Final Report

DISTRIBUTION SYSTEM CONSTRAINTS AND THEIR IMPACT ON DISTRIBUTED GENERATION Final Report CONTRACT NUMBER: DG/DTI/00005/REP URN NUMBER: 04/1114 The DTI drives our ambition of ‘prosperity for all’ by working to create the best environment for business success in the UK. We help people and companies become more productive by promoting enterprise, innovation and creativity. We champion UK business at home and abroad. We invest heavily in world-class science and technology. We protect the rights of working people and consumers. And we stand up for fair and open markets in the UK, Europe and the world. 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. © Crown Copyright 2004 May 2004 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 vi 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.

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