Final Report

DISTRIBUTION SYSTEM CONSTRAINTS AND THEIR IMPACT ON DISTRIBUTED GENERATION

Final Report

CONTRACT NUMBER: DG/DTI/00005/REP

URN NUMBER: 04/1114

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DISTRIBUTION SYSTEM CONSTRAINTS AND THEIR IMPACT ON DISTRIBUTED GENERATION

DG/DTI/00005/REP URN 04/1114

Contractor Halcrow Group Ltd Subcontractors EMS Consulting Limited Seeboard POWER NETWORKS plc IPSA Power Ltd

Prepared by Jim Thornycroft, Andrew Caisley Tim Russell Steve Willis Rida Youssef Richard Bawden, Gavin Holden, Jonathan Williams

The work described in this report was carried out under contract as part of the DTI Technology Programme: New and Renewable Energy, which is managed by Future Energy Solutions. The views and judgements expressed in this report are those of the contractor and do not necessarily reflect those of the DTI or Future Energy Solutions.

Preface

This report has been prepared as a part of the Department of Trade and Industry’s Sustainable Energy Programme, under Agreement No. ETSU/K/EL/00280/00/00 with the DTI. It constitutes the Final report for the project “Distribution System Constraints and their Impact on Distributed Generation ”.

The project is managed by Halcrow Group Ltd with subcontractors EMS Consulting Limited, Seeboard POWER NETWORKS plc. and IPSA Power Ltd. The work for the report was carried out between February 2002 and July 2003.

i EXECUTIVE SUMMARY

This report takes a novel look at constraints due to connection of Distributed Generators to the Distribution network. It concentrates on the connection of many small generators, and looks at how the constraints can be alleviated or accepted.

It considers both the ‘conventional’ solution of reinforcing the network to eliminate constraints due to thermal or voltage conditions, and also an alternative approach of ‘constraining off’ the generators themselves when limits on the existing network are approached. This is a form of ‘active management’ in that connected generators are constrained down when unacceptable network conditions would otherwise arise.

An economic model has been built using Excel spreadsheets, and this accepts data both on electricity pricing scenarios for when a generator is ‘constrained off’, and also the cost of conventional network reinforcement options such as transformer upgrades and cable replacements. It is built to be able to investigate the effect of a number of different electricity price scenarios as well as the effect of different values of ROCs and whether the periods of constraint are predictable far enough in advance to be able to trade out of them relatively cheaply.

A comparison of ‘partial reinforcement’ options is then undertaken to examine the possibility of providing a ‘mixed solution’ of some generator constraints and some capital investment in the network. This is in contrast to the current practice of ‘fit and forget’ upgrades to allow operation with no generator constraints.

To make the modelling process more realistic, a real section of network from the Faversham area within Seeboard has been used with data provided by Seeboard, and this has been modelled by IPSA Power Ltd using the IPSA power system analysis programme. In particular three samples of network were used, one to represent an ‘urban’ environment, one a ‘semi-rural’ environment, and finally one representing a ‘rural’ area.

Generation figures and mix of generator estimates were used from predictions carried out for Seeboard, and also from the South East Regional study, both corrected for local conditions.

Results indicated that:

In general in the examples it was found to be more economic to reinforce the network rather than suffer the loss of income from the generators. This was due in part to the long periods of the year for which the generators would be constrained off in the examples, and also the high price commanded by the generators for output where ROCs were earned.

ii For more marginal cases where network reinforcement was required to avoid constraints for just a few days per year, and/or where the generator was not entitled to ROCs, the conclusion could be reversed. In many cases the cost of network reinforcement is ‘incremental’ such as in going to the next transformer size up.

The income from ROCs was found to be more important than that of ‘free market’ electricity, and this was particularly the case at times of low electricity demand (when electricity prices are lowest), as the ROC value is not dependent on any variable factors. This was exacerbated by the fact that for the cases modelled the constraints were active at the lowest demand periods.

The cost of implementing ‘Active Management’ on the generators has not been factored into the results so far, but these would tend to favour conventional reinforcement further.

The issue of how the cost of network reinforcement and of generator constraints should be split between the interested parties is discussed. Two generic alternatives are suggested, the choice between them depending on the “depth” of connection charging regime being employed.

For a ‘shallow’ connection charge, the most appropriate mechanism for allocation of costs would be for the network operator to pay for times when the generator was ‘constrained’ off’ and recover the cost through levying a ‘use of system’ charge. This would cover the margin over and above the ‘shallow’ reinforcement charge, and the balance of these amounts could be agreed depending on how much compensation the generator wished to be paid if constrained off. It could also pay for the cost of ‘Active Management’ of generators that might be shared between several generator connections.

For deep connection charging regimes it would be more appropriate for the generator to decide on the level of reinforcement and itself bear the cost of not being able to run at times.

Some work was also undertaken investigating the economics of constraining off plant at very low demand times because the generator was unable to provide a frequency response service, and at these minimum demand times there was no space on the system for such plant.

The model, as it has been set-up, is very versatile and could also be used to examine further the balance between reinforcement and accepting constraints to a higher degree.

It is recommended that for example some real life cases involving larger generators connected with some network redundancy are investigated to see where the boundary lies in reinforcement or accepting constraints in cases where the constraint is predicted to last for only a few days or weeks per year.

iii CONTENTS

Preface i

1 Introduction 1 1.1 Background 1 1.2 Aims & Objectives 1 1.3 Content 2 1.4 Generators Modelled 2

2 Constraints 5 2.1 What is a Constraint 5 2.2 Types of Constraint and their Alleviation 5 2.2.1 Thermal, including Phase Unbalance 5 2.2.2 Voltage 6 2.2.3 Fault Level 7 2.2.4 Protection Limitations 7 2.2.5 Flicker and Harmonics 8 2.3 Balance between Reinforcement & Constraint 8

3 Summary of Technical Model 11 3.1 ‘Test’ Network 11 3.2 Generation Scenarios 13 3.2.1 Generation - ‘High’ Case 13 3.2.2 Generation - ‘Medium’ Case 13 3.2.3 Generation – ‘Low’ Case 14 3.3 Reinforcement Scenarios 14 3.3.1 Reinforcement – ‘Low’ Generation 14 3.3.2 Reinforcement - ‘Medium’ Generation 14 3.3.3 Reinforcement - ‘High’ Generation 14 3.3.4 Reinforcement - Costs 15 3.4 Constraint Results 16 3.4.1 Constraints Modelled 16 3.4.2 Constraints - ‘Low’ Generation 16 3.4.3 Constraints - ‘Medium’ Generation 16 3.4.4 Constraints - ‘High’ Generation 17 3.4.5 Summary of Constraints 18 3.4.6 Constraints - Lack of Frequency Response 18

4 Description of Economic Model 21 4.1 Economic Model - Outline 21 4.2 Economic Model - Inputs and Outputs 21 4.2.1 Input Data 21 4.2.2 Output 21 4.3 Economic Model - Description of Inputs 24 4.4 Economic Model - Price Tracks/ Combinations 28

iv 5 Results of Economic Modelling 31 5.1 Outline 31 5.2 Base Case (High Generation, No Reinforcement) 31 5.3 ‘Medium’ Generation – Simulations 33 5.4 ‘High’ Generation – Simulations 35 5.5 Constraints due to Lack of Frequency Response Capability 37

6 Allocation of Costs 41 6.1 Allocation of Reinforcement Costs 41 6.2 Allocation of Constraint Costs 42 6.3 Consistent Cost Allocation models 42

7 Conclusions 45

ANNEX 1 DESCRIPTION OF REFERENCE NETWORK A1 A1.1 Identifying a Network for the Study A2 A1.1.1 Faversham, Kent A2 A1.1.2 Network Characteristics A3 A1.1.3 Voltage Control A4 A1.1.4 Network Requirements – asset condition and load growth A4 A1.1.5 Reinforcement Options – increasing distributed generation A4

A1.2 Current Constraints on Faversham Network A5 A1.2.1 Network Design A5 A1.2.2 Asset Condition and Selection A6 A1.2.3 Network Opportunities through Distributed Generation A6 A1.2.4 Network Risks/ Constraints A7 A1.2.5 Safety A7 A1.2.6 Load Profile A7

ANNEX 2 TECHNICAL MODEL RESULTS A9 A2.1 Summary of Scenarios A10 A2.2 Preliminary Studies A10 A2.3 High Growth Scenario with no Network Reinforcement A11 A2.4 Medium Generation Scenario A11 A2.5 Time Analysis of Medium Generation Scenario A12 A2.6 Results of Medium Scenario with Full Reinforcement A13 A2.7 Time Analysis of High Generation Scenario A13 A2.8 Results of High Scenario with Full Reinforcement A14 A2.9 Time Analysis of High Scenario with ‘LV Cable only’ Reinforcement A15 A2.10 ‘Summary of Constraints’ Table A16 A2.11 Full Constraints Results A17

v ANNEX 3 DISTRIBUTED GENERATION GROWTH SCENARIOS A19 A3.1 South East Regional Study A20 A3.2 Derived Seeboard Figures A20 A3.3 Generation for Faversham Network A22

ANNEX 4 PRICE TRACKS A23

1 INTRODUCTION

1.1 Background

It is now accepted that a result of the desire to reduce carbon dioxide emissions will be a step change in the number of small generating units that will be connected not to the transmission system but to a distribution system. These will comprise both generators powered by renewable “fuels” and combined heat and power (CHP) units using conventional fuels with higher overall energy efficiency than electricity only cycles. The size and type of these distributed generators will have great variation. Some industrial scale CHP installations and large wind farms will have outputs exceeding 100MW. At the other extreme there are anticipated to be many domestic scale CHP or photovoltaic installations with electrical outputs of 1kW or less.

Appropriate methods of managing distributed generation at the two extremes of size will be different, as will some of the issues to be solved. In all cases however the generic question of constraints will arise. The issue is this – new generation may be connected to the network with various levels of security. In general the cheaper the connection work is (including all reinforcement to the network) the lower the level of security will be achieved. The lower the level of security, the more frequently there will be a “constraint” i.e. a limit to what generation (and in principal demand) will be able to operate. There is an optimum balance between levels of initial network investment, at time of connection, and the subsequent costs of having to constrain operation.

Some people use the expression “constraint” in the sense of something that prevents connection of more generation to the network. It has not been used in that sense in this report, as described further in chapter 2. There is no reason why any amount of additional generation need be prevented from connecting to the network on a non-firm basis i.e. anybody can connect. It is being permitted to operate subsequently that is the real issue. We therefore use the term constraints exclusively in the sense of limitations to the operation of connected installations.

1.2 Aims & Objectives

The aim of this project was to develop economic and technical models that could be used to examine the optimum balance between initial investment and subsequent constraint costs under a number of scenarios. This is then applied for these scenarios to a real and representative network so that some general conclusions may be formed.

The cost of network losses is ignored, which clearly would not be the case for a full optimisation. There is also a discussion on the options for allocating the various costs involved in a manner that encourages the optimum outcome.

1 1.3 Content

The report is structured as follows: Chapter 2 is an introduction and description of the causes of constraints on distribution systems and methods that may be used to reduce their severity Chapter 3 provides a summary of the results of the Technical model described fully in Annex 1, 2 & 3: • description of Test network modelled (with Annex 1) • generation Scenarios chosen (with Annex 3) • reinforcement Scenarios (with Annex 2) • constraints results (with Annex 2) It puts a cost on each of the reinforcement options and describes the effect that they would be expected to have on the frequency and severity of constraints to be used in the Economic model Chapter 4 describes the Economic model which was developed especially for this project and the inputs required Chapter 5 contains the results of the Economic model: • it looks at the cost implications of constraints, in terms of possible price tracks (see Annex 4) and how these may impact on the costs depending on how market rules develop • describes the results of the modelling of reinforcement versus constraint costs Chapter 6 looks at cost allocation patterns, how these fall on individual parties, and their effect on efficiency incentives and achieving other desirable outcomes Chapter 7 lists the conclusions and seeks to draw lessons from the modelling work that may have general applicability, as well as suggesting front runners for cost allocation that are most likely to lead to a desirable outcome

Annex 1 describes how the reference network for the Technical model was identified and chosen, and describes the constraints that currently exist Annex 2 includes the full results of the technical modelling: • the effect of a high growth scenario with no network reinforcement and discusses briefly what this would mean for the magnitude and frequency of constraints • investigation of a number of options for reinforcing the network that may be considered appropriate for each scenario, ranging from a minimum investment approach to one desired to minimise future constraints • looks at constraints from a number of scenarios for growth in distributed generation in the area of the reference network

2 • Annex 3 details growth scenarios applicable to the Technical model based on previous data Annex 4 includes a graphical representation of the price track information used in the model

1.4 Generators Modelled

Although the model is applicable to all sizes of distributed generation it was decided to concentrate on generators of up to 10MW for the purpose of examination of a specific network. Generators of over 10MW are likely to be connected either very close to a main ehv/11kV substation or at 33kV or above. Schemes to connect generators of this size are always “one offs” i.e. very location specific with each justifying an individual study looking at a number of connection and reinforcement options, to be evaluated for capital cost and likely constraints for each option. It was therefore felt to be of limited use to try to generalise about the connection of these generators.

Data can be input to the model to evaluate the optimum choice under various assumptions for settlement rules. Our generic network reinforcement options, based on an actual network, concentrate on the smaller generator as it is more meaningful to generalise reinforcement options at this level.

2 CONSTRAINTS

This chapter presents a brief overview of the main types of constraint that may arise on a distribution network and the methods that may be employed to alleviate them. There have been a number of previous reports both within and outside the New and Renewables Programme on technical aspects of the connection of new distributed generators. It is therefore intended that this chapter concentrate on a short summary of various types of constraint and their alleviation followed by the issues surrounding the balance between alleviation via primary plant investment, control system enhancements and accepting a certain level of expected future constraint.

2.1 What is a Constraint

A constraint is quite simply anything that prevents you doing what you want to do and, in the absence of that constraint, would do. In the context of this study it is being taken to mean specifically preventing generators that are already connected to the network from operating at their desired output level i.e. being ‘constrained off’.

Although in principle this applies just as much to generators being ‘constrained on’ to run at higher outputs than they otherwise would as to being constrained to run at lower outputs or not at all, it is most often applied to generators not being allowed to run as much as they would like. The above is true because although generators can be ‘constrained on’ (using the term loosely, not in any sense implying a particular type of dispatch, for example) their use in this way to support the distribution network tends to be regarded rather more as a “system service” than a constraint. It is taken for granted that if a generator is expected to generate more than it otherwise might to secure the network there must be commercial arrangements in place that ensure that it is not out of pocket as a result of this. How this is achieved will become a more important issue as/if distribution networks become more dependent on distributed generation for their security.

However, for the moment constraints will generally refer to generation, that is already connected not being allowed to operate to as high a level of output as it would like. The question of when/how much generation is allowed to connect is a separate one and is discussed at the end of this chapter.

