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Residential Demand Response in the Power System

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Residential Demand Response in the Power System RESIDENTIAL DEMAND RESPONSE IN THE POWER SYSTEM A thesis submitted to CARDIFF UNIVERSITY for the degree of DOCTOR OF PHILOSOPHY 2015 Silviu Nistor School of Engineering I Declaration This work has not been submitted in substance for any other degree or award at this or any other university or place of learning, nor is being submitted concurrently in candidature for any degree or other award. Signed ………………………………………… (candidate) Date ………………………… This thesis is being submitted in partial fulfillment of the requirements for the degree of …………………………(insert MCh, MD, MPhil, PhD etc, as appropriate) Signed ………………………………………… (candidate) Date ………………………… This thesis is the result of my own independent work/investigation, except where otherwise stated. Other sources are acknowledged by explicit references. The views expressed are my own. Signed ………………………………………… (candidate) Date ………………………… I hereby give consent for my thesis, if accepted, to be available for photocopying and for inter- library loan, and for the title and summary to be made available to outside organisations. Signed ………………………………………… (candidate) Date ………………………… II Abstract Demand response (DR) is able to contribute to the secure and efficient operation of power systems. The implications of adopting the residential DR through smart appliances (SAs) were investigated from the perspective of three actors: customer, distribution network operator, and transmission system operator. The types of SAs considered in the investigation are: washing machines, dish washers and tumble dryers. A mathematical model was developed to describe the operation of SAs including load management features: start delay and cycle interruption. The optimal scheduling of SAs considering user behaviour and multiple-rates electricity tariffs was investigated using the optimisation software CPLEX. Further, the financial benefits for SA users subscribing to multiple-rates electricity tariffs were investigated. The savings are mainly a result of the appliances’ load shifting feature and are sensitive to user settings. The savings averaged at 7% of the household annual electricity bill. For households in the United Kingdom, the SAs had a payback period of less than three years and a net present value of up to £206. Furthermore, the operation of distribution networks with different uptake rates of SAs was investigated. A simulation containing a load modelling method and a network model determines, through time series power flow analysis, the network branch loading and voltage profile. The thermal ratings and voltage limits were exceeded on the LV network due to deterioration in the temporal diversity of the appliance utilisation. A regional controller for SAs was developed which effectively limited the network peak demand and voltage drop. A framework was introduced which enabled transmission system operators to access demand response from SAs in a timeframe suitable for operating reserve. A multiple time-step simulation was developed that assessed the load reduction from a number of households as a response to a reserve instruction. The instruction was modelled as a price increase with a short notification period. It was estimated that up to half of the current operating reserve requirements of Great Britain’s power system can be obtained with 20% uptake of SAs. III Acknowledgements This thesis would not have been possible without the support of a number of individuals who have helped me throughout. To them I wish to offer my sincere gratitude. First, to my supervisors who have truly been my guides in this endeavour: Dr Jianzhong Wu, for his research ideas and general enthusiasm for distribution systems; Dr Janaka Ekanayake, for sharing his knowledge of power systems; and Dr Mahesh Sooriyabandara whose feedback always included the dimension of practicality. Special thanks to Professor Nick Jenkins, for his advice and healthy pragmatism. To my colleagues from the research group, for creating the perfect environment for sharing ideas: Mr George O’Malley for his IT knowledge, Ms Meng Cheng and Mr Lee Thomas for the discussions on the Demand Response topic. Special thanks to Mr Brian Drysdale who offered his invaluable help in proofreading this thesis. To my brother Iulian, who has encouraged me from the beginning. Finally, I wish to thank my wife Adina who has been on my side throughout this journey and with whom I eagerly anticipate the future ones. IV Table of Contents Abstract ...................................................................................................................................... III Acknowledgements .................................................................................................................... IV Table of Contents ....................................................................................................................... V List of Figures ......................................................................................................................... VIII List of Tables .............................................................................................................................. X Abbreviations ............................................................................................................................. XI 1 Introduction ......................................................................................................................... 1 1.1 Research context ........................................................................................................... 2 1.2 Current demand response practices ............................................................................... 4 1.3 Services provided by smart appliances ....................................................................... 10 1.3.1 Peak load shifting ................................................................................................ 11 1.3.2 Balancing services ............................................................................................... 13 1.3.3 Distribution network support............................................................................... 14 1.4 Modelling of smart appliances operation .................................................................... 16 1.4.1 Optimisation ........................................................................................................ 18 1.4.2 Other methods ..................................................................................................... 19 1.5 Research objectives and thesis structure ..................................................................... 21 1.6 Publications and achievements .................................................................................... 24 2 Smart Grid ready appliances ........................................................................................... 25 2.1 Introduction ................................................................................................................. 26 2.2 Load profiles ............................................................................................................... 27 2.3 Load management ....................................................................................................... 32 2.3.1 Smart timing ........................................................................................................ 32 2.3.2 Cycle interruption ................................................................................................ 33 2.4 User dependent parameters ......................................................................................... 34 2.4.1 Activation times .................................................................................................. 34 2.4.2 Maximum delay ................................................................................................... 36 2.5 Shifting algorithm ....................................................................................................... 37 2.5.1 Optimisation ........................................................................................................ 37 2.5.2 Execution of the shifting algorithm ..................................................................... 42 2.6 Model validation ......................................................................................................... 45 2.7 Overview of the simulation environment .................................................................... 48 3 Financial analysis for smart appliances users ................................................................ 50 3.1 Introduction ................................................................................................................. 51 V 3.2 Electricity tariffs .......................................................................................................... 51 3.3 Effects of parameters on household savings ............................................................... 55 3.3.1 Number of residents ............................................................................................ 56 3.3.2 Maximum delay ................................................................................................... 57 3.3.3 Cycle interruption ................................................................................................ 58 3.4 Annual savings for a group of one thousand GB households ..................................... 59 3.4.1 Electricity cost savings .......................................................................................
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