower exergetic efficiency.

Figure 26 Correlation of Exergetic efficiency with the annual average ambient temperature This can be expressed correlation with the results provided in Error! Reference source not found. and similar trends can be seen for some specific locations shown in Figure 27. It can be seen that even though the energy efficiency of Madrid is higher compared to the Davos, still the exergy efficiency of the Davos is higher due to lower annual ambient temperature, and thus higher quality of heat delivered to the user.

Figure 27 Collector Exergetic Efficiency However, this paper also realizes the notable uncertainties in energy performance analysis such as the delivery water temperature is assumed 60°C and 28 litres DHW demand per person for all the locations across the world, which may not be the case but it also cannot affect the result significantly. Also, the v/a ratio of the has been assumed as 80% for all the locations but since it may vary depending on the location and type of application, the resulted collector production would be slightly different in real-time but this approach has been assumed to achieve the aims of this paper.

Economic performance evaluation of PVT collector Based on the above boundary conditions and assumed parameters, the economic performance of the collector has been simulated in 86 different locations using the Abora 22 simulation tool. The economic parameters NPV and payback period potential in all the locations across the world. As the actual collector area is 1.96 m2, in this paper NPV is analysed per unit collector area. This paper has also analysed collector economic performance in two different financing models.

6.3.1. Collector economic performance in financing model 1 This financing model scenario has assumed that the total cost of the system is invested in the first year of the system period. As the total system cost will be invested in the first year, no interest rate is not considered. The Figure 28 is the digital representation of NPV potential per unit collector area with financial model 1 in all 86 geographical cities across the world and Figure 29 shows the NPV potential per unit collector area in geographical cities in Europe continent.

Figure 28 NPV potential per unit collector area for financing model 1

Figure 29 NPV potential per unit collector area in Europe for financing model 1 The cities with red colour represent the high NPV potential and cities with blue represents the least NPV potential. The cities Catania and Munich has the highest potential of 5140 €

23 and 5348 € respectively, followed by Bari, Lisbon, Setubal, Sevilla, Valencia, Zaragoza, Madrid and Berlin cities has potentially more than 4500€ per unit collector area. This is due to their high available GHI and electricity grid price, so the energy savings are high in these locations which reflected in huge NPV potential for this system. Although cities such as Oslo, Bergen, Reykjavik etc., with relatively lower electricity grid price, resulted with negative NPV due to less available GHI. The cities with high collector production such as Medina, Algeria, Cairo has shown negative NPV potential due to very less electricity grid price which eventually showed fewer energy savings.

Figure 30 Country-wise NPV potential per unit collector area for financial model 1 The NPV potential in all 86 simulated cities has been selected divided and segmented for the appropriate countries to define the NPV range per unit collector area of each country as shown in Figure 30. The NPV variation in each country is not significant in most of the countries, it is slightly identified in USA, India, Spain, Italy, Germany etc., because of large geographical area comparatively. However, the variation is not identified in few countries which are also geographically larger in size such as China, Argentina, Brazil etc., it is because only one city has been simulated in this paper which is uncertainty.

Figure 31 Country-wise average payback period of Abora PVT collector system Figure 31 shows the payback period of Abora PVT collector system for single-family house of 5 people in several countries. This is only simulated for the financing model 1 where the 24 total system cost is invested in the first year. As the simulation data has been done for the 86 large geographical cities in 34 countries. The results show that the total system cost will be returned in first ten years in countries such as Australia, Belgium, Denmark, Germany, Greece, Italy, Portugal, Spain, Switzerland etc. This is due to high Abora collector production and high conventional electricity grid price. Although countries such as Algeria, Saudi Arabia, Egypt has the highest Abora collector production, they have lower conventional electricity grid price which reflects the payback period of more than 20 years.

6.3.2. Collector economic performance in Financing model 2 This financing model has been analysed by assuming that the 75% of total system cost is paid within financing period of 7 years with certain interest rate and remaining 25% of total system cost is invested in the first year without any interest rate. The interest rate has been considered appropriate for each country. The NPV potential per unit collector area with financing model 2 in 86 geographical cities across the world is shown in Figure 32 and NPV potential per unit collector area in specific Europe continent is shown in Figure 33.

Figure 32 NPV potential per unit collector area for financing model 2

Figure 33 NPV potential per unit collector area in Europe for financing model 2 The cities with red colour represent the high NPV potential and cities with blue represents the least NPV potential. The cities performed high NPV potential in financing model 1 such as Catania and Munich has shown improved NPV of 5140 € and 5348 € respectively because of zero interest rates in those countries, whereas the cities with least NPV potential in financing model 1 such as Oslo and Reykjavik has also shown better NPV due to less interest rates of 1% and 2.5% respectively.

