ebook img

PhD thesis_Jeanne Andersen PDF

130 Pages·2015·1.26 MB·English
by  
Save to my drive
Quick download
Download
Most books are stored in the elastic cloud where traffic is expensive. For this reason, we have a limit on daily download.

Preview PhD thesis_Jeanne Andersen

2015-10 Jeanne Andersen PhD Thesis Modelling and Optimisation of Renewable Energy Systems DEPARTMENT OF ECONOMICS AND BUSINESS AARHUS UNIVERSITY (cid:2) DENMARK M ODELLING AND OPTIMISATION OF RENEWABLE ENERGY SYSTEMS By Jeanne Andersen Supervisor: KimAllanAndersen APhDthesissubmittedtotheSchoolofBusinessandSocialSciences,AarhusUniversity,in partialfulfillmentofthePhDdegreeinEconomicsandBusiness March2015 Summary This thesis consists of three chapters, each of which constitutes a self-contained research pa- per. The three papers are all related to the modelling of optimisation problems within energy systems. Inthefirsttwopapers,welookatelectricitysystemoperationswithinthehour,wheresup- ply and demand of electricity have to be balanced. In the papers, we present two proactive models. Based on forecasted imbalances between supply and demand, the models aim at re- ducing intra-hour balancing cost by optimally adjusting the production level before real-time operationbyutilisingmanualreserves. Inbothpapers,weseethattakingaproactiveapproach entails substantially lower cost than letting automatic reserves handle all the imbalances real- time. In the first paper, we propose a mixed integer deterministic model for the intra-hour bal- ancing problem. We investigate the Danish system, where wind power is highly used and a major source for intra-hour imbalances between supply and demand. We find that balancing costdonotoutweighthebenefitsofthefluctuatinginexpensivewindpower. Thesecondpaperisanextensionofthefirstpaper. Here,wepresentatwo-stagestochastic mixedintegermodelfortheintra-hourbalancingproblem. Themodelcapturestheuncertainty intheforecastsofwindpowerproductionbygeneratingscenariosforthepredictionerrors. We compare the stochastic and the deterministic solutions to the solution of perfect foresight and find that prediction errors entail huge balancing cost. Furthermore, we see that the stochastic solution incorporates a buffer when activating manual reserves compared to the determinis- tic solution. Incorporation of this buffer results in higher expected cost, but the actual cost incurredislowerinmostoftheinvestigatedcases. i In the last paper, we look at an environmental supplement or alternative to wind power. Here, we present a mixed integer linear model, which can be used to design the supply chain networkforbiomass. Improvingthelogisticsofbiomass-to-energysupplychainsisarequire- mentforenablingbiomassasaneconomicalandenvironmentallysoundadditionallong-term sourceofenergy. Thedesignofthesupplychainnetworkisimportantforachievingefficiency in logistics operations, and it involves long-term decisions regarding transport flows, capaci- ties,aswellasthenumberandtypesoffacilitiesusedinthenetworkforprovidingbiomassand transformingitintoenergy. Inourcasetheparticularbiomassisstrawthatmay be converted into compressed briquettes. In addition to other models for biomass supply chain design, we optimise the network design together with the truck routes. The paper is a preliminary ver- sion as we have not yet received all the necessary data needed to run the model on our full Danish case study (design of the supply chain network and transportation routes for the new bioethanolplantatMaabjerg). Fornow,weproposeaLagrangianrelaxationbyvariablesplit- ting as the solution method. On small test instances, this method provides reasonable gaps betweenupperandlowerboundsontheobjectivefunctionvalue. StandardsolversasCPLEX are not able to solve some of these small instances, which indicate a need for a tailor-made algorithmtosolvetheproblem. ii Resumé Denneph.d.