Optimal management of household load under demand response

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dc.contributor.advisor Xia, Xiaohua en
dc.contributor.postgraduate Setlhaolo, Ditiro en
dc.date.accessioned 2016-07-29T11:02:07Z
dc.date.available 2016-07-29T11:02:07Z
dc.date.created 2016-04-15 en
dc.date.issued 2015 en
dc.description Thesis (PhD)--University of Pretoria, 2015. en
dc.description.abstract Residential demand response (RDR) is one of the demand side management (DSM) programs for smart grid applications that are designed to enable utility companies to manage the userside electrical loads and also for consumers to voluntarily lower their demand. Instead of adding more generators to the electrical power system, RDR programs pay residential energy users to reduce consumption. Due to the complex interactions between residential customers and the power utility companies; in this thesis, RDR is studied using an optimization approach for the reason that optimization of energy consumption, with consequent cost reduction, is among the primary problems of the present and future smart grid. In this thesis optimal control models are formulated to study household energy management under timeof- use (TOU) electricity pricing strategy. The initial optimal control mathematical model is developed where consumers attempt to find the best way to schedule their household electrical resources depending on the tariff provided by the utility and the incentive offered during peak times. Under such a setting, whenever customers have enough transferable appliances, significant energy cost savings can be achieved with proper modelling of appliance usage in a household. Consumer behaviour plays a crucial role in ensuring that RDR is achieved. It has been discovered in this thesis that; inconvenience, incentive, budget and coordination of appliances affect consumer s energy consumption behaviour. Other areas that need attention in order to further enhance the solutions of the research question are investigated. It has been shown that by incorporating the storage and photovoltaic (PV) generator the consumer can increase cost savings and reduce their electricity peak consumption further as well as the total energy drawn from the grid. Insights on the complexity of the optimization problem are provided, to allow customers to better determine the trade-off between complexity, cost, and the need to schedule their energy resources. The derived models provide a blueprint for integrating demand-side management and scheduling of resources. The other part of the study proposes an optimal energy management system that combines DSM strategies for aggregated households; DR with a dedicated PV and battery which shows that the aggregated consumption can reduce the power demanded from a distribution system by a significant amount and thus relieve the power system network and afford some residential members significant collective savings. Further more, it is shown in this thesis that knowledge on carbon emissions can incentivize investment in renewable energy at household level. It is also demonstrated that the consumer s preferences on the cost sub-functions of energy, inconvenience and carbon emissions affect the consumption pattern. These results are important for both the consumer and the electricity suppliers, as they illustrate the optimal decisions considered in the presence of multiple sub-objectives. In this work, field measurements are carried out to obtain the baseline appliance commitment and these are compared with the optimal solutions obtained through the inconvenience model. en
dc.description.abstract Huishoudelike vraagrespons (HVR) is een van die vraagkantbestuur- (VKB) programme vir slimnetwerktoepassings wat ontwerp is om elektrisiteitsmaatskappye toe te laat om verbruikerskant- elektriese las te bestuur, asook om verbruikers toe te laat om hul elektriese aanvraag vrywillig te verlaag. In plaas daarvan om meer elektrisiteit te genereer, betaal HRV-programme huishoudelike verbruikers om hul verbruik te verlaag. Daar is komplekse interaksies tussen huishoudelike verbruikers en die elektrisiteitsmaatskappye. Daarom is die tesis dat HVR, benader vanuit n optimeringsperspektief, met gevolglike kostebesparing, een van die hoofuitdagings van die toekomstige slimnetwerk is. In hierdie tesis word optimale beheermodelle geformuleer om huishoudelike energiebestuur onder die tyd-van-verbruik- (TVV) prysstrategie te bestuur. Die aanvanklike optimale beheer wiskundige model word ontwikkel sodat die verbruiker sy elektrisiteitsverbruik skeduleer om gebruik te maak van die aansporing wat tydens spitstye gebied word. Sodoende kan noemenswaardige energiekostebesparings word, as verbruikers oor genoeg verskuifbare elektriese toestel-laste beskik. Verbruikersgedrag speel n deurslaggewende rol om HVR te verseker. Daar is in hierdie tesis bepaal dat ongerief, aansporing, begroting, en koördinasie van toestelle verbruikers se energieverbruikgedrag beïnvloed. Ander areas wat aandag nodig het ten einde oplossings te verbeter, word ook ondersoek. Daar word getoon dat deur energiestoring en fotovoltaïese (FV) generators te gebruik, die verbruiker sy kostebesparings kan vergroot en sy spitstydelektrisiteitsverbruik verder kan verlaag. Insigte in die ingewikkeldheid van die optimeringsprobleem word verskaf, ten einde verbruikers te help om kompleksiteit, koste en die skedulering van energiehulpbronne te bestuur. Die modelle verskaf n bloudruk vir geïntegreerde VBK- en toestelvlakskedulering. Die volgende gedeelte van die studie stel n optimale energiebestuursisteem vir VBK-strategieë met gesommeerde huishoudings voor. VR met n toegewyde FV-sel en battery word gebruik, en daar is bevind dat die gesommeerde verbruik noemenswaardig verminder kan word. Dit bring noemenswaardige gesommeerde besparings vir sekere huishoudings teweeg, en verminder ook die las op die elektrisiteitsnetwerk. Die volgende gedeelte van die studie wys dat kennis van koolstofvrystellings beleggings in hernubare energie kan aanspoor op huishoudelike vlak. Daar word ook bewys dat verbruikersvoorkeure met betrekking tot energie, gerief, en koolstofvrystellings verbruikpatrone affekteer. Die resultate is belangrik vir beide elektrisiteitsverskaffers en vebruikers, en illustreer optimale besluite gegewe die kompromieë tussen teenstrydige doeleindes. In hierdie werk word veldmetings gebruik om basislyntoesteltoewydings te bepaal en te vergelyk met optimale oplossings wat deur simulasie verkry is. en
dc.description.availability Unrestricted en
dc.description.degree PhD en
dc.description.department Electrical, Electronic and Computer Engineering en
dc.description.librarian tm2016 en
dc.identifier.citation Setlhaolo, D 2015, Optimal management of household load under demand response, PhD Thesis, University of Pretoria, Pretoria, viewed yymmdd <http://hdl.handle.net/2263/56107> en
dc.identifier.other A2016 en
dc.identifier.uri http://hdl.handle.net/2263/56107
dc.language.iso en en
dc.publisher University of Pretoria en_ZA
dc.subject UCTD en
dc.title Optimal management of household load under demand response en
dc.type Thesis en


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