METHODOLOGIES FOR THE PARTICIPATION OF AN ELECTRIC VEHICLES AGGREGATOR IN THE ELECTRICITY MARKETS

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1 METHODOLOGIES FOR THE PARTICIPATION OF AN ELECTRIC VEHICLES AGGREGATOR IN THE ELECTRICITY MARKETS Ricardo Jorge Gomes de Sousa Beno Bessa Thesis submied o he Faculy of Engineering of Universiy of Poro in parial fulfillmen of he requiremens for he degree of Docor of Philosophy Thesis Supervisor Professor Manuel Anónio Cerqueira da Cosa Maos Full Professor a he Deparmen of Elecrical and Compuer Engineering Faculy of Engineering, Universiy of Poro April 2013

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3 As we walked along he flablock marina, I was calm on he ouside, bu hinking all he ime - Now i was o be Georgie he general, saying wha we should do and wha no o do, and Dim as his mindless greeding bulldog. Bu suddenly, I viddied ha hinking was for he gloopy ones, and ha he oomny ones use like, inspiraion and wha Bog sends. Now i was lovely music ha came ino my aid. There was a window open wih he sereo on, and I viddied righ a once wha o do. Alex, Clockwork Orange, 1971

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5 Acknowledgmens The suppor of excepional researchers, colleagues, friends and family was essenial o conclude his work. Here, I will express a public word of appreciaion and acknowledge heir role in his hesis. This hesis was supervised by Professor Manuel Maos, Full Professor a he Faculy of Engineering of he Universiy of Poro (FEUP), o who I am graeful for acceping his supervision. Professor Manuel Maos was much more han a supervisor, i was a rue professor. His guidance and advices allowed me o improve my scienific and personal compeences, which ulimaely changed my viewpoins in differen subjecs. The opporuniy o work wih Professors Peças Lopes and Vladimiro Miranda was also very rewarding a differen levels, and heir eachings and enhusiasm influenced his hesis. I am ruly graeful o Professor Cláudio Moneiro since, on an early sage of my career, rused in me o work wih him in differen research projecs. His friendship and advices were crucial o follow his pah and his hesis is also a resul of his convicion in my capaciies. My former professors from he Faculy of Economics of he Universiy of Poro, in paricular Professor João Gama, were responsible for making me hink ou-of-he-box and open o mulidisciplinary research. In 2006, when I wen o work a INESC Poro, he high qualiy of he human resources creaed he perfec condiions o evolve a he scienific level. For me, i was a luck and a pleasure o have rue scieniss as examples, such as Carlos Moreira, Luis Seca, André Madureira, Jorge Pereira and Ricardo Ferreira. They were an inspiraion o his hesis, and heir suppor a valuable help. The opporuniy o work wih João Sousa and his friendship was essenial for my inegraion a INESC Poro and imporan for improving my programming skills. Furhermore, he research work and he vision of Joel Soares and Pedro Almeida abou he elecric vehicles opic, as well as heir friendship and valuable discussions, was an imporan conribuion o his hesis. The help of Leonardo Bremermann was an essenial suppor o combine he work of he ANEMOS.plus projec wih his PhD hesis. The friendship and sense of humour during criical (and non-criical) siuaions of Bernardo Silva were very graifying during hese years. Finally, I canno forge Célia Couo, Paula Casro and Rue Ferreira since heir work made my life much more easier during he PhD period. A a personal level, I mus dedicae a few paragraphs o acknowledge a group of persons ha made his work a realiy. Firs, hanks o my parens. I is no fair o work hard during heir life in order o give a beer

6 life o heir children, and see boh leave heir home o graduae in anoher ciy. This hesis and all my research work during hese almos four years, is dedicaed o hem, for heir effor, for heir suppor and for heir love. To my siser Ana Ria, mos of he ime I was away and unavailable, bu she also played an imporan role. To my grandmoher, who I know is very proud of her grandson. I also have a very good group of friends. I canno menion all heir names here because he number of pages of his hesis would increase exponenially. I paricularly acknowledge Vanessa and Anónio Pina, Joaquim Maos, Pedro Correia and Lourenço Moura since heir friendship, heir words and advices in specific momens of my life were essenial o complee his pah. The mavericks Pedro Cosa and Tiago Azevedo were also essenial o mainain he equilibrium beween he forces. Finally, words are no enough o described he role and imporance of my beloved Ana Pino. Her suppor and love during hese years were he ligh during darkes imes, he absolue rus in my capaciies was he fuel of his work, and her words were full of music and hope. Definiely, his is also her hesis!