2.2 Types of Constraint and their Alleviation

2.2.1 Thermal, including Phase Unbalance Thermal constraints are reached when the magnitude of the current flowing reaches a level that causes unacceptable temperature rise in the equipment. On single circuit radial systems (the vast majority of LV and 11kV networks to which generators below 10MW are connected, notwithstanding that post fault there may be an automatic or manual change over to an alternative feed from

4 the other end of an 11kV ring, for example), the usual question that needs to be asked is, “is the load on any part of any circuit currently at or beyond its thermal limit or is it likely to reach that state in the immediate future?” This is distinct from the question “higher up” the network, when there are generally two or more paths in parallel, which is the same as that above plus additionally “if there was a fault would a circuit that remained in service become overloaded?”

Traditionally, distribution networks have been designed for single direction power flow from the source towards demand. Connecting generation up to a certain level therefore tends to reduce flows. Once generation exceeds demand, however, flows reverse and further generation increases the flows further. Therefore up to a certain threshold distributed generation may reduce thermal loading problems, but thereafter it will exacerbate them.

Solutions to thermal loading problems include capital investment in up-rating existing or installing additional circuits, changing network configurations such as the normal split point in an 11kV ring, and limiting the volume of connected generation that is permitted to run at any one time, the amount of course varying with the demand on the critical circuit. The last option implies active management that results in a constraint. It may be that there is some network reconfiguration that can be undertaken remotely to allow more generation to run without breaching thermal limits. If the amount of generation running is likely to vary significantly over time then it is possible that the optimum system configuration will also vary. Some type of active management that alters the configuration as network conditions change may be appropriate. Whilst this may involve some investment in telecontrol equipment or the modification of one or more switching devices for remote operation, it may also present cost benefits over installing up-rated or new circuits.

Phase imbalance may cause problems particularly if individual micro sized generators are installed in nearby houses in a manner that does not distribute generation evenly between phases. It is thought that this is probably best dealt with when the generation is connected rather than to mitigate by constraint. Swapping services between phases to rebalance generation would seem the appropriate course of action in this case.

2.2.2 Voltage The major problem usually encountered with connecting generators to 11kV radial distribution networks is that of voltage rise. Issues associated with this have been covered comprehensively by the article by Dr C L Masters in the February 2002 edition of the IEE's Power Engineering Journal “Voltage rise - The big issue when connecting distributed generation to long 11kV overhead lines”. If the tap changer arrangements and voltage tappings of the 11kV/LV transformers along the line are set up so that the voltage is high enough at the remote end of the line at times of maximum demand without generation, then with line connected generation running there is a danger that at times of low demand the voltage in places will rise above statutory limits. There are a

5 number of ways of alleviating this including fitting lower impedance lines, installing voltage regulators along the line, changing the primary substation AVC (Automatic Voltage Control) scheme and constraining the output of the generators connected to the line with the limit changing as the demand changes in order to maintain a satisfactory voltage at all points. A significant amount of work on issues associated with this is currently being undertaken under the auspices of the Technical Steering Group of the Distributed Generation Coordination Group, DGCG, (website www.distributed- generation.org.uk).

A further solution to over voltage is to vary the power factor of the generator as system conditions change. Whilst this may be satisfactory in the steady state condition one must be mindful of the step change in voltage caused if a generator that is importing or exporting significant reactive power “trips”. There is also the possibility of hunting between adjacent generators that are set up to maintain a particular voltage as well as between such a generator or group of generators and the main substation automatic voltage control (AVC) scheme. These issues are all surmountable if the various voltage control systems are set up in a compatible and co-ordinated manner.

A separate issue is that of some main substation transformer tap changers being unable to accept reverse power flow. The corrective options here are either to modify or fit new tap changers or to constrain the power flows so that they do not reverse to flow from 11kV up to the higher voltage (typically 33kV). This may be effected either by constraining the amount of generation that may run or reconfiguring network split points as the demand and generation changes or a combination of the two.

2.2.3 Fault Level Fault level issues associated with increasing amounts of distributed generation have been described in several previous reports. Corrective options include uprating switchgear, reducing other fault infeeds by opening bus sections or opening one of the transformer LV circuit breakers at the primary substation. Introducing additional impedances such as series reactors and/or installing higher impedance transformers at primary substations are other methods that may be used.

A generic problem occurs if the amount of connected generation connected varies significantly over time. If the system is set up to stay within the maximum allowable fault levels with all possible generation running then, if little or none of it is on and the network configuration is not altered, the fault levels may be unsatisfactorily low. Low fault levels make voltage control more difficult, lead to larger voltage swings if there is a sudden change in demand and can also make protection systems more difficult to grade. It is often therefore beneficial to alter the network configuration dynamically as system conditions change i.e. manage the system actively. It is also the case that opening circuit breakers reduces security and it is therefore often necessary to fit an automatic closing scheme that operates if a circuit trips.

Super-conducting short circuit limiting devices that may limit fault levels without presenting a high impedance to normal load currents are currently under development. These may become one of the options for additional investment in hardware upon connection of increasing amounts of distributed generation. Furthermore they are intrinsically “fail safe” unlike explosive fuse devices and more likely to be acceptable from a safety point of view.

Apart from various combinations of network upgrading and active network management to reconfigure networks as conditions change, another method of containing fault levels is to limit the generation that can be run simultaneously on a particular part of the network. This involves imposing a constraint and in certain circumstances such as when the frequency of such a constraint for a particular generator is low, this may be the most economic way to manage the situation.

2.2.4 Protection Limitations It will often be the case that protection arrangements must be modified or reset to cope with the situation that, with the connection of generation, there is more than one potential infeed to a fault. In general once the minimum protection changes to accommodate new generation have been made, the protection will not be a cause of constraints on its operation. A possible exception is described below.

The exception relates to the field of system automation, including at its simplest auto-reclose schemes for overhead line faults. In order to provide maximum security for customers at minimum cost there is an increasing use of sophisticated post fault automatic switching and supply restoration schemes. The customer may experience these schemes as a loss of supply followed by a rapid restoration. Without further information it is not clear that the system has stabilised. Distribution Network Operators would therefore not wish generation disconnected upon the loss of supply to reconnect without establishing that it was safe to do so. At present safe reconnection is ensured via a phone call between the generator and the Distribution Control Centre. Given that many new distributed generators will not have staff continuously available and the high workload, particularly during bad weather at Distribution Control Centres, there may be a significant delay between the generator wanting to reconnect and the necessary communication being available to allow this.

Many smaller generators may have facilities that reconnect automatically after sensing the return of mains voltage (and possibly a time delay). This may however be inappropriate for generators that are larger, particularly if they are quite large relative to the capacity of the network into which they are connected. These generators may suffer delays in reconnection following any incident in which an automatic switching sequence has been initiated. This constitutes a potential “constraint” on the generator's behaviour. There may be scope for lessening such “delay to reconnection” constraints by further automation involving sending “permission to reconnect” signals to

7 disconnected generators. The economics of such schemes for smaller generator may be a factor limiting application.

2.2.5 Flicker and Harmonics As for protection, one would expect that the minimum network engineering necessary to stay within acceptable flicker and harmonic limits would be undertaken prior to the connection of a new generator. In some instances it may be sensible to connect such that there is a constraint on the number of particular kinds of generator that can operate at any one time in order to stay within acceptable limits, particularly at times when fault levels are low. It is envisaged that inverter-connected generators would be subject to these types of harmonic related constraints.

Flicker problems may be caused by a generator whose output fluctuates rapidly, especially if it is of significant capacity relative to the network it is accommodated in. Single plant wind installations may be potential sources of flicker. It is thought that certain types of micro CHP plant may also be a source if their output varies with household gas usage. The extent to which this is the case is not currently known.

2.3 Balance between Reinforcements, Active Network Management and the Acceptance of Constraints

Traditionally with few exceptions both generation and demand has been connected to distribution systems on a “connect and forget” basis. The system has been designed so that once connected the generation or demand is allowed to vary its output or ‘take’ between its minimum and maximum levels in an unconstrained manner. It may be that there will be an increasing trend towards this ceasing to be the general rule.

In many cases it will become cheaper to employ active network management, and perhaps accept that there will at times be constraints on how much generation can run, than to reinforce the network so as to allow unconstrained generation. Any constraint (other than a generator becoming disconnected from the network by a fault) implies active management taking place i.e. a decision being taken that because of system conditions at a particular time certain generation must be constrained. This may involve human intervention or may be automated e.g. a scheme that automatically monitors how many generators are connected to a part of the network and once a particular number or combination is reached sends out a signal automatically that prevents additional generators in the area connecting.

Whilst a constraint always implies “live human” or “pre-programmed” active management it is not the case that active management always involves a constraint. In the example above for instance when a certain number of connected generators were connected, the action might have been, not to prevent further connection, but to open a bus section or infeed circuit breaker to keep fault levels within limits. In this case active management would have

8 been used not to initiate a constraint but to allow continued unconstrained operation.

In terms of allowing generators to connect in the first place this report assumes that there will be a wide choice available as to the commercial firmness of the connection i.e. generators can opt for less firm connections in exchange for paying lower charges. This implies an acceptance by them of liability for a higher level of constraint than would have been the case if they went for a commercially firmer connection with higher charges. In assessing the options available it is assumed that the Distribution Network Operator (DNO) will have no incentive to weight primary equipment reinforcement differently to active management “investment” where both achieve equivalent security at the same cost. This will result in a number of levels of “investment” (whether in primary equipment or not) each of which gives a different level of anticipated future constraint exposure. A balance must be struck between initial investment and future risk. Generally the less frequent the expected constraint of generator output the less justification there will be for expenditure to avoid it.

Which parties fund investment, are exposed to the risk and therefore make decisions is discussed in chapter 6 ‘Allocation of Costs’. This issue becomes more complicated when considering many small generators connecting to the same area of network than it would be in the case of a larger generator with few interactions with the connection of other parties.

9 3 SUMMARY OF TECHNICAL MODEL

3.1 ‘Test’ Network

As described in Annex 1 a representative system has been chosen on which to model Distributed Generation and Constraints and this is shown in the diagrams below. The 11kV diagram is shown first, followed overpage by the sections of LV network modelled.

The network is chosen to be representative of a typical distribution system and plant data within Seeboard network in the Faversham area. In the model, a 33kV Substation supplies 11kV consumers at Feeders 6 and 10 with smaller consumers connected at 230/398.4V via LV transformers and circuits. See Annex 1 for discussion of the selection of the model.

11kV Network Modelled

10 Four different LV sections are used. The first two represent urban areas fed from 11kV/433V substation transformers, while the others are fed from pole- mounted transformers supplying semi-rural and rural systems as follows:

1. Judd Road (urban area): This section is feeding 204 LV customers as follows; 112 are at Hazebrouk Rd N/W, 15 at Hazebrouk Rd N/E and 77 at Judd Rd/ Crossway/ Lower Rd

2. London Road Boughton (urban area): This feeding 76 LV customers

3. Woodman Hall (semi-rural): This is a semi-rural area. The section is feeding 69 LV customers from a LV substation

4. Oversland (rural): This is a rural area fed from a pole transformer with 23 customers

The transformer sizes are 500kVA for Judd Road substation, 200kVA Woodmans Hall substation, 100kVA London Rd Boughton substation and 50kVA for Oversland pole transformer.

LV Network Modelled

11 3.2 Generation Scenarios

Annex 3 contains data from previous reports on possible growth scenarios for renewables in the Seeboard area, and a possible mix of those generators to make up the total.

However, as discussed in Annex 2, the distribution of renewable and other distributed generators is not going to be uniform around the distribution network. It is to be expected that some areas will have well above an average level and other areas will have much less. Thus although a level of penetration is associated with a target “average” for a year say 2015, it is perfectly credible that it could be achieved in 2010 or even before in parts of the network with “above average” levels of penetration. Accordingly it will simply be referred to as a ‘High Generation’ case, divorcing it from association with a particular year.

Consistent with the average High generation level described in Annex 3 and scaled appropriately to the demand at Faversham being modelled and local conditions, the following generation was modelled. Note that the 3.316MW in the table below is compared to about 1MW if this were scaled from the average load demand figures for the two feeders compared with the overall demand for the total Seeboard area:

3.2.1 Generation - ‘High’ Case

Generation - ‘High’ Case MW 1. A 1,500KW farm waste digestion generator is connected through a 1.5 transformer to the 11kV network at the “Oversland” farm (bus ‘391126TP’). This generator can supply power to the 11kV network for 8500h/yr

2. 13 micro CHP units connected to Oversland customers, with each unit 0.013 output capacity of 1 kW

3. 10 PV units connected to Oversland customers, each unit output 0.05 capacity of 5 kW

4. A 1,320KW landfill unit is connected through a transformer to the 11kV 1.32 network at “Woodman Hall” (bus ‘391164TP’). The load factor of this distributed generator is 7500h/yr

5. 103 micro CHP units installed for the customers at Hazebrouk Rd of 0.103 Judd Road LV section. Each unit has a maximum generation of 1 kW

6. 66 PV solar units installed for the customers at Judd Rd, Crossway and 0.33 Lower Road Judd LV section. Each unit has a maximum generation of 5 kW.

TOTAL 3.316MW

The ‘theoretical’ 1MW is calculated as follows: As Faversham feeders 10 & 06 have a demand of 1.7MVA & 4.3MVA for 2002/3 compared with Seeboard’s maximum demand of 4,000MVA this approximates to a ratio of about 0.15% of

12 load. Applying this to generation, with the total generation predicted for the Seeboard area at 662.5MW in Annex 3 this gives about 1MW of distributed generation in the ‘test area’, i.e. 0.15% of 622.5MW is equal to about 1MW.

3.2.2 Generation - ‘Medium’ Case The Medium penetration level assumed the following generation connected:

Generation - ‘Medium’ Case MW 1. A 1,500KW farm Waste Digestion generator connected through a 1.5 transformer to the 11kV network at the ‘Oversland’ farm (bus “391126TP”). This generator can supply power to the 11kV network for 8500h/yr.

2. 13 micro CHP units connected to Oversland customers, with each unit 0.013 output capacity of 1 kW.

3. 10 PV units connected to Oversland customers, each unit output 0.05 capacity of 5kW.

TOTAL 1.563MW

3.2.3 Generation – ‘Current situation’ & ‘Low’ Cases Modelling of the current and ‘Low’ generation cases found no reinforcements required to prevent constraints and so were not used further in the technical analysis.

3.3 Reinforcement Scenarios

3.3.1 Reinforcement - Low Generation The ‘Current Situation’ and the ‘Low’ generation penetration levels modelled require no reinforcement so it is the Medium and High generation levels that require consideration.

3.3.2 Reinforcement - Medium Generation From the modelling results in Annex 2 it can be seen that the problem at medium generation is a high voltage within the Oversland LV network. Two alternative reinforcements have been suggested to overcome this:

Option 1. Replacement of the 11kV/LV transformer at Oversland with one with a wider range of tapping positions including one that would be maintain the voltage within limits.

Option 2. A 30KVAr shunt reactor connected at the LV transformer terminals at Oversland

Option 1, ‘replacement of the transformer’ was favoured as it would provide an option of a low loss transformer, should the regulatory regime make this beneficial to the DNO. For the conditions studied a transformer with off-load tap changing capability only would be satisfactory. If the variation between the lowest and highest net demands were to increase further, a distribution

13 transformer with an on-load tap changer and Automatic Voltage Control AVC scheme would be needed. If this were anticipated it might be preferable to fit such a transformer initially.

