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.
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.