7 This work was suppored by Fundação para a Ciência e a Tecnologia (FCT) de Porugal, under PhD gran SFRH/BD/33738/2009 and by INESC TEC - Science and Technology.

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9 Absrac The Elecric Vehicle (EV) is one elemen ha conribues o a susainable ranspor secor since i helps reducing greenhouse gas (GHG) emissions and oil-dependency. I also esablishes a connecion beween he ranspor and elecric power secors. In order o promoe a susainable developmen, differen sakeholders from he elecric power secor are seeking an increase of Renewable Energy Sources for Elecriciy (RES-E), complemened by a smar grid infrasrucure ha enables a more acive paricipaion of he demand-side in he power sysem operaion. The EV charging, if unconrolled and during peak hours, could resul in echnical problems a he disribuion nework level (e.g., branches congesion). However, direc-conrol of he EV charging using he smar grid echnology increases he demand-side flexibiliy which miigaes he echnical problems and suppors he inegraion of RES-E (e.g., by offering reserve services). The exising elecriciy marke rules do no allow bids from small loads and, in order o decrease he communicaion requiremens beween he sysem operaors and EV, a marke agen called aggregaor can serve as an inermediary beween a group of vehicle owners, elecriciy marke, ransmission and disribuion sysem operaors. Compuaional algorihms are needed o make he smar grid archiecure feasible. Wihin his conex, his PhD hesis explores he concep of an EV aggregaor and conribues wih a se of compuaional ools ha enable is acive paricipaion in he elecriciy marke, in paricular he provision of secondary and balancing reserve services. Firsly, a framework wih opimizaion/forecasing models covering he majoriy of he elecriciy marke sessions is defined. Then, day-ahead opimizaion models, based on forecass for he marke prices and EV variables, are formulaed o deermine he bids for he elecrical energy, secondary and balancing reserve marke sessions. Operaional managemen algorihms, using informaion from he plugged-in EV and he acceped bids, are proposed o coordinae EV charging during he operaing day and comply wih he marke commimens (e.g., avoid reserve shorage). The opimizaion models are evaluaed in a es case wih synheic EV ime series and daa from he Iberian elecriciy marke. The main conribuions from his PhD hesis are: (a) day-ahead opimizaion models for elecrical energy, secondary and balancing reserve bids; (b) operaional managemen algorihms ha coordinae he EV individual charging and allow he provision of reserve wihou compromising power sysem reliabiliy; (c) esimaion of he forecas errors impac on he aggregaor s oal cos and reserve shorage magniude.

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11 Resumo O veículo elérico (VE) é um elemeno de uma solução global para o desenvolvimeno susenável do secor dos ranspores, uma vez que permie reduzir as emissões de gases de efeio de esufa e dependência do peróleo. Esabelece uma ligação com o secor elérico, no qual diferenes agenes procuram, em conjuno com o conceio de rede ineligene, aumenar a conribuição de fones de energia renovável para produção de elericidade, promovendo um desenvolvimeno susenável. A inegração de VE, com carregameno não-conrolado, pode provocar problemas écnicos na rede elérica de disribuição. No enano, o conrolo do carregameno com base numa infraesruura de comunicação bidirecional miiga problemas écnicos e auxilia a inegração de geração de base renovável. De forma a reduzir os requisios de comunicação para conrolo do carregameno, e dado que as auais regras do mercado de elericidade não permiem a paricipação individual de pequenas cargas, é inroduzido um novo agene de mercado chamado agregador de VE. Ese agene serve de inermediário enre um grupo de VE, mercado de elericidade, operadores da rede de ranspore e disribuição. Nese conexo, esa ese de douorameno explora o conceio de agregador e conribui com um conjuno de algorimos compuacionais que permiem uma paricipação aiva do agregador no mercado de elericidade, em paricular no fornecimeno de reserva secundária e de balanço. Numa primeira fase, é definida uma arquieura que inclui modelos de previsão e oimização para cada sessão do mercado. Em seguida, são formulados modelos de oimização, baseados em previsões para o dia seguine dos preços de mercado e consumo dos VE, com o objeivo de oimizar as oferas de energia elérica e reserva. São igualmene proposos algorimos operacionais para coordenar o carregameno dos VE de forma a saisfazer os compromissos do mercado elérico durane o próprio dia e com base em informação de VE esacionados para carregameno. Os modelos de oimização são esados num caso de esudo consruído com dados sinéicos do consumo de VE e dados reais do mercado Ibérico de elericidade. As principais conribuições desa ese são: (a) modelos de oimização para o dia seguine das proposas de compra de energia elérica e venda de reserva secundária e de balanço; (b) algorimos operacionais que coordenam o carregameno individual dos VE, e permiem ao agregador fornecer reserva sem compromeer a fiabilidade do sisema elérico; (c) esimação do impaco dos erros de previsão no cuso oal do agregador e na magniude das siuações com reserva não-fornecida.