Option 2, addition of the shunt reactors was not favoured due to spatial constraints and increased network losses.

Both options were checked to confirm that they would not result in voltages below statutory limits under maximum demand conditions.

3.3.3 Reinforcement – High Generation It can be seen from the full results in section Annex 2 that for the High generation case: • in addition to unacceptably high voltages in the Oversland and Judd Road networks, there are: • some overloads in the Judd Road low voltage network • as well as reverse power flows through the 33kV/11kV transformers. The reverse power flow occurs because the demand and generation on only a limited number of feeders is being modelled. However if these feeders where representative of the demand and generation patterns on the other feeders at Faversham then there would be a genuine reverse power flow through the 33kV/11kV transformers.

The preferred reinforcement option was again replacement 11kV/LV transformers, with the possibility of on-load tap changers and automatic voltage control AVC to be considered should an element of “future proofing” be required. Additionally the 33/11kV transformer tap changers would have to be replaced to allow reverse power flow. This might involve either work on the tap changers themselves such as changing the diverter resistors or a complete change of the transformers.

Although theoretically the high voltage issue could be relieved using shunt reactors (300kVAr reactor at Judd LV transformer substation, 120kVAr reactor at Woodman Hall Pole mounted substation, & 30kVAr reactor at Oversland Pole mounted LV terminals) this was rejected again on the same grounds as for the Medium generation case above.

In addition, in order to relieve the overloading in the Judd Road low voltage network, the cable reinforcement requirements detailed in the cost table below were identified.

In the constraints analysis below it was decided, in addition, to examine the ‘partial reinforcement’ situation where the low voltage cable reinforcements were undertaken, but no transformers were replaced.

14 3.3.4 Reinforcement - Costs a) Costs for Replacement Transformers with off load tap changers

Transformer Replacement Indicative Cost 1. 50kVA pole mounted for Oversland £3,700

2. 200kVA pole mounted for Woodman Hall £6,000

3. 500kVA ground mounted for Judd Road £15,000

Additional cost of replacement of 33/11kV tap changers to take Between reverse power flow depending on the extent of upgrade £10,000 and required. £260,000 per transformer

b) Costs of Replacement Low Voltage Cables

‘LV only’ Reinforcement Indicative Cost 1. An extra pair of cables ‘Stranded Copper (imp), 0.06 type’ £17,000 at Lower Road to east of length 262 meters each in the LV section of Judd Road. 2. An extra reinforcement cable 185mm Aluminium from £3,500 Judd Road to 1st branch with a length of 50 meters. 3. An extra cable (type 120W) from Judd Road, 1st branch to £3,100 2nd branch at Lower Road of a length of 60 m.

3.4 Constraint Results

3.4.1 Constraints Modelled Studies were undertaken for Low, Medium and High generation penetration levels with no network reinforcement, ‘LV Only reinforcement’, and ‘Full reinforcement’. The effect on constraints are described in the sections which follow.

3.4.2 Constraints - ‘Low’ Generation For the ‘Low’ generation level there were no constraints.

It should be noted however, that one can not generalise to say that no reinforcement will be needed on any network at a Low generation level. Apart from all networks (and possible generation growth patterns) being unique, the modelling undertaken has assumed balanced three phase generation penetration. At low voltage this may not be the case and in certain areas as discussed in Annex 1 if a three phase low voltage supply is available, post connection balancing may be carried out by changing the phase to which some of the new low voltage generation premises are connected to. If this is not possible, phase imbalance can lead to voltage rise effects of up to six times that of balanced connections for the same penetration level. This is because of the

15 current magnitude in a single phase increasing three times compared to connections of the same size balanced over three phases and the fact that there is now potentially a current of this size flowing in the neutral, rather than no neutral current in a balanced system (UMIST PV Experimental Programme “Simulation and Analysis of the Effects of PV Systems on the Supply Network”; N Jenkins, G Strabac and M Barnes).

3.4.3 Constraints - ‘Medium’ Generation For the case with ‘Medium’ generation, repeated studies were undertaken at the various reinforcements, with increased demands and appropriate patterns of generation until no system voltage, current or other limits (constraints) were violated. It was confirmed that there were no constraints at any higher demand levels than this i.e. that all constraints were at a particular demand level or less. The resulting constraints for the Medium Generation level are summarised below.

In the table generation constraints (if any) are split by column according to the part of the network to which the generation is connected. More detailed results are given in Annex 2.

Summary of Constraints - Medium Generation Network Section Main supply LV at LV at LV at LV at 33/11kV substation Judd London Wood Oversl ‘0080450’ Road Rd man and Boughton Hall No Potential Distributed 2,025 MWhr/yr - - - None Reinforce generation energy not ments permitted to the network in MWhr/year ‘Full’ Potential Distributed None - - - None Reinforce generation energy not ments permitted to the network in MWhr/year

Medium Generation – No reinforcement It can be seen that the farm waste digester is constrained down from 1500KW to 1200KW for a large portion of the year, resulting in a potential loss of over 2GWh. There is no need to constrain any of the LV connected generation although as discussed if it is not possible to balance the phase loadings sufficiently this might no longer be the case.

Medium Generation – ‘Full’ reinforcement With the Full reinforcement, there are no generation constraints. From Annex 2 it can be seen that in particular the voltage at Oversland is satisfactory (though would not be if at some time in the future the upper permissible voltage limit was reduced to 230 volts +6%).

16 3.4.4 Constraints - ‘High’ Generation As for the Medium generation level, repeated runs were done at ‘High generation’ reducing output until a point was reached where no limits were breached. This resulted in the following limitations for the three reinforcement scenarios. These are discussed in more detail in the paragraphs below:

Summary of Constraints - High Generation Reinforcemen Network Section LV at LV at t London LV at 11kV network LV at Judd Wood Rd Overslan ‘0080450’ Road man Boughto d Hall n No Potential Distributed 6,556 261 MWhr/yr - - None Reinforcemen generation energy MWhr/yr t not permitted to the network in MWhr/year ‘LV only’ Potential Distributed 3,865 None - - None reinforceme generation energy MWhr/yr nts not permitted to the network in MWhr/year ‘Full’ None None - - None reinforcemen ts

High Generation – No reinforcements At this level of generation with no reinforcement, it would be necessary to constrain a considerable amount of low voltage connected generation at Judd Road and the 11kV connected generation.

High Generation – ‘LV only’ reinforcements It was also decided for ‘High Generation’ to investigate the effect of carrying out all the low voltage cable reinforcement at Judd Road but no other reinforcements. It is marginal whether for the generation that can run under these conditions it is necessary to have tap changers on the 33kV/11kV transformers that can accept reverse power flow. It was deliberately decided for this scenario to try to avoid constraining any low voltage connected generation. The maximum generation that could be allowed under these conditions is as shown above.

It can be seen that compared to the “no reinforcement” scenario the total energy constrained from being produced is almost halved. One explanation for this is that, with the LV cable reinforcement, transformer taps can be lowered without the voltage becoming too low under maximum demand conditions thus relieving the voltage constraint to a significant extent as well as the more obvious effect of eliminating the low voltage overloading.

High Generation – ‘Full’ reinforcements This reinforcement option leads to no generation constraints. Hence With “full” reinforcement i.e. transformer replacement (or theoretically the addition of shunt reactors) and reinforcement of some sections of low voltage cable in the Judd Road network, no limits are breached.

17 3.4.5 Summary of Constraints The constraints discussed above may be summarised in the table below:

Summary of results of Constraints Modelling for various densities of Generation Present Low Medium High No Reinforcement None None 2,025 MWhr/yr 6,556 MWhr/yr on on 11kV network 11kV network

261.61 MWhr/yr at LV Judd Road ‘LV Only’ Reinforcement - - None 3,865 MWhr/yr on 11kV network ‘Full Reinforcement’ - - - No Constraints (Transformer Replacement & LV Cable replacement)

3.4.6 Constraints - Lack of Frequency Response It is worthwhile to investigate a different type of constraint that is unrelated to the reference network but may be relevant to distributed renewable generation in the future, particularly large wind farms.

The National Grid Company (NGC) currently have a concern that, particularly at times of very low demand, there will not be sufficient plant running that has a significant active frequency response capability. Their current approach is to suggest that all non-traditional forms of generation with a completion date of after January 2006 should have the same frequency response capability as traditional forms of generation. (Grid Code Consultation D/03 June 2003).

An alternative approach would be to leave the decision to provide frequency response capability to the generator with economic incentives to encourage provision. A consequence of this may be that generation without active frequency response capability would, on occasion, not be allowed to run. Such times would fall mostly at times of low system demands. Therefore the economic model was used to calculate the income forgone by not running during periods of very low frequency (low demand). It was noted that wind generators may not run during such periods due to lack of wind.

18 A load duration curve from the NGC Seven Year Statement is shown below to illustrate this:

Given that 100% of demand corresponds to over 50GW, stopping generation running for the lowest 5% or 6% demand of the year (right hand end of curve) gives an additional 2 to 3GW of demand to be met from alternative plant with a frequency response capability. It is considered unlikely in the short to medium term (for example until most of the older nuclear stations have been closed) that there would be more wind farms running than this at times of minimum demand so it should be sufficient to consider not allowing such generation to run on occasions for that sort of period of the year at the most. The economic analysis for this is carried out in Section 5.5.

19 DESCRIPTION OF ECONOMIC MODEL

4.1 Economic Model - Outline

In order to calculate the cost of constraints and balance it against network reinforcement costs, an economic model was developed under this project that would have sufficient flexibility to be used for a wide variety of scenarios and with a larger number of different types of generator than are being modelled for this study.

The model can simulate up to 20 years of operation and each year is divided into ten time bands/price segments. The flowchart for the model is shown overpage.

4.2 Economic Model - Inputs and Outputs

An example of the input and related output is shown below by way of an example:

4.2.1 Input Data There are eight categories of input data to the economic model (these are described and discussed in more detail in the sections that follow):

a. Case title b. Capital Cost and timing of network reinforcement c. Discount rate d. Standing generator data comprising generation running cost and whether “ROC” entitled e. Time period definition f. Value of electricity in each time period/income forgone if constraint predictable and unpredictable g. Cost per MWh varying by year of “ROC” type income forgone h. MWh Constrained for each generator type in each time period both predictably and not

4.2.2 Output The output of the model details for each generator type the income forgone in each year for each type of constraint (reasonable notice or not), any ROC type income forgone and running cost saving as well as a discounted total “cost” for the year. Summaries are produced as well as a total figure for the net present cost of constraints and reinforcements for the scenario being evaluated as shown in the example below.

The output includes a full description of the case, taken from the main case title and all the sub titles as well as a summary result and year by year item by item results. For example, the format would look something like the following (restricting the study to 8 years purely to avoid unnecessary size of the example):

• High solar penetration • 11kV switchgear uprated and shunt reactors added • 6.5% discount rate • High gas costs from year 6 • High priced electricity at peak periods from year 5 but collapse in low demand period prices from year 7 with extreme short notice prices also from year 7 • Shortage of “ROCs” in years 5-8 • High proportion of constraints predicted

TOTAL Net Present Cost of Constraints plus reinforcements £1,875,632

This would also provide a break-down in a ‘results table’ as follows:

Total Reinforce Constraints Constraints “ROC” Generation Total Discounte Cost ments (predictable (prompt price Loss Cost saving Cost d Of ) exposure) Total Cost (£k) Year 1 a b c d e f g 2 h i j k l m n 3 n o p q r s t 4 u v w x y z aa 5 ab ac ad ae af ag ah 6 ai aj ak al am an ao 7 ap aq ar as at au av 8 aw ax ay az aaa aab aac Total discounted Total Total Total Total Net reinforcement discounted discounted discounte discounted present predictable constraints d “ROC” generation cost constraints (prompt price income cost saving exposure) lost £xxxxx £yyyyy £zzzzz £wwwww £1,875,632

21 Flowchart for the Economic Model process showing the inputs and outputs

Set Year =1 Any other Generator type=1 generator Time band=1 types? Y

N Increment generator type. Multiply MWh Reset time constrained (orderly trade out) by price/MWh Sum total cost of constraints in

year

Multiply MWh constrained (cash out price exposure) by price/MWh

Is generator Add cost of network entitled to ROC reinforcements in year

type income?

N Y

Multiply total MW constrained by “ROC” type income forgone Apply discount factor for year to cost of constraints plus network reinforcements Sum income forgone

Y Any more Multiply total MWh constrained years? by cost saving/MWh N

Increment Year. Reset Generator type=1 Sum discounted total Calculate net cost = income annual costs to forgone less cost saving Time band=1 produce total cost

Are there any other time FINISH Y bands in year?

Increment Sum net cost of time band constraints for this generator type

4.3 Economic Model - Description of Inputs

Taking each item in turn as introduced in section 4.2: a. Case Title The input will be an alphanumeric phrase. In addition each other item of data should have the facility for their own title. For a run output the case title and the “subtitles” of the separate sets of input data should be brought together as a full description of that case. Example of case title: “High solar penetration” b. Capital cost and timing of network reinforcement This input details the cost of reinforcements in the scenario being modelled.

This will be one cost item per year (for up to 20 years) in thousands of pounds and have an alphanumeric title. For a twenty year study entries would be expected to be sparse. An example of the data would be: “11kV switchgear up-rated and shunt reactors added”

Year 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 1 20 9 Reinfor 2,200 400 cement Cost £k c. Discount rate Another key input parameter is the discount rate to be used. When adding reinforcement or constraint costs that occur in different time periods each one has to be “discounted” by a suitable amount to reflect the time value of money. Thus constraint costs incurred one year in the future are discounted by the factor chosen, before being added to constraint costs being incurred now, to reflect the fact that a cost in the future could be paid for with a lower amount of money today, by investing it for a year.

This would be a single figure for each study (assumed to be a percentage), the figure, plus the term “% discount rate” forming the subtitle for the output. An example of the input data could therefore be: “6.5” It is currently thought appropriate to use nominal rather than real terms for all cash values so nominal rates of return are required. Thus it was decided to use nominal terms for all money values i.e. all fuel costs/electricity prices are in money of the day assuming 2.5% annual inflation. This is in line with the Government target for the Bank of England. The discount rate can be set at any value but clearly should be a nominal rather than a “real” rate i.e. it should not be net of inflation. Thus for example if a “real” rate of return of 4% is to be

23 assumed then the nominal rate with 2.5% inflation would be 6.5% and that is the figure that would be used in the model. d. Standing Generator data If a generator is unable to run it may save some cost (typically fuel). Each generator has a facility for such a cost saving to be set independently for each year of the simulation.

