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Virtual power plant and microgrids controller for energy management based on optimization techniques

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dc.citedby5
dc.contributor.authorAbdolrasol M.G.M.en_US
dc.contributor.authorMohamed A.en_US
dc.contributor.authorHannan M.A.en_US
dc.contributor.authorid35796848700en_US
dc.contributor.authorid57195440511en_US
dc.contributor.authorid7103014445en_US
dc.date.accessioned2023-05-29T06:38:31Z
dc.date.available2023-05-29T06:38:31Z
dc.date.issued2017
dc.descriptionAggregates; Energy management; Forecasting; Learning algorithms; Optimization; Particle swarm optimization (PSO); Weather forecasting; Backtracking search algorithms; Distribution generation; Intelligent decisions; Micro grid; Optimization techniques; Particle swarm optimization algorithm; Virtual power plants; Virtual power plants (VPP); Energy management systemsen_US
dc.description.abstractThis paper discuss virtual power plant (VPP) and Microgrid controller for energy management system (EMS) based on optimization techniques by using two optimization techniques namely Backtracking search algorithm (BSA) and particle swarm optimization algorithm (PSO). The research proposes use of multi Microgrid in the distribution networks to aggregate the power form distribution generation and form it into single Microgrid and let these Microgrid deal directly with the central organizer called virtual power plant. VPP duties are price forecast, demand forecast, weather forecast, production forecast, shedding loads, make intelligent decision and for aggregate & optimizes the data. This huge system has been tested and simulated by using Matlab simulink. These paper shows optimizations of two methods were really significant in the results. But BSA is better than PSO to search for better parameters which could make more power saving as in the results and the discussion. � JES 2017.en_US
dc.description.natureFinalen_US
dc.identifier.epage294
dc.identifier.issue2
dc.identifier.scopus2-s2.0-85020073428
dc.identifier.spage285
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85020073428&partnerID=40&md5=48d2e644d37d20451ccca07a7ae74994
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/23218
dc.identifier.volume13
dc.publisherEngineering and Scientific Research Groupsen_US
dc.sourceScopus
dc.sourcetitleJournal of Electrical Systems
dc.titleVirtual power plant and microgrids controller for energy management based on optimization techniquesen_US
dc.typeArticleen_US
dspace.entity.typePublication
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