Modeling and Analysis of Price-Responsive Loads in the Operation of Smart Grids

dc.contributor.authorRamos-Gaete, Felipe
dc.date.accessioned2013-09-23T18:15:55Z
dc.date.available2013-09-23T18:15:55Z
dc.date.issued2013-09-23T18:15:55Z
dc.date.submitted2013-09-17
dc.description.abstractIn this thesis, a demand elasticity model is developed and tested for the dispatch of high voltage power systems and microgrids. The price obtained from dispatching a network in a base-case scenario is used as input to a price-elastic demand model. This demand model is then used to determine the price-responsive demand for the next iteration, assuming that the load schedule is defined a day-ahead. Using this scheme, trends for demand, hourly prices, and total operation costs for a system can be obtained to study the impact of demand response on unit commitment and dispatch of distributed energy resources. This way, the effect on the scheduling of dispatchable generators and energy storage systems can be analyzed with respect to price-elastic loads. The results for a test power system and a benchmark microgrid show that as the demand is more elastic, the longer it takes for the dispatch to converge to a final condition. The 24-hour model eventually converges to a steady state, with prices and costs at their lowest values for different scenarios, which is good for most system participants and desirable in a market environment, thus highlighting the importance of price-responsive loads in electricity markets.en
dc.identifier.urihttp://hdl.handle.net/10012/7891
dc.language.isoenen
dc.pendingfalseen
dc.publisherUniversity of Waterlooen
dc.subjectDemand Responseen
dc.subjectPower Systemsen
dc.subject.programElectrical and Computer Engineeringen
dc.titleModeling and Analysis of Price-Responsive Loads in the Operation of Smart Gridsen
dc.typeMaster Thesisen
uws-etd.degreeMaster of Applied Scienceen
uws-etd.degree.departmentElectrical and Computer Engineeringen
uws.peerReviewStatusUnrevieweden
uws.scholarLevelGraduateen
uws.typeOfResourceTexten

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