This comprises for each generator type, the running cost/MWh of generation (which for many types of renewable would be zero) and additionally whether that type of generator was entitled to a “ROC” or equivalent. There would also be a title for this set of data. A typical set of data might be: “High gas costs from year 6” Generator Generator “ROC” Running 1 2 3 4 5 6 7 8 9 10 type Type entitlem cost/MW reference ent? h in year

1 Large solar Y 0 0 0 0 0 0 0 0 0 0 2 Small solar N 0 0 0 0 0 0 0 0 0 0 3 Micro CHP N 27 28 29 30 32 45 47 49 52 55 4 Waste N 12 12 13 12 14 14 15 14 15 16 5 Landfill Gas Y 0 0 0 0 0 0 0 0 0 0 6 LV N 0 0 0 0 0 0 0 0 0 0 connected wind 7 HV Y 0 0 0 0 0 0 0 0 0 0 connected wind Note that the dimensions of this table could be up to 15 generator types and 20 years. e. Time period definition The year is spilt into ‘Time Bands’ as below. Up to 10 time bands per year should be allowed for, expressed in terms of hourly bands (expressed as a % of hours in the year) starting with those of lowest electricity prices and progressing upwards to those of higher prices. Thus time band one comprises the 1% of hours in the year (87.6 hours) with the lowest demands. Time band 2 comprises the 5% of hours in the year with the next highest demands and so on so that band 10 comprises the 1% of hours with the highest demands in the year. There should be no need for a title for this section of data. An example of the data could be:

Time/Demand 1 2 3 4 5 6 7 8 9 10 Band reference % hours in year with 1% 5% 10% 20% 20% 20% 10% 8% 5% 1% lowest price from previous up to

In the above, it has been assumed that a load duration curve with a correlation between demand levels and prices is sufficiently accurate for use in the model

24 and that ten demand/price bands per year would suffice. The reason that the above time split has been used (although any other division could be modelled merely by ensuring that the constraints were split into the desired time bands and the price information was averaged by the same price bands) is to be able to have extremes at either end of the price duration curve if desired. Thus it would be possible to look at extremely high electricity prices for the top 1% of hours in a year and likewise zero or even negative prices in the lowest 1% of time. The “middle” time/price segments of the year are currently grouped together in 20% segments although the year can be split otherwise if preferred. f. Value of electricity in each time period/income forgone If a generator is constrained from running it can not sell its output. The loss is the value for which it could have sold less cost savings from not generating. As discussed below this holds true in cases where there is “adequate” notice of the constraint and either the generator has not yet sold the energy that it will not been able to produce or it has but can trade its way out of the position i.e. buy back the power at a similar price. The conditions for this to be possible are a reasonably liquid market and that the price has not moved significantly since the original sale was made. If there is little notice of the constraint then the generator trying to trade out of its position (or other party doing so on its behalf) will be distressed resulting in a less favourable price. If there is very little notice the only option may be, under current market arrangements, to go out of balance in the balancing mechanism.

The difference in prices between the situation when one has time to trade at leisure and when one does not will depend on the liquidity of the market and how it has moved. It is possible in some circumstances that the prices obtained in a prompt trade (or even in balancing mechanism cash out) may be better than in an orderly trade. This however will not be the normal situation and we have not created any scenarios where constraints with little or no notice result in a lower loss of income than those of which there is more notice.

The balancing mechanism rules and indeed the whole trading mechanism may change significantly in the future. Nevertheless it is felt that it will always be valid to have some sort of premium for the cost of resolving constraints of which there is little notice. One could for instance postulate that there is some sort of generators’ insurance scheme under which generators pay into a fund that pays for a band of reserve to cover shortfalls, whether caused by plant breakdown, constraints or even lack of wind. If this was allowed to prevent shortfalls being targeted individually then the cost may become similar to that of purchasing energy on an orderly market. On the other hand targeting imbalances on individual generators that are short for whatever reason will tend to maintain a differential between orderly trading prices and those obtained when there is little notice. In general differentials between orderly and distressed trading/balancing mechanism prices tend to increase the tighter the margin between supply and demand gets i.e. the higher the demand.

25 Thus this input comprises two tables each with figures in £/MWh for each time period in each year. There will also be an alphanumeric heading that may be rather longer than for the other headings. An example might be: “High priced electricity at peak periods from year 5 but collapse in low demand period prices from year 7 with extreme short notice prices also from year 7”

£/MWh Time/De 1 2 3 4 5 6 7 8 9 10 income mand forgone with Band sufficient referenc notice for e orderly trades Year 1 0 4 9 13 16 18 22 27 38 112 2 0 4 9 13 16 18 22 27 38 112 3 0 4 9 13 16 18 22 27 38 112 4 0 4 9 13 16 18 22 27 38 112 5 0 4 9 13 16 18 22 33 52 140 6 0 4 9 13 16 18 22 33 52 140 7 0 0 4 5 9 15 25 33 52 140 8 0 0 4 5 9 15 25 33 52 140 9 0 0 4 5 9 15 25 33 52 140 10 0 0 4 5 9 15 25 33 52 140 11 0 0 4 5 9 15 25 33 52 140 There would be a similar table for income forgone (imbalance cash out/illiquid short term trades) which would have an identical format but (usually) different £/MWh figures. Both tables are dimensioned for up to 20 years of data. g. Cost/MWh of ROC type income forgone In addition to the MWh constrained below, one may set each generator type to lose an additional payment that may change every year but does not vary with time or “notice” of the constraint. The obvious current application for this additional income forgone is to simulate the loss of Renewables Obligation Certificates (ROC) payments. What types of generator are eligible for such payments and the practicality of claiming them for very small generators may be a matter of conjecture for the future but the model allows flexible assumptions to be made on this.

This is one figure per year in £/MWh which will also have one alphanumeric heading. For example: “Shortage of “ROCs” in years 5-8” Year 1 2 3 4 5 6 7 8 9 10 11 12 1 1 15 16 1 1 19 20 3 4 7 8 £/MWh 43 44 45 45 53 56 55 56 48 42 43 42 4 4 43 41 4 4 44 43 value 1 0 2 3 of “ROC” h. MWh Constrained For each of the time bands two different “gross costs of being constrained off” i.e. income foregone may be referenced. This enables a distinction to be made between predictable constraints and those that there was little or no notice of.

26 It can be postulated that if it is known in advance that generation will not be possible a generator can trade out of his position (or not sell the electricity that will not be generated in the first place). If there is little or no notice of a constraint then it can be assumed that it may be more expensive. For example a generator may be a distressed purchaser of energy to make up the shortfall or he may under current arrangements be cashed out in the Balancing Mechanism.

For the size of generators being considered in this study one would expect all trading or cash out exposure to fall to the supplier or consolidator through whom the generation is sold in the first instance. Separate input figures may thus be given for the energy constrained off for each time period for each type of generator where there is reasonable notice of the constraint and where there is little or no notice. The way “reasonable notice” is described as far as the model is concerned relates merely to which of the two sets of prices one wants to assume is lost due to the constraint.

For each generator type there would be two tables of identical format each giving constrained MWh in each time band in each year, one table for constraints that can be predicted far enough in advance to trade out of them in an orderly fashion, the other where there is insufficient notice for this and therefore exposure to cash out price or trading in a relatively illiquid market. There may be a separate heading associated with this table for example: “High proportion of constraints predicted” The format of the input tables would be as per the example below:

MWh Time/Demand 1 2 3 4 5 6 7 8 9 10 constrained, Band reference reasonable notice so orderly trades. Generator type 1 Year 1 32 34 28 29 14 6 0 0 0 0 2 30 33 26 27 12 2 0 0 0 0 3 29 30 25 25 11 1 0 0 0 0 4 28 29 24 24 10 0 0 0 0 0 5 28 29 24 24 10 0 0 0 0 0 6 28 29 24 24 10 0 0 0 0 0 7 28 29 24 24 10 0 0 0 0 0 8 28 29 24 24 10 0 0 0 0 0 9 28 29 24 24 10 0 0 0 0 0 10 28 29 24 24 10 0 0 0 0 0 11 28 29 24 24 10 0 0 0 0 0 The table would be identified for up to 20 years of data and there would be a table in similar format for constraints that were not as predictable sufficiently far in advance to allow orderly trading. There would be a pair of such tables for each type of generator.

4.4 Economic Model - Price Tracks/ Combinations

Annex 4 illustrates in graphical form the five basic price “tracks” each one with a ‘normal’ and ‘peaky’ variation to give 10 graphs. ‘Peaky’ means that the prices as demands rise increase more than for the ‘normal’ versions.

The basic price “tracks” i.e. the way electricity prices are assumed to change over time were taken as follows: 1. Current forward curve for 4 years then flat real. In other words this scenario takes the actual forward prices in the market for the next 4 years as they were in June 2003 and for the period after this 4 years indexes the four year ahead price by the assumed rate of inflation of 2.5%. This represents a continuing over supply i.e. continuing buyer power and prices remaining depressed 2. As above for 4 years but then trending towards new entrant prices by 2011 The new entrant price is a CCGT with a real gas price of 20p/therm so it implies a move towards a sustainable (in economic terms) equilibrium. 3. As case 2 above but trending to a high new entrant price This is as for the case above but assuming a gas price of 30p/therm because for instance exporting countries such as Russia and Algeria are able to use their producer power. 4. Two per cent a year real annual increase A “steady as she goes” case. 5. Large Combustion Plane Directive bites and high new entrant prices by 2006, increasing thereafter at 1% real until 2016 This is the steepest rise of all and assumes coal retirements forced by the LCPD coinciding with nuclear retirements and high gas prices as for case 3.

Of the five scenarios constructed above, each was profiled with time in the year in two versions, ‘normal’ and ‘peaky’ to give ten types of “orderly traded” price profile. The average annual price performance under each of these scenarios as well as the annual shapes are given in Annex 4.

On top of this three “prompt price” derivatives were constructed for ‘non- orderly trades’ where there is little notice of the constraints. It was assumed that they would be related to the orderly traded ones in one of three ways: 1. A fixed modest increment (£2/MWh) between the two prices. This corresponds to some sort of insurance arrangement minimising additional premium at high demand levels 2. A scenario that assumes that the price for the highest priced 1% of the year is double for prompt trades/balancing mechanism cash out than for orderly trades with a differential that declines in a logarithmic manner to give no premium for the bottom 1% of prices. Although recent changes to the imbalance cash out mechanism makes observations under the current rules over a whole year impossible this scenario probably represents differentials that may be expected under the present rules 3. An even peakier adjustment based on a power function

This gives a total of thirty different orderly/prompt price profiles. The prompt/orderly factors applied for scenarios 2 and 3 are shown below:

Forced trade/orderly trade ratios (fixed differential option not shown)

Non-Orderly Shaper Multiplier

4.50 4.00 3.50 3.00

2.00 1.50 1.00 0.50 25%29% 33% 37%41% 45% 49%53% 57% 61% 65%69% 93 97% 0.00 89% % 1% 5% 9% 17% 73%77% 81%85%

Tranche

Shape 2 Shape 3

29 This can then be combined with seven ROC scenarios that were developed as on the figure below:

Within each of these scenarios the high or low obligation refers to whether the level of obligation increases post 2011.

Note Scenario 4 assumes that there is an increased allowance to earn ROCs with appropriate fuels co-fired with non-ROC entitled fuels. Although this facility could be utilised for a payment other than ROCs, the income forgone streams for the scenarios modelled assume that the value was based on reasonable expectations of the value of ROCs.

ROC Scenarios £/MWh 100.00

90.00

80.00

70.00

60.00

50.00

40.00

30.00

20.00

10.00

0.00 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Year

High Build, Low Obligation £/MWh Central Build, Low Obligation £/MWh Low Build, Low Obligation £/MWh Central Build, Extended Cofiring, Low Obligation £/MWh High Build, High Obligation £/MWh Central Build, High Obligation £/MWh Low Build, High Obligation £/MWh

This combined with the 30 scenarios given above gives 210 different price combinations that are available for use.

30 5 RESULTS OF ECONOMIC MODELLING

5.1 Outline

The results from the Technical model described in the chapter 3 was used in the Economic model of chapter 4 to investigate the monetary costs imposed on distributed generators by different distribution system operating conditions. The effect of generation constraints and reinforcement costs on the level of justifiable system investment was modelled using Faversham as a representative distribution network.

Some parameters were set as constant throughout the investigation. A non- zero generation cost was applied only to Micro CHP (2p/kWh at current prices). This cost was designed to reflect the natural gas input. It is possible to argue that Landfill Gas and Farm Waste Digestion bear a cost when generating intermittently, for example the cost of burning off excess gas. This cost was considered as wasted “free” fuel and therefore as for solar power a zero cost of generation was used. Of the generation examined above only the landfill gas unit would benefit from ROC at present, although for example the PV systems would if they were large enough or could be aggregated to a large enough size.

Any reinforcement cost was assumed to be a fixed one off cost at the start of the twenty year period modeled.

5.2 Base Case (‘High’ Generation , No Reinforcement)

Initially some base cases were examined. The ‘High’ generation scenario shown in section 3.2.1 was modelled with the following assumptions: • Electricity prices would follow the current forward curve for 4 years then flat real • All trading would occur in an orderly way i.e. there would be sufficient notice of constraints to trade one’s way out of them in a relatively liquid market. • ROC allocation scenario 1 “High Build, Low Obligation” • No network reinforcement is undertaken • Any constraint is always implemented at times of lowest demand and hence lowest loss to the generator. Given the nature of the constraints this is in fact realistic.

The Inputs are as follows:

Generator Type ROC Entitlement Running cost 1 No. Waste @ Oversland (11kV) No No 13 No. Micro CHP @ Oversland (lv) No Yes 10 No. Solar @ Oversland (lv) No No 1 No. Landfill Gas @ Woodman Hall (11kV) Yes No 103 No. Micro CHP @ Judd Road (lv) No Yes 66 No. Solar @ Judd Road (lv) No No

31 The results derived are shown below for a 20 year run with a 6.5% discount rate:

Discounted Values Total Generation Income Lost due to Constraints £1,190,085.53 ROC Income Lost due to Constraints £1,590,149.78 Cost of Reinforcements £0.00 Saving made by Reduction in Generation £30,807.13 Total Income Lost £2,749,428.19

This simple example provides some important points. For the network under consideration only one of six generating “units” qualifies for ROC, nevertheless this accounts for the most significant loss of income. It was found to be the general case that loss of ROC payments is dominant by comparison to the loss of generation earnings. This is particularly so when one considers constraints at low demand/price periods.

As noted above there are few mitigating benefits associated with not generating for the plant being modelled, only CHP has a fuel cost saving. Thus, as expected, the saving made by reduction in generation is minimal.

Under this scenario a very significant loss is made. It seems likely that distribution network reinforcement would be cost effective under most price scenarios for this generation mixture on the reference network. The estimated cost of reinforcement of this scenario to eliminate these constraints vary from £68,300 to £568,300 depending on the cost of modifying the 33kv/11kv tap changers to take reverse power flow.

It should also be noted that the assumptions for this case minimise the cost of constraints. In practice the loss would be likely to be even higher. It would be unlikely that a generator (or consolidator acting on its behalf) would be able to trade in an orderly way all the time. In a situation of disorderly trading a larger income would be lost due to constraints with exposure to cash out prices or the trading out realised in a ‘thin’ market. This would be more expensive than orderly trading. The electricity price scenario used is also favourable to minimising losses from constraints. The assumption made is that there will be a continuing period of oversupply and hence low wholesale electricity price.