-afhandlingbeståraftreuafhængigeartiklerihvertsitkapitel,somalleerrelateret tilmodelleringenafoptimeringsproblemerindenforenergisystemer. Idetoførsteartiklerservipåelsystemetsdriftindenfordenenkeltetime,hvorudbudog efterspørgsel af elektricitet skal balanceres. Vi præsenterer to proaktive optimeringsmodeller, som,baseretpåforudsigelserafubalancermellemudbudogefterspørgsel,prøveratreducere balanceringsomkostningerne ved at justere produktionsniveauet med manuelle reserver før selve drifttidspunktet. Vi ser i begge artikler, at den proaktive tilgang resulterer i betydeligt lavereomkostningerendhvisviventermedathåndtereubalancernetilselvedrifttidspunktet, hvorautomatiskereserverbenyttes. Viforeslåridenførsteartikelendeterministiskmodeltilatbeskrivebalanceringsproblemet inden for timen. Vindenergi er en kæmpe kilde til ubalancer inden for timen mellem udbud og efterspørgsel af elektricitet. I den førte artikel undersøger vi derfor effekten balancemæs- sigt af vindenergi i det danske system, hvor det dækker en stor del af elforbruget. Det viser sig, at selvom fluktuerende vindenergi skaber større ubalancer i elsystemet jo mere vind der inkluderes,såerfordeleneveddenbilligevindkraftrentomkostningsmæssigtlangtstørreend ulemperne. Den anden artikel ligger i forlængelse af den første og her præsenterer vi en stokastisk modeltilat beskrivebalanceringsproblemetindenfortimen. Modellenfangerusikkerheden i forudsigelserneafproduktionenafvindenergivedatgenererescenarierforfejlenivindenergi- prognoserne. Vi sammenligner den stokastiske løsning og den deterministiske løsning med løsningengivetvedperfektfremsynethedogser,atprognosefejlenemedførerbetydeligebalan- ceringsomkostninger. Endvidereservi,atdenstokastiskeløsning,setiforholdtildendetermi- iii nistiskeløsning, inkorporererenbuffer, nårdenaktiverermanuellereserver. Inkorporeringen af denne buffer resulterer i højere forventede omkostninger, men de aktuelle omkostninger er tilgengældlavereideflesteafdeundersøgtetestinstanser. I den sidste artikel ser vi på et miljøvenligt supplement eller alternativ til vindenergien. Herpræsenterervienblandetheltalsmodel,somkanbrugestilatdesignenetværketforforsy- ningskæden af biomasse. Forbedringer af logistikken i forsyningskæden biomasse-til-energi er en betingelse for, at biomasse bliver en økonomisk og miljørigtig langvarig kilde til energi. Designet af netværket for forsyningskæden er af yderste vigtighed for at opnå effektivitet i logistikken. Optimering af netværket involverer langsigtede beslutninger vedrørende trans- porten og kapaciteter såvel som hvor mange og hvilke typer anlæg, der skal bruges for at tilvejebringebiomasseogtransformeredettilenergi. Ivorestilfældevilbiomassenværehalm, somkankonverterestilbriketter. Iforholdtilandreoptimeringsmodellerfordesignafforsyn- ingskæderafbiomasseoptimerervinetværketsamtidigmed,atvioptimererlastbilernesruter. Daviendnuikkeharaltdatatilrådighedtilatkunnekøremodellenpåvoresfuldecase(design af forsyningskæde samt transportruter for den nye bioethanol fabrik ved Maabjerg), er denne artikel en foreløbig version. I denne version foreslår vi Lagrange relaksation med opdeling af variabler (variable splitting) som løsningsmetode. På mindre test instanser giver metoden forholdsvissmåforskellemellemøvreognedregrænserforobjektfunktionsværdierne. Nogle afdissemindreinstansererenstandardsolversomCPLEXikkeistandtilatløse,hvilketviser behovetforatudvikleenspecialdesignetløsningsmetodeforproblemstillingen. iv Preface I have prepared this thesis during my enrollment as a PhD student at the Department of Eco- nomics and Business, Aarhus University, in the period from January 2011 to March 2015. My PhD project has been funded by CFEM (Center for Foundations of Electronic Markets) which inturnisfundedbytheDanishCouncilofStrategicResearch. During my PhD studies, I had two small internships and a temporary employment at the Danishtransmissionsystemoperator,Energinet.dk. Theinternshipswerein2011andthetem- poraryemploymentwasintheperiodfromSeptember2012toFebruary2013. Eventhoughmy employment at Energinet.dk was not directly related to my PhD studies, I learned a lot about electricitysystemsandmarketswhichIthinkhasbeenahugeassetformethroughouttherest ofmystudies. However,ithasalsobeenachallengetocombineknowledgeofrealworldprob- lems and approaches with the academic discipline. It has especially been