Figure 34 Country-wise NPV potential per unit collector area for financing model 2 Figure 34 shows the NPV potential per unit collector area in each country for the financing model 2. As compared with financing model 1, there is slightly better performance in NPV in most of the countries. Thus, there is not much variation has been identified in this model 2 compared with model 1. It was expected to identify some variation in Argentina due to large geographical area and significantly high interest rate, but due to uncertainty that only single city is chosen from the country, it hasn’t been noticed any interesting finding.

Figure 35 NPV profit increase with financing model 2 In order to conduct detailed analysis on the improved NPV per unit collector area with consideration of financing model 2, a digital world map has been developed to show the difference in NPV between first and second financial models in Figure 35. This has been expected and identified that the countries with high interest rate has shown a negative effect on NPV and countries with less and zero interest rates has shown better NPV potential such as USA, Australia and most of the European countries. However, due to high interest rate of 38% in Argentina, a huge negative impact is identified with this financing model 2. Furthermore, a correlation is derived between NPV variation with an interest rate of a specific location in Figure 36.

Figure 36 Correlation of NPV potential variation with an interest rate

Uncertainty analysis However, this paper also discovered some considerable uncertainties in economic performance analysis of the collector. As the conventional electricity grid price is the key parameter of the total system energy savings which decision-making factor, the auxiliary energy price is taken as the generalized price for every specific country, whereas in real-time case the energy price would be different for every state/city/municipality depending on localized energy policy. It has been considered as because of unavailability of precise data 27 and it may not be significantly higher. The marginal cost of the total system cost is one of the key contributors to economic feasibility. Thus, a realistic material marginal cost has been assumed differently i.e. 30% of the material marginal cost of total system cost for locations in Spain, 35% of total system cost for all European locations other than Spain country locations and all remaining locations outside Europe continent has been chosen as 40% of total system cost, whereas these are considered as realistic percentages but the precise numbers can be different accordingly. Regarding interest rate which has been used for deriving the NPV potential difference between financing model 1 and model 2, for few countries which have negative and zero interest rate has been assumed as 0.1% due to simulation tool unacceptance of negative or null values. However, it has also realized that uncertainty of difference between the negative interest rates and assumed interest rates has not been less than 1% which is not significantly affecting the NPV potential difference. Hence, the assumptions have been considered in order to achieve the aims in possible optimistic and realistic approaches irrespective of the uncertainties.

28 7 Conclusions The Abora collector electrical and thermal performance is dependent on available solar radiation, ambient temperature, source and desired water temperatures, inclination angle for the appropriate location. The inclination has been varying with latitude and altitude of the location. The better energy performance has been increasing with an increase in the total thermal demand and specific volume ratio (v/a ratio). The total thermal demand has also been varying for each location accordingly with the ambient temperature due to the temperature difference between ambient temperature and desired water temperature at the consumer end. In the northern hemisphere, the monthly variation of PVT collector energy performance is higher in locations with less latitude and lower performance in high latitude locations, whereas it is vice-versa in the southern hemisphere. Overall, the correlation of collector thermal and electrical production has been indicated that they are highly dependent on available GHI trend and partly on the ambient temperature. The electrical production by PVT collector has also likely improved in high ambient temperature locations. The highest and lowest energy utilization ratio of the collector has been recorded in Reykjavik, Iceland (63%) and Medina, Saudi Arabia (54%) respectively. The highest and lowest exergetic efficiency of the collector has been recorded in Reykjavik, Iceland (23%) and Medina, Saudi Arabia (17%) respectively. The energy savings is one of the key parameters which decides the economic feasibility compared with the conventional energy source of the consumer as it increases the benefit of the solar system. These energy savings are higher for the countries which have high electricity grid price, GHI and ambient temperature. The average NPV per unit collector area of 86 geographical cities for first financial model 1 and financial model 2 are 1886€ and 2221€ respectively. The payback period of the PVT system is analysed for the financial model 1, as it has been observed that it is directly proportional to the energy savings. The NPV and Payback Period analysis of the PVT system has shown positive results for the cities which have high collector production and high electricity grid price reflecting high energy savings. However, the financing model 1 is highly recommended for the locations with high interest rate and financial model 2 is beneficial for the locations with less interest rate.

29 References:

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