The deferral of network reinforcement was also investigated. Results are shown below. Both tables show alternative deferments of reinforcements necessary to eliminate constraints. Thus the first column shows the case where all reinforcement is carried out in year 1 i.e. no deferment. The second column shows the case where reinforcement has been deferred to year 2, the third to year 6 and the forth to year 11. In the first table it is assumed that no reinforcement to allow reverse power flow is required. In the second table an additional reinforcement cost of £520,000 to replace two transformers to allow reverse power flow is included. As expected the results show that deferring network reinforcement increases loss:

Reinforcement at Beginning of Year 1 2 6 11 Generation Income Lost due to Constraints £53,761 £258,483 £479,123 ROC Income Lost due to Constraints £81,403 £356,752 £668,835 Cost of Reinforcements £48,300 £45,352 £35,253 £25,730 Saving made by Reduction in Generation £2,166 £10,000 £18,297 Total Income Lost £48,300 £178,350 £640,488 £1,155,391

Reinforcement at Beginning of Year 1 2 6 11 Generation Income Lost due to Constraints £53,761 £258,483 £479,123 ROC Income Lost due to Constraints £81,403 £356,752 £668,835 Cost of Reinforcements £568,3000 £533,615 £414,791 £302,748 Saving made by Reduction in Generation £2,166 £10,000 £18,297 Total Income Lost £568,3000 £666,613 £1,020,026 £1,432,409

For the higher reinforcement cost it can be seen from the table above that deferring is proportionally less significant.

5.3 ‘Medium’ Generation - Simulations

The Medium generation case was then investigated for various scenarios. The “low growth” projection was ignored for this investigation since this level of generation would require no reinforcement of current network infrastructure.

The objectives of these simulations were two-fold. The initial aim was to derive the level of infrastructure investment which could be justified to avoid loss of income through constraint. Further, it was aimed to establish the level of network penetration before a step level of network reinforcement became profitable.

These studies also investigated the effects of orderly and non-orderly trading i.e. whether how much notice one had of a constraint made a significant difference.

The additional generation required for Medium penetration is shown in section 3.2.2. Under this scenario the only constrained generation is that of a 1,500kW farm waste unit. With no network reinforcement this unit is constrained to 1,200kW generation for 6,750hrs/year. The total cost of network reinforcement required to alleviate the constraint entirely is £3,700.

33 Initially the system was modelled assuming no network reinforcement. Thus all constraints were in operation. The following conditions were used: • All trading would occur in an orderly way • Any constraint applies at times of lowest demand and hence lowest loss to the generator

The following input was varied: • The price of electricity as described in section 4.3f

The ROC scenario was not varied as no generator in this case qualified for a ROC. The study modelled generation constraints over a 20 year period.

‘Medium’ Generation Scenario – Price Scenario

£500,000

£400,000

£300,000

£200,000 5 Constraint 4

Loss of Income under 3 £100,000 Electricity 2 Pricing Scenario £0 1

An important point in this scenario is the extremely high loss incurred if generation is constrained. Loss of income is from direct “loss of sales” and hence has a greater variance than in the High scenario covered in the next section when there is a loss of ROC income. A network investment to eliminate constraints of between £324,095 and £454,935 (assuming orderly trading) could be justified.

Further modelling showed that with all disorderly trading (again the most extreme scenario) the cost of constraint increases significantly. In the most serious case nearly £50,000 extra is lost in this example. A figure illustrating this, using disorderly pattern 1, is shown below.

Medium Generation Scenario – Orderly/ Disorderly

£600,00 £500,00 £400,00 £300,00 £200,00 5 £100,00 3 Electricity Pricing Scenario Loss of Income Loss of under Constraint Constraint under £0 1 OrderlDisorder Electricity Trading Scenario

It would be of interest to know at what size of generator the reinforcement becomes marginal. As the size of generator is reduced the energy constrained off decreases and the number of constrained hours in the year also reduces. This is not possible to model without further power system study work. It is, however clear that under even the lowest electricity price scenario the maximum size of farm waste unit that is acceptable without reinforcement is much nearer to 1,200kW than 1,500kW.

5.4 ‘High’ Generation - Simulations

The additional generation required for High penetration is described in section 3.2.1. Under this scenario several additional units are constrained. As well as the 1,500kW farm waste unit constraints are added to the landfill unit and micro CHP and PV units. The total cost of network reinforcement is between £68,300 and £568,000 depending on what needs to be done to enable the 33kv/11kv transformers to accept reverse power flow.

Initially the system was modelled assuming no network reinforcement. Thus all constraints were in operation. The following conditions were used: • All trading would occur in an orderly way • Any constraint always occurs at times of lowest demand and hence lowest loss to the generator

The following inputs were varied: • The ROC allocation scenario as described in section 4.3g • The price of electricity as described in section 4.3f

The system was modelled over 20 years.

35 High Generation Scenario - ROCs

£3,500,000 r £3,000,000

£2,500,000

£2,000,000

£1,500,000 Constraint £1,000,000 Loss of IncomeLoss unde of £500,000 5 £0 3 Electricity Pricing 1 Scenario 2 3 1 4 5 6 7 ROC Scenario

Again an extremely high loss is incurred for any pricing scenario and for any ROC scenario if generation is constrained. The simulation suggests that an investment of at least £2,153,556 (and at most £3,230,649) would be justified if network constraints could be removed. This is again greater than the predicted cost of a maximum of £268,300 for network modification.

The significant effect of the ROC scenario assumptions is shown more clearly below with the effect of the different cases highlighted for electricity price scenario 1. It should be noted that it is only the landfill gas unit that was assumed to be entitled to ROC benefit.

High Generation Scenario

£3,000,000

£2,500,000

£2,000,000

£1,500,000

Constraint £1,000,000 Loss of Income under £500,000

£0 1 2 3 1 Electricity Pricing 4 5 6 7 Scenario ROC Scenario

In the case of disorderly electricity trading a greater cost increase is displayed than for the Medium scenario. Nevertheless the effect of disorderly trading is less significant as a proportion of total revenues in this case as ROC revenues are available. These are unaffected by orderly or disorderly trading.

High Generation – LV Reinforcement Only

Section 3.4.4 concluded with a scenario of low voltage network only reinforcement. In such a case the constrained generation is that of the 1,500kW farm waste unit and the 1,320kW landfill gas generator. The cost of network reinforcement required in this case is £23,600.

The system was modelled with only 11kV constraints in operation. Trading was modelled both as orderly and disorderly (all types). Any constraint applies at times of lowest demand and hence lowest loss to the generator. The price of electricity was varied as described in section 4.3.

No constrained generator in this case qualified for a ROC. Hence the ROC scenario was not varied. The study modelled generation constraints over a 20 year period.

A total investment of between £1,643,608 and £1,896,445 (assuming orderly trading) could be justified. Modelling showed that with all disorderly trading the justifiable investment increases to between £1,643,839 and £1,987,154. A figure illustrating this data is shown below. High Generation Scenario with Low Voltage Network Reinforcement

£2,000,000

£1,500,000 Loss of Income under £1,000,000 Constraint £500,000 5 Electricity 3 Pricing £0 Or Dis Dis 1 der Dis Scenario ord ord ly ord erl erl y 1 erl y 2 y 3

ROC Scenario

5.5 Constraints due to Lack of Frequency Response Capability

As discussed in Section 3.4.5 it may become necessary in the future to constrain generation in times of low demand (as above) but in this case to avoid the expenditure required to provide a frequency response capability.

The income lost by constraining a normalised, ROC entitled generator, 1%, 6% and 16% of the time was investigated. The generator examined was capable of providing 100MWhrs each year (approximately equivalent to an 11.5kW generator exporting at all times). The 100% figure gives the total value of generation over twenty years. The three most dissimilar electricity-pricing schemes were used (schemes one, four and five) and for each all ROC scenarios were examined. Constraints were found to result in the following loss of income over 20 years: Cost of Constraint * 1% 6% 16% 100% ROC Scenario Cost Scenario Min £689 £4,156 £11,202 £82,468 1 1 Max £1,073 £6,471 £17,422 £126,373 7 5 Each cost case is illustrated more fully by the figures below. The first figure shows the constraints on type 1 (orderly electricity pricing) for each of seven ROC scenarios. The second examines the same situation for type 4 (orderly) pricing. The final graph uses type 5 (orderly pricing). Each of the graphs uses the non-peaky pricing scenario.

38 Income Forgone Under 1%, 6%, 16% Constraint Price Scheme 1

£140,000

£120,000

£100,000

Income £80,000 Forgone £60,000

£40,000

£20,000

£0 1234567 ROC Scenario

Income Forgone Under 1%, 6%, 16% Constraint Price Scheme 4

£160,000 £140,000 £120,000 £100,000 Income £80,000 Forgone £60,000 £40,000 £20,000 £0 1234567 ROC Scenario

Income Forgone Under 1%, 6%, 16% Constraint Price Scheme 5

39 £160,000 £140,000 £120,000 £100,000 Income £80,000 Forgone £60,000 £40,000 £20,000 £0 1234567 ROC Scenario

It can again be seen that the effect of the different ROC scenarios dominates the income lost, the different basic electricity price scenarios being of less importance. Translating the results into whether it is worth fitting frequency control equipment depends on the duration for which one would not be generating as well as how much loss of generation there would actually be during this period, as well as the cost of providing a frequency control capability.

From section 3.4.5 it is reasonable to assume that one would not be able to generate for the lowest demand of say 6% of the year (making way for generation that has got a frequency response capability). The issue is probably most relevant to wind turbines and for these it is doubtful whether an average output of more than 10% of their maximum capability should be assumed for these very low demand conditions, that will be exclusively in the summer period. Occasionally output may be higher but an average figure of 10% of maximum output for these periods is probably more than would be obtained.

Thus the income lost per kW of installed plant would be 10% of the tabled amount for a 6% of the year constraint divided by 11.5 to normalise the size to 1kW.

This gives the following:

Constraint Cost/KW installed assuming 6% per year constraint Minimum Price Scenario 1, ROC Scenario 1 £36-15 Maximum Price Scenario 5, ROC Scenario 7 £56-27

This is only a first estimate of the cost above which it would be better to forgo low demand level generation in favour of frequency response capability. It is likely that much better estimates can be obtained. In addition the question as to whether response to low frequencies as well as high would be needed in which case some generation would have to be pulled back anyway. Nevertheless this illustrates that the model may be used to look at the effect of

40 various assumptions that both network operators and generation developers need to address.

41 6 ALLOCATION OF COSTS

6.1 Allocation of Reinforcement Costs

There are two elements of costs that need to be considered in this chapter, those of any reinforcement undertaken considered here, and the cost of any constraint which is considered in the next section 6.2.

The depth of connection charging i.e. who pays for any reinforcement required as a result of a (generation or demand) customer connecting or modifying their requirements has been a subject of heated debate since 1990 (and probably before on the demand side). Currently for generation connected to the transmission system connection charges are shallow i.e. they only pay for the “local” part of any work required. In addition transmission connected generation pays a Use of System charge that varies with location.

Distribution connected generation on the other hand currently pays deep connection charges i.e. it pays for all work required when it connects. It pays no use of system charges. Thus a distribution-connected generator that does not require reinforcement to be undertaken when it connects pays no distribution charges.

The structure of distribution charges is however currently under review with the expectation that from April 2005 the charges will be somewhat shallower but with generators being subject to Distribution Use of System Charges. The current tentative proposals for this “Structure of electricity distribution charges: Initial conclusions” published by The Office of Gas and Electricity Markets in June 2003, suggests: • For connections at 33kV and above shallow connection charges combined with locationally varying use of system charges • For connections at voltages below 33kV non locationally varying use of system charges and connection charges that “reflect, to some degree, the associated costs”

Whatever is actually implemented from April 2005 may vary from the above. Nevertheless it seems likely that distribution charges for generators are moving to a shallower connection basis than currently and that some sort of distribution “Use of System” charges will be levied. In addition for domestic scale generators there is a recognition that continuing to base use of system charges on units imported may in certain circumstances over reward such generation and Distribution Network Operators are invited to consider special cost reflective charges for such customers.

It is essential that whatever mechanism is developed to recover distribution network costs caused by new generation is effective. Whilst it can be argued that it is not of fundamental importance whether those costs are born initially by generation or demand, as demand will eventually pay the cost, there is a

42 recognition that there ought to be some charge differential to encourage more distributed generation in areas where it saves network investment and less in areas where it leads to more investment. It is also important not to penalise for using the distribution network through unit based charges if the distribution network is in fact not being used at times when it is most stretched.

Ideally there should also be a choice in the level of network investment so that the investment/constraint balance can be optimised. It is clearly possible for the generator to make a choice where deep connection charges apply. If, however, shallower charges apply with some of the cost of connecting a generator being recovered through a use of system charge then it is less appropriate for the generator to choose the level of reinforcement. He will not be paying for it in the direct fashion in which he does with a deep connection charging environment. Reinforcement that is paid for out of Distribution Use of System charges is best determined by the DNO.

6.2 Allocation of Constraint Costs

The obvious options for funding the cost of constraining generators from generating at times most suitable to themselves include: • The generator paying • The DNO providing some form of compensation to the generator. We will not discuss further how under this option this affects the DNO’s overall income, which would be a matter for the price control review.

Under the first option the generator has a primary interest in the degree to which it is constrained. Under the second option its level of interest varies with compensation mechanism. The more fully it is compensated for lost profit, the less interest it will take in the amount of constrained running it incurs.

6.3 Consistent Cost Allocation Models

Although it may be possible to devise coherent arrangements with different parties bearing the cost of network reinforcement and that of constraints it is much simpler for one party to optimise the balance. Thus, to the extent that a generator can choose how much reinforcement is to take place (that we suggested fits in best with a deep connection charging environment) it would be consistent for the generator to meet the cost of constraints caused by a decision not to make an investment. Where the network operator decides how much investment to make then there is an argument that it ought to bear the cost of constraints that could have been avoided by additional network investment.

The above is not to say that distribution network operators should not continue to have a liability if particular performance standards are not met. Neither is it saying that where the DNO does have a liability it should apply in all

43 circumstances i.e. it should not be expected to provide compensation for not having an infinite system.

There are two issues associated with a DNO providing compensation to generators for constraints. 1. The source of the funding for any such payments 2. Whether the generator loses a degree of choice over the arrangements

Clearly to the extent that this might be a new payment not previously made by the DNO additional funds need to be provided to meet it. There is an argument that current distribution networks are not generally such that there are significant generation constraints and that providing the DNO is funded so that it can invest sufficiently to maintain its present design standards, any constraint compensation payments could be funded from investment not made in the process of constraint/investment optimisation. To the extent that additional funding is required it should come from Use of System charges.