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13 Conens Lis of Figures Lis of Tables Lis of Acronyms and Symbols xvi xx xxii 1 Inroducion General Conex and Moivaion Objecives of he Thesis Srucure of he Thesis Lis of Publicaions Background and Sae of he Ar Inroducion Background Power Sysem Reserves Elecriciy Markes Demand-side Acive Paricipaion Inegraion of EV ino he Power Sysem Early Sudies Recen Sudies Economic and Technical Issues of EV in he Elecriciy Marke Peak and Base Power Ancillary Services Sorage and RES-E EV Aggregaion Agen Business Models for he Aggregaor EV and Marke Rules xii

14 Conens Summary and Remarks Smar Grid and Sandardizaion Algorihms for Supporing he EV Aggregaor Business Opimizaion Algorihms wihou Nework Consrains Nework Consrained Opimizaion Algorihms Forecasing EV Variables Baery Model for Opimizaion Algorihms Final Remarks EV Aggregaor Model and Framework Archiecure Ineracion wih EV Owner and Charging Poin Manager Ineracion wih TSO and DSO Informaion Flows Economic and Physical Flows Managemen Processes Elecriciy Marke Framework and Algorihms Shor-erm Horizon Very Shor-erm Horizon Operaional Managemen Marke Selemen Final Remarks Opimizaion Models for he Day-ahead Energy Marke Inroducion Global Approach Represenaion of he EV Informaion Advanages and Limiaions Formulaion of he Opimizaion Problem Forecasing Tasks Divided Approach Represenaion of he EV Informaion Advanages and Limiaions Formulaion of he Opimizaion Problem Forecasing Tasks Operaional Managemen Algorihm Formulaion of he Opimizaion Problem Forecasing he Imbalance Uni Coss Tes Case Descripion xiii

15 Conens EV Synheic Time Series Elecriciy Marke Paricipaion in he Elecriciy Marke Forecasing Models Sampling Process for Evaluaion Comparison Beween Global and Divided Opimizaion Models Illusraive Example of he Opimizaion Models Oupu and Resuls Comparison of he Deviaions Beween Acceped Bid and Acual Charging Values Comparison of Coss from Paricipaing in he Elecriciy Marke Sensiiviy Analysis of he Global Approach Performance of he Operaional Managemen Algorihm Comparison wih Sae of he Ar Operaional Algorihms The Impac of Very Shor-erm Forecass Discussion Opimizaion Models for he Secondary Reserve Marke Inroducion Problem Descripion Paricipaion in he Elecriciy Marke Characerisics of he Secondary Reserve Day-ahead Energy and Reserve Opimizaion Operaional Managemen Algorihm EV Flee Operaing Poin and Calculaion of he Available Reserve Operaional Managemen Marke Selemen Tes Case Resuls Sampling Process Aggregaor s Viewpoin: Toal Cos TSO s Viewpoin: Reserve Shorage Differen Qualiy of he EV Variables Forecass Final Remarks Opimizaion Models for he Balancing Reserve Marke Inroducion Problem Descripion Characerisics of he Balancing Reserve Paricipaion in he Elecriciy Marke Day-Ahead Energy and Reserve Opimizaion xiv

16 Conens Inpu Variables and Forecass Formulaion of he Opimizaion Problem Operaional Managemen Algorihms Operaional Managemen for Day-Ahead Reserve Bids Operaional Managemen for Hour-Ahead Reserve Bids Marke Selemen Tes Case Resuls Sampling Process Aggregaor s Viewpoin: Toal Cos TSO s Viewpoin: Reserve Shorage Impac of he Reserve Direcion Forecas Differen Qualiy of he EV Variables Forecass Final Remarks General Conclusions and Fuure Work Conribuions and Main Findings Conribuions Main Findings Perspecives for Fuure Work Bibliography 227 A Saisical Analyses of he Tes Case Daa 251 A.1 Synheic EV Time Series A.1.1 Individual EV A.1.2 Aggregaed EV A.2 Energy and Reserve Prices B Evaluaion of he Forecas Performance 267 B.1 Aggregaed EV Variables B.2 Individual EV Variables B.2.1 Forecas Error of he Changed Forecass B.3 Marke Prices B.4 Reserve Direcion C Sae of he Ar Operaional Algorihms 277 C.1 Prioriy-based Algorihm C.2 Price-ranking-based Algorihm xv