difficult to find the balancewherearealworldproblemwasdescribedgoodenough,whileanacademicapproach stillwasmaintained. On the personal level I was fortunate to become mother to a wonderful boy in late 2013. Even though it has not been easy to manage both motherhood and writing this thesis, it has also brought structure and happiness into the writing process; it has just been lovely to have these small joyful moments of pause that naturally occur when spending time with a small child. Acknowledgement First and foremost, I want to express my gratitude to the Department of Economics and Busi- ness for providing an excellent research environment and to CFEM for providing financial v support. I want to thank my supervisor Kim Allan Andersen for encouraging me to write a PhD, and for being a moral support throughout the years. Even though the project did not follow the original plan, he never doubted me, and he always protected my interests for which I am trulygrateful. I want to give a special thanks to my co-supervisor, Nina Kildegaard Detlefsen. She has alwaysbeentherewhenIneededsupportaswellaswhenIjustneededtogetfrustrationsout in the open. Furthermore, we have had many fruitful academic discussions which definitely hasimprovedthecontentofthisPhDthesis. Iwanttothankmydearfriendandcollaborator, DitteMølgårdHeide-Jørgensen, whoisa co-author on my first paper. Even though we have had some challenges, pregnancies among other things, we have kept our friendship and learned a lot from each other. It has been a privilegetoworkwithher! I also want to give a special thanks to Trine Krogh Boomsma, who is also a co-author on my first paper. She did not have an easy task of supervising the paper, since she where not involvedfromthebeginning, butshenevergaveuponus. Ialsowanttothankherforallthe workshehasputintocommentingoneverythingIhavesenther-eventhoughitcameback moreredthanblackIamtrulygrateful,andIthinkithasmademeabetterwriter. FromMarchtoJune2012,IvisitedAsgeirTomasgardattheDepartmentofIndustrialEco- nomics and Technology Management at NTNU, Trondheim. It was an interesting period, where I had the opportunity to be in a research environment with people who were inter- estedinproblemssimilartomine. IamtrulygratefultoAsgeirforhostingmystayandforour collaborationonmysecondpaper. DuringmystayinNorway,AsgeirintroducedmetoMichal KautatSINTEF,Trondheim. IwanttothankMichalforourcollaborationonmysecondpaper. Ialsowanttothankmyco-authorsonthethirdpaper,AndreasKloseandClausAageGrøn Sørensen. Ithinkithasbeenaninterestingprojectandaverygoodcollaboration. Another person I want to give a special thank is Stephan Wöllner, who I met during my stays at Energinet.dk. Stephan has been a good colleague and he has made a lot of effort in making SimBa, a model from Energinet.dk, deliver the necessary data in the correct format, such that it could be used in my second project. I also want to express my gratitude to En- vi erginet.dkforprovidingdata,lendingmodels,fortheirhospitalityduringmytwointernships. Also, I want to thank my colleagues at CORAL and my fellow PhD students. I specially want to thank Camilla Pisani, David Sloth Pedersen, Lene Gilje Justesen, Lukas Bach, Maria ElbekAndersen,MarieHerly,RezaPourmoayed,SamiraMirzaei,SuneLauthGadegaard,Tine Louise Mundbjerg Eriksen, Tue Rauff Lind Christensen, and Viktoryia Buhayenko. The last fouryearswouldnothavebeenthesamewithoutyouguys! Lastbutnotleast,Iwanttogiveaspecialthanktomyfamilyandespeciallymyboyfriend, MortenLeanderPetersen,forbelievinginmeandforallthesupporthehasgivenme. Icanonly imaginehowitmusthavebeenforhimthroughoutthelastcoupleofyears,andespeciallythe last couple of months, while I have been writing this thesis. I really appreciate all his support andhiseffortstomakemylifeeasier. Ilovehimwithallofmyheart! vii

Description:
A PhD thesis submitted to the School of Business and Social Sciences, .. renewable energy in the total energy system, and 50% of the electricity
See more

The list of books you might like

Most books are stored in the elastic cloud where traffic is expensive. For this reason, we have a limit on daily download.