On first inspection DNOs having sole control over the level of reinforcement removes a degree of choice that generators currently enjoy. It is suggested that some degree of choice by the generator can be maintained through being able to choose a more or less firm connection contract. This “commercial firmness” would determine the amount of compensation, if any, to be paid to the generator if constrained. Choosing a different level of firmness would still leave the DNO to choose the optimum investment/anticipated constraint compensation balance but the higher the level of firmness the higher would be the reference level of investment (or constraint payments) against which the optimisation would start. It would be appropriate for a higher level of Use of System charges to be payable by the generator the greater the commercial firmness it required.

In summary, it is suggested that in order to optimise the balance of network investment and constraint payments the party responsible for direct funding of any network reinforcement should also meet any constraint payments. There are two recommended options which may coexist. 1. In a deep connection environment where the generator pays for all reinforcement the generator may choose the level of reinforcement and meet itself whatever level of constraints results. 2. Where there is a shallow connection arrangement the generator may choose the level of commercial firmness of the connection and will pay higher Use of System charges the greater the firmness. It will then be up to the DNO to optimise the network investment/constraint balance and make appropriate payments to generators when they are constrained.

44 7 CONCLUSIONS

A model has been developed that allows the cost of preventing generation running to be calculated and compared with the cost of various reinforcement options. Conventional power system analysis software was used to determine the constraints for each scenario.

For the scenarios studied, which were based on part of the network in Faversham, Kent, the following key conclusions can be drawn:

1. ROCs vs Price Track For the generation portfolio considered the cost of constraints was more influenced by the assumptions on ROC income than on electricity price track. This confirms that a predictable and stable income from ROCs is more important to owners of generators that can benefit from this than the “free market” price of electricity. Whilst this is generally accepted it is particularly noteworthy that at times of low demand and lowest value of electricity, the value of a ROC is the same as at peak demand times, thus making constraints for ROC entitled generators more costly than one might have predicted at times of very low electricity demand.

2. Reinforce vs Constraints For all scenarios considered where constraints were due to the distribution network it was better to reinforce the network rather than suffer the constraints. This is commented on further in 5 below.

3. Frequency Control Although the cost of providing frequency control capability at wind farms is not yet known with any certainty it has been demonstrated how the model can be applied to questions such as how much is it worth spending on such capability rather than not generating at times of low demand. Clearly if response capability becomes mandatory a developer will not have this choice.

4. Generator Size The conclusion that it is always better to reinforce can not be generalised to all situations. The scenarios being modelled envisaged constraints that lasted for a large proportion of the year with generation that with one exception had free fuel and a significantly sized generator of which had a ROC entitlement. In addition there were no fault level violations that might have resulted in the relatively expensive necessity of replacing switchgear to avoid constraints. It is thought likely that for larger generators there might normally have been more redundancy in the connection arrangements and reinforcement may be conventional purely to avoid constraints during faults or planned outages that last a few days per year. Here the economics of accepting the constraint and saving the reinforcement cost may be more favourable.

45 5. Active Network Management When costing constraints in practice the cost of managing the constraint would need to be considered. This may be fairly small if for example devices are fitted to generators that force a reduced output automatically upon detection of the local voltage being above a particular level. However the initial case that precipitates the need for full “active network management” in an area does need to be carefully assessed, not only to cost the active management facilities but also to consider the extent to which they will be utilised for other projects in the future and their cost therefore spread over several projects.

There are several cost allocation models possible. It would appear that in order to arrive at the economic solution either the generator should fund all reinforcement and pay itself for any constraint that it suffers or the DNO should fund reinforcement and compensate constrained generators. The former option is more appropriate to a deep connection charging world and the latter to a shallower one. In the latter the DNO would receive additional funding through Use of System charges and generators would have a choice over the level of such charges that they paid depending on the level of compensation they wanted if constrained.

ANNEX1 DESCRIPTION OF REFERENCE NETWORK

A1 ANNEX1 DESCRIPTION OF REFERENCE NETWORK

A1.1 Identifying a Network for the Study

The differing characteristics of DNO networks across the United Kingdom and the varying impact of the different distributed generation technologies lead to the potential for a plethora of opportunities and risks at the local network level. For the purposes of this project it was important to identify the network constraints that are most likely to manifest themselves early, in a concerted drive to implement renewable energy sources.

DNO networks can largely be divided into local areas based on “city”, “urban town”, semi-rural and rural configurations. Network capacity and resilience is closely matched to load density in most cases and this is expected to also reflect the capacity of the network to accept distributed generation to a reasonable level without constraint. In particular the more dense the existing development, the more likely there is to be a “strong” network both in terms of capacity and low source impedance to minimise both power flow and voltage fluctuation issues.

In examining the various technologies of distributed generation likely to be promoted in the next 5-15 years existing development density was also taken into consideration. In city environments with high-density existing development and new development largely restricted to re-generation areas it is considered most likely that new developments will incorporate new technology at the outset and new connections to the network will be developed with that in mind. This will also apply in major new development areas where new towns and major estates are developed with new networks.

There will also be greater opportunity in city environments to effect local network re-configuration or transfer of services between phases and circuits to defer the need for reinforcement for a greater period.

In the case of non-city areas away from major new developments the impact on existing networks is likely to be much greater. This impact is exacerbated where local networks are sourced from relatively remote grid connections such that source impedance is likely to lead to earlier onset of network constraint. Many DNO primary 33/11kV networks are based on a main primary substation in a localised urban area that also serves the surrounding rural communities with little opportunity for significant interconnection to other such networks. With increasing levels of small domestic or commercial generation occurring in random locations the opportunity for integrated development of the network is unlikely.

Thus for the purposes of this project it was determined that the most appropriate network to study would be a primary 33/11kV substation in relatively small urban area but also serving outlying areas that could match both semi-rural and rural concepts. It was also determined that it would be

A2 most beneficial for ongoing research that the area to be chosen included some parameters that potentially both encouraged most new distributed generation technologies and exhibited some of the more pertinent network issues.

A1.1.1 Faversham, Kent The Faversham area of Kent in the Seeboard DNO area was chosen for this study based on a number of key features:

1. Faversham 33/11kV s/s is served via a long dual circuit 33kV overhead line giving a relatively high source impedance

2. Faversham is on the fringe of the Thames Gateway development area and has good rail and road links that will encourage local re-development for both housing and economic growth within the confines of existing development areas

3. Demand on the primary substation is typical in terms of profile but high in terms of demand related to available capacity (11,727 customers, 19.7MW demand with 23MVA capacity)

4. The network is a traditional mix of underground cable in the urban areas and overhead in the rural areas and is adequate in terms of meeting projected demand but without significant spare capacity

5. The area is generally of flat terrain and has both good wind and sun characteristics and a mix of areas with and without mains gas

6. The lightning risk to local networks is relatively high and network automation on the 11kV network to minimise network outage is commensurately applied

Faversham comprises a sizeable urban area with several major industrial plants and a number of small commercial developments. The customer base supplied from the Judd Road substation serves to illustrate the urban opportunity for implementation of micro-CHP and limited photovoltaic (PV) technology.

The most significant village served is Boughton-Under-Blean to the east of Faversham. This is a sizeable residential development with no significant commercial activity. This village has been determined as meeting the “semi- rural” aspect of the network studies and comprises both ground mounted and pole-mounted substations. It is also an “east-west” development that will lend itself to maximising opportunity for PV installations. London Road Boughton is a key substation in the village serving the central residential area but in a location that will provide opportunity for micro-CHP, PV and limited wind technology. This area has not been concentrated on in the model as this examines the extremes - more information is given regarding the network studied in the main report.

The surrounding rural areas comprise a number of separate hamlets interspersed with individual residential properties and farms. Agriculture, salt flats and wooded areas account for most of the land with some small, localised commercial developments in some farm properties. The Oversland pole

A3 transformer serves a small rural community comprising several large properties and local community/farm cottage groups with the opportunity for limited small commercial generation as well as residential focussed technologies.

A1.1.2 Network Characteristics The Faversham Primary substation was established in the 1960s, on the eastern outskirts of the town, to meet increasing demand typical of the period. It replaced long 11kV feeders from the main Sittingbourne conurbation to the west.

Load grew steadily with development of the area but local industry was mainly related to brewery operation and traditional industries based on the local barge shipping into Faversham Creek – timber, gunpowder and aggregates. Since the early 1980s load growth has been limited largely to inherent increase in electricity consumption rather than new business. As local industry has closed re-development of sites for commercial use has occurred but with little demand change.

Development in the area outside the urban confines is strictly limited and network extension is rarely needed. The DNO focus in the area has, for a number of years, been on reliability improvement rather than reinforcement. The load profiles included in this report demonstrate this typical local network with high commercial demand during the day-time but a very low night-time load predominately based on residential and commercial heating/cooling loads (supermarkets, brewery and similar).

The urban area primarily comprises ground-mounted substations in sites of restricted size served by an underground 11kV network of relatively small cross section. 11kV feeders with limited interconnection for P2/5 compliance and a number of long teed spurs serve the outlying areas. Network automation is extensively used to effect restoration following transient faults in this high lightning risk area. 11KV overhead lines primarily comprise light construction 0.06 copper or 50mm aluminium conductor.

LV networks in the urban area are radial distributors from local substations with limited manual interconnection for P2/5 compliance. In the semi rural network of Boughton LV networks are primarily underground cables fed from a mix of ground mounted and pole-mounted substations with limited manual interconnection.

The rural areas however are virtually entirely fed from small pole-mounted transformers often in restricted sites with LV distribution effected by 0.06 copper 4 wire or 2 wire lines or single service connections with no interconnection available.

A4 A1.1.3 Voltage Control Voltage control is effected by use of an Automatic Voltage Control (AVC) system at the primary substation utilising limited Line Drop Compensation (LDC) control. All network distribution transformers are fixed tap with graded settings down the length of the longer feeders to maintain voltage within limits.

A1.1.4 Network Requirements – Asset Condition and Load Growth With little development in the area the network is largely static and this is likely to remain the position due to the protected status given to both the urban and rural areas under Local Authority Development Plans. The network is adequate for known load growth requirements through to 2020 excepting the possibility of one sizeable housing/economic development area near the primary substation that could necessitate primary reinforcement by interconnection at 11kV to Whitstable primary substation.

In the rural areas asset condition and demand requirements indicate little need to carry out any major works on the networks in the same period except for wood pole replacement.

A1.1.5 Reinforcement Options – Increasing Distributed Generation Any sizeable CHP or similar installation is likely to have to be connected by direct connection back to the primary substation by cable circuits. Such an installation could provide the “backbone” for limited other distributed generation connection but this is limited by the inability of the primary transformers of accepting reverse power. This is very important as one scenario studied has a 692kw export (based on the feeders modelled) at minimum demand. To allow this the primary transformers/tap changers would need to be modified to accept reverse power. Depending on the precise type of tap changer, employed this may involve replacement of diverter resistors, changes to the tap changer sequencing mechanism or replacement of the entire transformer. Costs may vary from £10k for diverter resistor uprating to £260k for complete transformer replacement. A detailed assessment of what would be required on the Faversham 33kv/11kv transformers was not undertaken.

A key aspect of future reinforcement is likely to relate to LV or small HV distributed generation connection in the rural or semi-rural areas. With the introduction of the Electricity Safety, Quality and Continuity (ESQC) regulations providing the end user with the right to connect up to 16A per phase of distributed generation and inform the DNO on the day of commissioning, network management on the LV networks and local distribution transformers will become complex.

For initial connections where a 3-phase network is available at LV, reconnection of service phases to LV lines will enable balancing to a limited extent. The next option will be to profile local load by on-site measurement to determine if the voltage tapping of the local transformer can be adjusted to still maintain statutory limits at all times. With more general increases across the

A5 primary substation the installation of a capacitor/reactor combination at the primary substation may become necessary at an approximate cost of £80,000.

However, as the studies in this report demonstrate, local HV and LV reinforcement beyond these simple solutions is likely to become necessary in a piecemeal fashion as levels of uptake increase. One solution suggested is the use of reactors at local transformation points, however with restricted space available at both ground-mounted and some pole-mounted sites this may not be a preferred option. Replacement of local distribution transformers with ones with on-board AVC systems and on-load tap changers may be required in addition to installation of higher capacity 11kV and LV circuits.

In each of these options there is a clear requirement for potential substantial investment being driven by small increases in distributed generation that “tip the balance”.

A1.2 Current Constraints on Reference Network

A1.2.1 Network Design The Faversham reference network exhibits typical non-urban characteristics in that it provides an ‘adequate’ supply of electricity within the parameters of both statutory and License requirement but with potential issues when viewed in light of a vision of increasing Distributed Generation.

The network complies with the requirements for security of supply as defined in Engineering Recommendation P2/5. Statutory voltage limits are maintained by intelligent use of the primary site AVC/LDC (Automatic Voltage Control/ Line Drop Compensation) systems and graded tapping of remote distribution transformers. The DNO has an opportunity, when required, to provide a capacitor/ reactor system at the primary substation to aid voltage stability.

The key DNO constraints in relation to normal system operation revolve around meeting regulatory requirements and incentives for supply availability and reliability – quality of supply. To this end, and based on the predominance of the use of overhead circuits at both 33kV and 11kV, a key issue is the intelligent use of both automated and remote controlled switchgear on these circuits to maximise availability and minimise supply losses to below 3 minutes where possible. Alternate circuits are utilised for temporary restoration in most cases.

Typically, with little substantial development in the area envisaged, there is unlikely to be a clear incentive for costly major reinforcement, by the DNO, of the source supplies at 33kV. The most cost effective solution for reinforcement will be by limited switchable 11kV interconnection between this network and those of adjacent primary substation networks to provide mutual system support for abnormal situations. This option is, within the parameters of known Local Authority development plans projected to 2020, likely to preclude any other major reinforcement.

A6 Thus DNO driven network development is unlikely to lead to enhanced generation connection capability without new incentives.

A1.2.2 Asset Condition and Selection The nature of the local network fits with the current and projected land use. There is little or no incentive for the DNO to do more than ‘maintain’ the networks by judicious and timely asset replacement on a piecemeal ‘as- required’ basis. Indeed most asset replacement decisions will currently be married more with improvement of quality of supply than with reinforcement. Thus selected network re-configuration (simplification), undergrounding or use of insulated line conductors will predominate in these decisions. There may sometimes be opportunities to upgrade the lines to ones of a higher rating/lower impedance if they are being replaced for one of the above reasons. However there is no current incentive for the DNO to actively work to alleviate future constraints at the time of minimum additional cost – when asset replacement is effected.

A key limiting factor in the system studies is the constraint by virtue of the capability of local distribution transformers. Clearly there is a need for DNOs and the Regulatory bodies to consider the revision of specification for distribution transformers to be used for replacement purposes as required and particularly in rural applications.

In terms of ‘re-engineering’ the network to accommodate distributed generation a substantial benefit could be achieved in the longer term by the normal replacement of such units being effected with higher capacity and lower impedance types at a marginal cost increase – but also leading to small reductions in system losses. This is a matter for Regulatory discussion in terms of capital allowance to reduce predicted constraints.