17 Lis of Figures 1.1 Final energy savings of he European ranspor secor and forecased number of elecric vehicles Life cycle GHG emissions from vehicles shown as a funcion of he life cycle GHG inensiy of elecriciy generaion Frequency conrol scheme and acions of he ENTSO-E operaional handbook Response ime and duraion of differen reserve caegories in he USA Srucure of he elecriciy marke Illusraive example of an EV providing regulaion up and down A es on providing wo hours of secondary reserve Technical managemen and marke operaion framework for EV inegraion Package deal business model Sandards used in he EDISON projec EV aggregaor archiecure Componens of public (or semi-public) and fas charging saions for Aggregaor- EV-CPM ineracion Componens of a residenial or office charging saion Informaion flows beween aggregaor, DSO/TSO, EV and CPM Economic and physical flows beween aggregaor, DSO/TSO and EV driver Elecriciy marke framework and algorihms for he EV aggregaor EV variables: charging requiremen and availabiliy Global and divided approaches for shor-erm managemen Seasonal plos for EV availabiliy of one and 1500 EV Toal charging requiremen forecas and realized value Availabiliy forecas and realized value of one EV Diagram wih he sequence of asks for paricipaing in he elecriciy marke xvi

18 LIST OF FIGURES 4.6 Diagram wih he emporal horizons of he forecas and opimizaion models Acceped bids of he global and divided approaches for one illusraive day Acceped bids and acual charging (from he operaional algorihm) for one illusraive day MAPD of he divided approach wih forecased informaion for flees A and B MAPD of he global approach (for flees A and B) wih forecased and realized values of he EV variables as inpu DBIAS of he global approach (for flees A and B) wih forecased and realized values of he EV variables as inpu Toal cos increase beween he divided approach wih forecased and realized values used as inpu in he day-ahead opimizaion Toal cos increase beween he global approach wih forecased and realized values used as inpu in he day-ahead opimizaion Coss reducion of he divided and global approach in flee A compared o he inflexible EV load approach Coss reducion of he divided and global approach in flee B compared o he inflexible EV load approach β agains MAPD for differen aggregaion sizes and flee A β agains MAPD of differen aggregaion sizes and flee B The impac of β in he componens of he oal cos for flee A The impac of β in he componens of he oal cos for flee B Aggregaion size agains MAPD for flees A and B obained wih four differen operaional algorihms Surplus and shorage coss for flees A and B obained wih hree differen operaional algorihms Marke clearing of he secondary reserve bids Sequence of asks for paricipaing in he day-ahead energy and secondary reserve markes Secondary reserve PJM AGC regulaion signal for 6 hours Hisograms for he number of equivalen minues of he upward secondary reserve of a hydro and hermal power plans in Porugal for he year Hisograms of he secondary reserve in Porugal and PJM Auocorrelaion plos of he secondary reserve in Porugal and PJM Day-ahead forecas of he secondary reserve capaciy price One sep-ahead forecas of he upward eriary reserve price in Porugal POP, upward and downward reserve power of one EV xvii

19 LIST OF FIGURES 5.11 Oupu of he day-ahead opimizaion for one illusraive day of he es case (flee A) Oupu of he day-ahead opimizaion for one illusraive day of he es case (flee B) Oupus of he day-ahead opimizaion for energy and secondary reserve bids Increase in secondary reserve by saring he non-adjusable generaor M3 as eriary reserve Variables required o redefine he operaing poin Illusraive examples for he calculaion of he redefined operaing poin Illusraive example of he operaional managemen algorihm oupu for secondary reserve and flee A Illusraive example of he operaional managemen algorihm oupu for secondary reserve and flee B Toal cos reducion in flees A and B from selling secondary reserve Reducion in he oal cos for boh flees and wih differen ses of available informaion pcrps and picrps for upward and downward reserve direcions pcrps and picrps for upward reserve as a funcion of wo differen olerances for he arge SoC prns and pirns of upward and downward reserve in flees A and B pcrps and prns of upward and downward reserve in flees A and B for differen qualiies of charging requiremen and availabiliy forecas (wih a raio beween upward and downward reserve bids) pcrps and prns of upward and downward reserve in flees A and B for differen qualiies of charging requiremen and availabiliy forecas (wih separaed upward and downward reserve bids) Balancing reserve Marke clearing of he balancing reserve bids Sequence of asks for paricipaing in he energy and balancing reserve marke sessions Auocorrelaion diagrams of he binary variable ha indicaes if he secondary and balancing reserve was dispached in he upward direcion Illusraive examples of he day-ahead energy and balancing reserve opimizaion Illusraive example of he day-ahead and hour-ahead operaional managemen algorihms oupu for balancing reserve Reducion in he oal cos compared o opimizing only he energy bids Toal cos reducion of hree differen ses of available informaion Upward prns and pirns in flees A and B xviii