A1.2.3 Network Opportunities through Distributed Generation The random connection of small distributed generation into this type of network is unlikely to provide any discrete benefit to the DNO network useable in terms of network operation or investment deferment. In the main the benefits will accrue in terms of overall system loss per annum

One opportunity that does exist relates to the potential for constraining on of larger generation units with reliable and continuous energy source to meet system peaks or abnormalities. This is a matter for commercial negotiation as covered before under other projects within the DTI framework. The landfill gas and farm waste units considered would potentially meet these criteria.

A1.2.4 Network Risks/ Constraints The key constraints in the existing network are thus related to voltage control and quality of supply. Without active network management and in the absence of any real time distributed generation output information, the network operates blind to the impact of that generation. The impact is that on loss of

A7 supply on either 11kV feeders or one of the source 33kV feeders the amount of local generation source loss is indeterminate and the supply restoration or voltage control strategy to be employed in system recovery lacks full information of the network requirements.

This is a key issue as distributed generation increases prior to the application of a clear active network management policy.

A key constraint to be considered as distributed generation increases will be the capability of both normal and abnormal feeding arrangements to accommodate the export capacity whilst maintaining statutory limits. Thus whilst a generator may apparently operate unconstrained under normal feeding arrangements the automatic re-connection of circuits to alternate sources may require an immediate constraint to be applied – by deferral of permission to re connect the generation post supply restoration.

Whilst it has been noted that potential ‘responsibility’ for investment decisions may vary with depth of connection charging this infrastructure impact on alternate connections does in some cases already lead to constraint of generation connection regardless of those concepts.

The complexity of generation data requirements for active network management under the multitude of different network configurations possible is a significant issue and potential risk to network operation.

A1.2.5 Safety The issues for national generation availability and resilience are clear on a UK basis. The need for ‘ride-through’ capability of distributed generation is recognised but must be considered against the risks of distributed generation remaining connected to islanded network sections without a system earth and with the potential for operation outside both voltage and frequency limits. These constitute potential safety issues that must be addressed by constraint or costly (relative to the power connection cost) control systems between the DNO network management systems and the generation connection point (see Report Ref: K/EL/00281/00/00 Micro-generation Network Connection – Renewables).

A1.2.6 Load Profile A key aspect of operating this typical network is the load profile related to the lack of reverse power capability (and voltage control range) of the primary substation transformers. Faversham exhibits a typical demand variation from 7.5MVA minimum to 20.5MVA maximum.

One significant issue is that a local greenhouse intensive agricultural development in the area already has a 9MW distributed generation CHP capability. However this was connected to the neighbouring Whitstable primary network by 2 long 11kV circuits due to its 24 hour operation - which the Faversham network load could not accommodate outside the working day. Thus this represents an existing constraint on the reference network in that the

A8 cost of connection to Whitstable was substantially lower than the cost of transformer replacement and enhancement of voltage control systems that would be required at Faversham.

ANNEX 2 TECHNICAL MODEL RESULTS

A10 ANNEX 2 TECHNICAL MODEL RESULTS

A2.1 Summary of Scenarios The scenarios that have been analysed with no reinforcements are: 1. The present situation 2. A High generation penetration level 3. A Medium generation penetration level 4. A Low generation penetration level (not reproduced here as no problems)

Although the last three may be thought of as corresponding to an “average” situation for 2005, 2010 and 2015 it is perfectly credible that in parts of the network the latter two penetrations are reached much earlier. As also already mentioned because the effect of phase imbalance has not been modelled there may be problems at lower penetration levels than Medium if phase balancing can not be achieved.

A2.2 Preliminary Studies Before studying the high growth scenario the existing network situation was analysed as a check using the network described in the main report. A summary of the results is tabulated below.

Summary Table of Present Network State: Summary of the current operating conditions for both maximum and minimum demand cases:

Main supply LV at Judd LV at London LV at LV at 33/11kV Road Rd Boughton Woodman Oversland substation Hall ‘0080450’ Net Demand (ADMD)kW, 8,109 130 80 87 31 kVAr 100.27 2.03 3.796 .15 1.07 Net Demand (Min) kW, 2081 34 21 23 8.17 kVAr 6.55 0.13 0.24 0.14 0.07 Max. Voltage in PU at 1 1.052 1.047 1.047 1.048 min Load Min. Voltage in PU at 0.950119 at 0.996 at 0.9916 at 0.9867 at 1.0004 at Maximum Load ‘39116641’ JUD-LV7 LRB-LV6 WH-LV3 OVL-LV14 3-phase RMS fault level 6.99 11.939 2.536 4.934 1.28 at maximum Loading in kA 3-phase RMS fault level 6.88 12.174 2.638 5.122 1.334 at minimum Loading in kA Line to ground RMS fault 8.148 0 0 0 0 level at maximum loading in KA Overloaded circuits None None None None None

All conditions can be seen to be satisfactory. It is however worth noting that the maximum voltages at minimum load at low voltage are about 5% above

A11 nominal, whereas the minimum voltages at maximum load at low voltage are below nominal. Whilst this is well within the statutory limits of between 0.94PU and 1.1PU at low voltage and between 0.94PU and 1.06PU at high voltages below 132kv. It demonstrates that a major proportion of the allowable range of conditions within the network is being utilised and there is therefore not a lot of headroom available to accommodate new generation.

A2.3 High Growth Scenario with no Network Reinforcement

Generation Selection and Results The potentially most onerous condition was assumed to be 0700 on a summer morning when all of the above generation was assumed to be running with the exception of the PV which was assumed to be at 40% of its maximum output. Clearly it could be higher but in this it is possible that less of the heat led micro CHP units (operating to make hot water only in the summer) would be generating at any one time to compensate for this.

A summary of the results is tabulated below.

Network Section Main supply LV at JUDD LV at London LV at LV at 33/11kV Road Rd Boughton Woodman Oversland substation Hall ‘0080450’ Net Demand (690) kW, 40kW 21kW 23 kW 12kW (generation) kW, 152kVAr 13kVAr .24kVAr .14kVAr 30kVAr kVAr Net Distributed 2700kW 225kW 32kW Generation kW, kVAr Max. Voltage in 1.053 1.17 at JUD- 1.0914 1.0944 1.12 PU lv7 3-phase RMS fault 7.26kA 12.18kA 2.73kA 5.32kA 1.41kA level at minimum at busbar 21.2kA 4.73kA 9.03kA 2.39kA Loading in kA ‘0080450’ Asymmetrical 12.99kA RMS kA Line to ground 8.36 0 0 0 0 RMS fault level at 15.01 min Loading in kA Initial Asymmetrical values Over loaded None Yes None None None Circuits

It can be seen that there are some overloads in the low voltage network fed from Judd Road as well as unacceptably high voltages there and at Oversland. In addition there is reverse power flow (based on the feeders modelled) through the 33kV/11kV transformers at Faversham and its tap changers are not suitable for this. The condition is therefore unacceptable indicating that for this scenario, credible within the next 10 years or so for parts of a typical network, there will have to be either reinforcement or some of the distributed generation will have to be constrained.

A12 The remainder of the technical modelling looks at some other scenarios, and quantifies the reinforcement or constraining of generation required.

A2.4 Medium Generation Scenario

Condition Studied It was established that the critical condition was at 0630 on a summer morning. It was assumed that the PV generators were operating at 38% of their maximum output.

Results of Medium Scenario without Reinforcement The results of this scenario are tabulated below:

Network Section Main supply LV at LV at LV at LV at 33/11kV Judd London Woodman Oversland substation Road Rd Hall ‘0080450’ Boughton Net Demand (generation) kW, 598kW 34kW 21kW 23kW 12kW kVAr 0kVAr 0 0.24kVAr 0.14kVAr .13kVAr Net Distributed Generation kW, 1500kW 32kW kVAr Max. Voltage in PU at Min Load 1.013 1.05 1.061 1.0648 1.1061

3-phase RMS fault level at Min 7.1 12.17 2.668 5.183 1.39 Loading in kA Line to ground RMS fault level 8.36 0 0 0 0 at Min Loading in kA Over loaded Circuits None None None None None

It can be seen that the maximum voltage in the Oversland network is more than 10% above nominal and therefore unsatisfactory.

A2.5 Time Analysis of Medium Generation Scenario

For the case without reinforcement, repeated studies were undertaken with increased demands and appropriate patterns of generation until no system voltage, current or other limits (constraints) were violated. It was confirmed that there were no constraints at any higher demand levels than this i.e. that all constraints were at a particular demand level or less. In other words all constraints were at a particular level of demand and all demand levels lower than this. The resulting constraints for the Medium generation level and no reinforcement are summarised below.

Network Main supply LV at LV at LV at LV at Oversland Section 33/11kV substation JUDD London Woodman ‘0080450’ Road Rd Hall Boughton Growth 1500 kW farm waste N/A N/A N/A 13 micro CHP, 1 kW Scenario unit Units Medium at 391126TP 28.47 MWhr/yr + penetration available 8500 hr/yr 10 PV 5 kW

A13 Total available = 12750 MWhr/yr Units(2555 hr/year) Distributed =127.75 MWhr/year generation Total 156.22 MWhr/yr MWhr/year Growth 1500 kW farm waste N/A N/A N/A 13 micro CHP, 1 kW Scenario unit Units Medium at 391126TP 28.47 MWhr/yr penetration available 1750 10 PV 5 kW Allowable hr/year at full load Units(2555 hr/year) Distributed + 1200 (capped) =127.75 MWhr/year Generation output for 6750 Total 156.22 MWhr/yr MWhr/year hrs/year = 10725 MWhr/yr Potential 2025 MWhr/yr N/A N/A N/A None Distributed generation energy not permitted to the network in MWhr/year Medium penetration (no reinforcements)

It can be seen that the farm waste digester is constrained down from 1,500KW to 1,200KW for a large portion of the year, resulting in a potential loss of over 2GWh. There is no need to constrain any of the LV connected generation although as discussed above if it is not possible to balance the phase loadings sufficiently this might no longer be the case.

A2.6 Results of Medium Scenario with Full Reinforcement

With the ‘Full reinforcement’ described in the main report the following results from the worst case load flow etc. studies were obtained.

Network Section Main supply LV at JUDD LV at London LV at LV at 33/11kV Road Rd Boughton Woodman Oversland substation Hall ‘0080450’ Net Demand 598 kW 34kW 21kW 23kW 12kW (generation) kW, 0 0.13kVAr 0.24kVAr 0.14kVAr 30kVAr kVAr Net Distributed 1500kW 32kW Generation kW, kVAr Max. Voltage in 1.038 1.0518 1.0648 1.0646 1.0742 PU at min Load 3-phase RMS 7.36kA at busbar 12.19 2.668 5.183 1.39 fault level at ‘0080450’ minimum Loading in kA Line to ground 8.36kA at busbar 0 0 0 0 RMS fault level at ‘0080450’ min Loading in kA Over loaded None None None None None Circuits

A14 It can be seen that in particular the voltage at Oversland is satisfactory (though would not be if at some time in the future the upper permissible voltage limit was reduced to 230 volts +6%). There are thus no generation constraints with the reinforcement.

A2.7 Time Analysis of High Generation Scenario

As for the Medium penetration level repeated runs were done until a point was reached where no limits were breached. This resulted in the following limitations for a scenario with no network reinforcement:

A15

Network LV at LV at 11kV network LV at JUDD Section London Rd Woodman LV at Oversland ‘0080450’ Road Boughton Hall Growth 1500kW Unit farm 103 micro CHP, N/A N/A 13 micro CHP Scenario High waste 1 kW units 1kW Units penetration at 391126TP 225.57 28.47 MWhr/yr+ Total available available 8500 hr/yr MWhr/yr + 10 PV, 5kW Distributed = 12750 MWhr/yr + 66 PV 5kW units(eq2555 generation 1320kW landfill (eq.2555 hr/yr) hr/year) =127.75 MWhr/year unit at 391164TP 843.15 MWhr/year available 7500 hr/yr MWhr/yr = 9900 MWhr/yr Total = 1068.72 Total = 156.22 Total = 22650 MWhr/yr MWhr/yr MWhr/yr Growth 1500 kW Unit farm 52 micro CHP, 13 micro CHP, Scenario High waste 1 kW units = 1kW Units penetration at 391126TP at max 117.26 28.47 MWhr/yr+ Allowable for MWhr/yr +54 10 PV 5kW Distributed 1750 hr/year + PV, 5kW units units(eq2555 Generation capped to (eq.2555 hr/yr) hr/year) =127.75 MWhr/year 800kW for 6750 689.85 MWhr/yr hr/yr MWhr/yr = 8025 MWhr/year Total = 807.11 Total = 156.22 + MWhr/yr MWhr/yr 1320kW landfill unit at 391164TP for 1750 hr/yr + capped to 1000 kW for 5750 hrs/yr = 8060 MWhr/year Total = 16085 MWhr/yr Potential 6556 MWhr/yr 261.61 None Distributed MWhr/yr generation energy not permitted to the network in MWhr/year High penetration (no reinforcements)

At this level of penetration with no reinforcement it would be necessary to constrain a considerable amount of low voltage connected generation at Judd Road and the 11kV connected generation.

A2.8 Results of High Scenario with Full Reinforcement

With “full” reinforcement i.e. transformer replacement (or theoretically the addition of shunt reactors) and reinforcement of some sections of low voltage cable in the Judd Road network, as above, the conditions observed under the most onerous conditions are tabulated below:

A16

Network Section Main supply LV at Judd LV at LV at LV at 33/11kV Road London Rd Woodman Oversland substation Boughton Hall ‘0080450’ Net Demand (generation) kW, (694)kW 40kW, 21kW, 23kW, 12kW, kVAr 613kVAr 15kVAr .24kVAr .14kVAr 30kVAr Net Distributed Generation 2700 225 32 kW, kVAr Max. Voltage in PU 1.051 1.078 at 1.09 1.062 1.083 busbar ‘JUD- LV7’ 3-phase RMS fault level at 7.58kA 12.22kA 2.73kA 5.32kA 1.41kA minimum Loading in kA at busbar 20.68kA 4.73kA 9.03kA 2.39kA Asymmetrical RMS kA ‘0080450’ 12.99kA Line to ground RMS fault level 8.36kA 0 0 0 0 at min Loading in kA 15.01kA Initial Asymmetrical values Over loaded Circuits None None None None None

It can be seen that no limits are breached. This reinforcement option leads to no generation constraints.

A2.9 Time Analysis of High Scenario with ‘LV Cable only’ Reinforcement

As was discussed in the main report, it was decided also to examine for the High Generation case, the option of carrying out all the low voltage cable reinforcement at Judd Road but no other reinforcements. It is marginal whether for the generation that can run under these conditions it is necessary to have tap changers on the 33kV/11kV transformers that can accept reverse power flow. It was deliberately decided for this scenario to try to avoid constraining any low voltage connected generation. The maximum generation that could be allowed under these conditions is as shown below:

A17

Network Main supply 33/11kV LV at JUDD Road LV at LV at LV at Oversland Section substation ‘0080450’ London Wood Rd man Boughto Hall n Growth 1500kW Unit farm 103 micro CHP, N/A N/A 13 micro CHP 1kW Scenario waste 1kW units Units High at 391126TP 225.57 MWhr/yr + 28.47 MWhr/yr+ penetration available 8500 hr/yr 66 PV 5kW 10 PV, 5kW Total = 12750 MWhr/yr + (eq.2555 hr/yr) units(eq2555 available 1320kW landfill unit at 843.15 MWhr/yr hr/year) =127.75 Distributed 391164TP Total = 1068.72 MWhr/year generation available 7500 hr/yr MWhr/yr MWhr/year = 9900 MWhr/yr Total = 156.22 Total = 22650 MWhr/yr MWhr/yr Growth 1500kW Unit farm 103 micro CHP, 13 micro CHP, 1kW Scenario waste 1kW units Units High at 391126TP at max for 225.57 MWhr/yr + 28.47 MWhr/yr+ penetration 1750 hr/year + capped 66 PV 5kW 10 PV 5kW Constrained to (eq.2555 hr/yr) units(eq2555 Distributed 1200kW for 6750 hr/yr 843.15 MWhr/yr hr/year) =127.75 Generation = 10725MWhr/year + Total = 1068.72 MWhr/yr MWhr/year 1320 kW landfill unit at MWhr/yr 391164TP for 1750 hr/yr Total = 156.22 + capped to 1000 kW MWhr/yr for 5750 hrs/yr = 8060 MWhr/year Total = 18785 MWhr/yr Potential 3865 MWhr/yr None None Distributed generation energy not permitted to the network in MWhr/year High penetration

It can be seen that compared to the “full reinforcement” scenario the total energy constrained from being produced is almost halved. One explanation for this is that, with the LV cable reinforcement, transformer taps can be lowered without the voltage becoming too low under maximum demand conditions thus relieving the voltage constraint to a significant extent as well as the more obvious effect of eliminating the low voltage overloading.

A18 A2.10 ‘Summary of Constraints’ Table Present Low Medium High No Reinforcement - - 2,025 MWhr/yr on 6,556 MWhr/yr on 11kV network 11kV network

261.61 MWhr/yr at LV Judd Road ‘LV Reinforcement’ - - - 3,865 MWhr/yr on (LV reinforcement 11kV network only)

‘Full Reinforcement’ - - - No Constraints (Transformer Replacement & LV Cable replacement)

A19 A2.11 Full Constraints Results

Network Section LV LV at at London 11 kV network LV at JUDD Wo Rd LV at Oversland ‘0080450’ Road odm Bought an on Hall Low Generation Scenario 750 kW Unit farm waste None None Non None Total available Embedded at 391126TP available e generation 8500 hr/yr MWhr/year = 6375 MWhr/yr Low Generation Scenario 6375 MWhr/yr None None Non None Constrained Embedded e Generation MWhr/year Potential Embedded generation None N/A N/A N/A N/A energy not permitted to the network in MWhr/year, (no reinforcements) Medium Growth 1,500 kW farm waste N/A N/A N/A 13 micro CHP, 1 kW Scenario unit Units Total available Embedded at 391126TP available 28.47 MWhr/yr + generation 8500 hr/yr = 12750 10 PV 5 kW MWhr/year MWhr/yr Units(2555 hr/year) =127.75 MWhr/year Total 156.22 MWhr/yr Medium Growth 1,500 kW farm waste N/A N/A N/A 13 micro CHP, 1 kW Scenario unit Units Constrained Embedded at 391126TP available 28.47 MWhr/yr Generation 1750 hr/year at full load 10 PV 5 kW MWhr/year + 1200 (capped) output Units(2555 hr/year) for 6750 hrs/year =127.75 MWhr/year = 10725 MWhr/yr Total 156.22 MWhr/yr Potential Embedded generation 2025 MWhr/yr N/A N/A N/A None energy not permitted to the network in MWhr/year, (no reinforcements) High Growth Scenario 1500 kW Unit farm waste 103 micro CHP, N/A N/A 13 micro CHP 1 kW Total available Embedded at 391126TP available 1 kW units Units generation 8500 hr/yr = 12750 225.57 MWhr/yr 28.47 MWhr/yr+ MWhr/year MWhr/yr + 66 PV 5 kW 10 PV, 5 kW + 1320 kW landfill unit at (eq.2555 hr/yr) units(eq2555 391164TP available 7500 843.15 MWhr/yr hr/year) =127.75 hr/yr = 9900 MWhr/yr Total = 1068.72 MWhr/year MWhr/yr Total = 156.22 Total = 22650 MWhr/yr MWhr/yr High Growth Scenario 1,500 kW Unit farm 52 micro CHP, 1 13 micro CHP, 1 kW Constrained Embedded waste kW units = Units Generation at 391126TP at max for 117.26 28.47 MWhr/yr+ MWhr/year 1750 hr/year + capped to MWhr/yr +54 10 PV 5 kW 800 kW for 6750 hr/yr PV, 5 kW units units(eq2555 = 8025 MWhr/year (eq.2555 hr/yr) hr/year) =127.75 + 1,320 kW landfill unit at 689.85 MWhr/yr MWhr/yr 391164TP for 1750 hr/yr Total = 807.11 + capped to 1000 kW for MWhr/yr Total = 156.22 5750 hrs/yr = 8060 MWhr/yr MWhr/year Total = 16085 MWhr/yr Potential Embedded generation 6556 MWhr/yr 261.61 MWhr/yr None energy not permitted to the network in MWhr/year, (no reinforcements)

A20 High Growth 1,500 kW Unit farm 103 micro CHP, 13 micro CHP, 1 kW Scenario waste 1 kW units Units Constrained Embedded at 391126TP at max for 225.57 MWhr/yr 28.47 MWhr/yr+ Generation 1750 hr/year + capped to + 10 PV 5 kW MWhr/year 1200 kW for 6750 hr/yr = 66 PV 5 kW units(eq2555 (LV Cable Reinforcement only) 10725MWhr/year (eq.2555 hr/yr) hr/year) =127.75 + 1,320 kW landfill unit at 843.15 MWhr/yr MWhr/yr 391164TP for 1750 hr/yr Total = 1068.72 + capped to 1000 kW for MWhr/yr Total = 156.22 5750 hrs/yr = 8060 MWhr/yr MWhr/year Total = 16085 MWhr/yr Potential Embedded generation 3865 MWhr/yr None None energy not permitted to the network in MWhr/year, LV Cable Reinforcement only

A21 ANNEX 3 DISTRIBUTED GENERATION GROWTH SCENARIOS

A22 ANNEX 3 DISTRIBUTED GENERATION GROWTH SCENARIOS

A3.1 South East Regional Study

Three growth scenarios have been chosen based on the findings of the Regional study for the South East, and Seeboard’s own internal data.

The regional study for the South East “Development of a Renewable Energy Assessment and Targets for the South East”, Government Office for the South East GOSE/RST/SD1/2000, puts forward a target of 6.6% from renewables by 2010 rising to 10% by 2015. They also propose a ‘low growth’ projection for 2010 which equates to 3.3%.

A3.2 Derived Seeboard Figures

The baseline total electricity generation within the Seeboard area is 6,310MW from the South East Regional Study. This corresponds to: • 208MW for 3.3% (this is taken as the 2005 target for the purposes of this report) • 416MW for 6.6% (2010) • 631MW for 10% (2015)

Total existing renewables capacity is stated as 73MW for the South East Region as a whole, with 17MW to be allowed for electricity displaced by active solar heating (thermal water heating). No breakdown is provided for the Seeboard area alone, so it has been assumed that 50% of this is within the Seeboard area.

Thus the projected installed capacity for the Seeboard area for ‘Renewables’ excluding “mains” gas fired CHP can be summarised as:

Distributed Existing 3.3% (2005) 6.6% (2010) 10% (2015) Generation Installed 36.5MW 199.5MW 407.5MW 622.5MW Capacity

This is shown in the table overpage.

This capacity has been allocated as different types of generation along with the typical sizes (maximum output) of the generating plant shown in MW. This is shown in the table overpage. The typical number of schemes that this would correspond to is shown in brackets after the capacity figure. Large scale CHP from mains gas is excluded from the table because it does not qualify for the % from renewables, and has plant sizes above that which we are interested in for the model.

A23 MW Installed Capacity/ GWh/yr Exported Units

Distributed Typica Assu Existing 3.3% 6.6% 10% Generation l Size med (MW/ (MW/ (MW/ (MW/ Capacity (MW) Load GWh/yr) GWh/yr) GWh/yr) GWh/yr) (from Factor (2002) (2005 ) (2010) (2015) ‘renewables’) (h/yr)

Landfill Gas 1- 7,500 26 MW 47 MW 55 MW 83 MW 2MW h/yr 195 GWh/yr 355 GWh/yr 414 GWh/yr 624 GWh/yr 17Units 32Units 37Units 55Units

Sewerage 0.5M 7,500 1.75 MW 8 MW 9 MW 14 MW W h/yr 13 GWh/yr 57 GWh/yr 69 GWh/yr 104 GWh/yr 3Units 15Units 18Units 28Units

Biomass 1-2or 7,500 9 MW 81 MW 121 MW Combustion 12MW h/yr 71 GWh/yr 604 GWh/yr 910 GWh/yr 1 Unit 10 Units 15 Units

Waste 2- 7,500 1MW 1MW 2MW Combustion 3MW h/yr 7 GWh/yr 9 GWh/yr 13 GWh/yr 1Unit 1Unit 1Unit

Municipal & 8- 7,500 7.5MW 130MW 250MW 376MW Industrial 10MW h/yr 56 GWh/yr 973 GWh/yr 1,872 2,821 Waste 1Unit 14Units GWh/yr GWh/yr 28Units 42Units

Farm Waste 0.5- 8,500 - - 1MW 2MW Digestion 1MW h/yr 9 GWh/yr 13 GWh/yr 1Unit 2Units

Wind 50kW- 2900 - - - - 2MW h/yr

PV Solar 5kW 800 0.05MW 0.5MW 2.3MW 3.46MW h/yr 0.3 GWh/yr 1 GWh/yr 2 GWh/yr 3 GWh/yr 10Units 101Units 459Units 692Units

Micro CHP 1kW 1000 - 3.92MW 7.41MW 10.76MW h/yr 4 GWh/yr 7 GWh/yr 11 GWh/yr 3,919Units 7,142Units 10,764Units

Mini Hydro 100kW - - - -

TOTAL 36.5MW 199.5MW 407.5MW 622.5MW 264GWh/yr 1,484GWh/yr 3,034 4,499GWh/y GWh/yr r

Note: Large Scale CHP from ‘mains’ gas is not included as it does not contribute to percentage from renewables, and is also typically a larger plant size than we are interested in for this study.

A24 A3.3 Generation for Faversham Network

In order to be used in the reference model, it should be noted that small non- conventional distributed generation growth will depend to large extent on the nature of the area and customers. It may vary for urban, semi-rural and rural areas.

The Seeboard area has approximately 2.2M customers. Of these, about 50% have gas-fired central heating (with this percentage varying in urban, semi-rural and rural areas). Assuming that the average life of a boiler is 20 years, 55,000 boilers are replaced annually. If the government provides incentives for micro- CHP in terms of boiler price discounts, the growth of micro-CHP follows differing trends – e.g. 5% per annum, 10% per annum or non-linear scenarios (a range of curves). Considering the number of customers on each of the substations under review we may derive the likely take up per annum over 10- 15 years on those networks as a proportion of the total.

Judd Road it is likely to be nearly all gas, say 50-60% for Woodmans Hall and the other Boughton s/s and say 0-50% (depending on whether there is gas available) for Oversland or similar rural s/s.

Similar scenarios can be projected for micro-wind which is conversely likely at Oversland and decreasing to virtually none in the urban areas.

PV will be more likely in the rural areas but has opportunity in all areas. Such generation is probably more likely in rural areas when one considers physical housing orientation – urban areas are laid out on grids with little reference to sun aspects.

The levels of generation chosen to represent the scenarios for the ‘Test’ model are tabulated in the main body of the report in section 3.2.

A25

ANNEX 4 PRICE TRACKS

A26 ANNEX 4 PRICE TRACKS

This Annex shows in graphical form the basic 5 Price Tracks corrected for orderly/peaky market price by time band vs. year, giving the 10 graphs:

Average Nominal Prices

£/MWh 30

1 3 5 7 9 11 13 15 17 19 21 23 25 Year

1 Forward Curve for 4 Years then Flat Real - Continuing Over-supply £/MWh 2 Forward Curve for 4 Years Trending to Central New Entrant by 2011 £/MWh

3 Forward Curve for 4 Years Trending to High New Entrant by 2011 £/MWh 4 2% Real Annual Increase from Today £/MWh

5 As Scenario 1 but LCPD Bites and Jump to High New Entrant in 2008, thereafter incumbents maket power causes 1% Real Rise Until 2016 £/MWh

A27 1. Current forward curve for 4 years then flat real – normal

£120 £100 £80 Cost/MWhr £60 £40 £20 2021 £0 year 2012 1%

44% 2003 Highest 99% Demand % of Year

2. As Case 1 for 4 years then trending towards new entrant prices by 2011– normal

£140 £120 £100 £80 Cost/MWhr £60 2027 £40 2019 £20 2011 year £0 2003 1% 24% 84%

Highest 100% Demand % of Year

A28 3. As Case 2 but trending to a high new entrant price – normal

£180 £160 £140 £120 £100 Cost/MWhr £80 2027 £60 £40 2019 £20 2011 year £0 2003 1% 24% 84%

Highest 100% Demand % of Year

4. Two per cent a year real annual increase – normal

£180 £160 £140 £120 £100 Cost/MWhr £80 £60 2024 £40 2017 £20 2010 year £0 2003 1% 24% 84%

Highest 100% Demand % of Year

A29 5. Large Combustion Plane Directive bites and high new entrant prices by 2006, increasing thereafter at 1% real until 2016 – normal

£200 £180 £160 £140 £120 Cost/MWhr £100 £80 £60 2024 £40 2017 £20 2010 year £0 2003 1% 24% 84%

Highest 100% Demand % of Year

6. Current forward curve for 4 years then flat real – peaky

£180 £160 £140 £120 £100 Cost/MWhr £80 £60 £40 £20 2027 £0 2019 year 2011 1%

44% 2003 Highest 99% Demand % of Year

A30 7. As Case 1 for 4 years then trending towards new entrant prices by 2011– peaky

£180 £160 £140 £120 £100 Cost/MWhr £80 2027 £60 £40 2019 £20 2011 year £0 2003 1% 24% 84%

Highest 100% Demand % of Year

1. 8. As Case 2 but trending to a high new entrant price – peaky

£250

£200

£150 Cost/MWhr £100 2027 2019 £50 2011 year £0 2003 1% 24% 84%

Highest 100% Demand % of Year

A31 9. Two per cent a year real annual increase – peaky

£250

£200

£150 Cost/MWhr £100 2024 £50 2017 year 2010 £0 2003 1% 24% 84%

Highest 100% Demand % of Year 2.

10. Large Combustion Plane Directive bites and high new entrant prices by 2006, increasing thereafter at 1% real until 2016 – peaky

£300

£250

£200

Cost/MWhr £150

£100 2024 2017 £50 year 2010 £0 2003 1% 24% 84%

Highest 100% Demand % of Year

A32