20 LIST OF FIGURES 6.10 Upward and downward prns and pirns of flees A and B, assuming ha he reserve is no fully dispached during each ime inerval prns of upward and downward balancing reserve in flees A and B for differen qualiies of he charging requiremen and availabiliy forecas A.1 Availabiliy daily paern of each EV from flee A divided by driver ype A.2 Frequency of arrivals and deparures in each ime inervals from hree EV from flee A A.3 Boxplos summarizing he average and maximum plugged-in ime of flee A A.4 Boxplos summarizing he average and maximum plugged-in ime of flee B A.5 Boxplos summarizing he average iniial and arge SoC of flee A A.6 Boxplos summarizing he average iniial and arge SoC of flee B A.7 Boxplos summarizing he average flexibiliy of each EV in flees A and B A.8 Auocorrelaion diagram of he availabiliy ime series of one EV of each ype A.9 Seasonal plo of he aggregaed variables from flee A A.10 Seasonal plo of he aggregaed variables from flee B A.11 Auocorrelaion diagram of he aggregaed variables from flee A A.12 Boxplos condiioned o he hour of he day for he marke prices of year A.13 Boxplos condiioned o he hour of he day for he marke prices of year A.14 Boxplos condiioned o he hour of he day for he marke prices of year A.15 Auocorrelaion plo of he energy and secondary reserve capaciy prices for year B.1 Boxplo wih he accuracy of he availabiliy forecas for flees A and B B.2 Boxplo wih he mmape for he charging requiremen of flees A and B B.3 Spearman correlaion and mean absolue error of he prices forecass B.4 Mean absolue error of he forecass for he eriary and secondary reserve prices in Porugal xix

21 Lis of Tables 2.1 Economic value of differen ypes of EV in he elecriciy marke Illusraive example of hree EV wih charging process conrolled by he aggregaor Illusraive example of he charging requiremen disribuion of hree EV Parameers of he runcaed Gaussian probabiliy densiy funcion Three ypes of behavior regarding EV charging Toal cos increase and deviaions obained from no including very shor-erm forecass in he operaional algorihm Secondary reserve bids from one EV plugged-in during four hours and ne elecrical energy ha resuls from he reserve provision during he firs wo hours Se of charging soluions of an EV offering upward reserve power Example of a charging soluion of an EV offering upward and downward reserve power Toal cos s componens of selemen scheme (a) for a es sample of flee B Percenage of upward and downward reserve power shorage Sandard deviaion values used in he runcaed Gaussian disribuions for he charging requiremen and availabiliy forecass Illusraive example of he upward and downward balancing reserve dispach in Porugal Downward prns and pirns from flees A and B prns of he upward and downward balancing reserve and oal cos increase wih differen forecass for he reserve direcion Toal cos s componens for one es sample wih differen forecass for he reserve direcion xx

22 LIST OF TABLES 6.5 Sandard deviaion values used in he runcaed Gaussian disribuions for he charging requiremen and availabiliy forecass A.1 Summary saisics of he average raio beween charging requiremen and baery size for all vehicles from flee A A.2 Summary saisics of he average raio beween charging requiremen and baery size for all vehicles from flee B A.3 Summary saisics of aggregaed EV variables of flee A A.4 Summary saisics of aggregaed EV variables of flee B A.5 Summary saisics of day-ahead elecrical energy price for years 2009, 2010 and 2011 in Porugal A.6 Summary saisics of upward eriary reserve price for years 2009, 2010 and 2011 in Porugal A.7 Summary saisics of downward eriary reserve price for years 2009, 2010 and 2011 in Porugal A.8 Summary saisics of secondary reserve capaciy price for years 2009, 2010 and 2011 in Porugal B.1 Forecasing performance for he EV aggregaed variables for flees A and B B.2 mmape of he aggregaed availabiliy and charging requiremen forecas for flees A and B wih 1500 EV B.3 mpbias of he aggregaed availabiliy and charging requiremen forecas for flees A and B wih 1500 EV B.4 mmape and mpbias of he modified aggregaed availabiliy and charging requiremen forecas for flee A B.5 mmape and mpbias of he modified aggregaed availabiliy and charging requiremen forecas for flee B B.6 Accuracy and Area Under he ROC Curve (AUC) of he day-ahead forecass for he balancing reserve direcion in Porugal B.7 Accuracy and Area Under he ROC Curve (AUC) of he hour-ahead forecass for he balancing reserve direcion in Porugal B.8 Accuracy of four differen basic (or heurisic) binary forecas models xxi

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