Optimal Power Management for Nanogrids Based on Technical Information of Electric Appliances

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dc.contributor.authorLee, Sangkeumko
dc.contributor.authorLee, Junhoko
dc.contributor.authorJung, Heedaeko
dc.contributor.authorCho, Jintaeko
dc.contributor.authorHong, Junheeko
dc.contributor.authorLee, Sangminko
dc.contributor.authorHar, Dongsooko
dc.date.accessioned2019-04-29T02:12:02Z-
dc.date.available2019-04-29T02:12:02Z-
dc.date.created2019-03-14-
dc.date.issued2019-05-
dc.identifier.citationENERGY AND BUILDINGS, v.191, pp.174 - 186-
dc.identifier.issn0378-7788-
dc.identifier.urihttp://hdl.handle.net/10203/261609-
dc.description.abstractA novel power management for nanogrids is presented. In this paper, effect of resident location in residence is taken into account for evaluation of power consumption in nanogrids. Depending on the resident location, operating conditions of heater, ventilation fan, and air-conditioner are adjusted. Electric appliances that allow delayed use, i.e., shiftable, are scheduled for efficient power management. Considering massive deployment of energy storage system (ESS) as a supplementary power source, effect of the ESS on power management is investigated. Demand response program for reduced electricity cost is also considered for power management. As a result, an objective consisting of power consumed by non-shiftable and shiftable electric appliances, power supplied/consumed by the ESS during discharging/charging, and time-varying electricity cost is formulated. Another objective for power management is a function of delays in scheduling of shiftable electric appliances. Variation of resident location combined with temporal use of electric appliances according to the resident location are considered as the resident behavior and incorporated into these two objectives. Using these two objectives, a multi-objective optimization is performed for nanogrids at each time interval. It is demonstrated by simulations that leveraging resident behavior is beneficial for power management of nanogrids. In addition, effects of the number of residents in each apartment and combined activity of each resident on the power management are presented with related simulation results. (C) 2019 Elsevier B.V. All rights reserved.-
dc.languageEnglish-
dc.publisherELSEVIER SCIENCE SA-
dc.titleOptimal Power Management for Nanogrids Based on Technical Information of Electric Appliances-
dc.typeArticle-
dc.identifier.wosid000464298900016-
dc.identifier.scopusid2-s2.0-85062993825-
dc.type.rimsART-
dc.citation.volume191-
dc.citation.beginningpage174-
dc.citation.endingpage186-
dc.citation.publicationnameENERGY AND BUILDINGS-
dc.identifier.doi10.1016/j.enbuild.2019.03.026-
dc.contributor.localauthorHar, Dongsoo-
dc.contributor.nonIdAuthorLee, Junho-
dc.contributor.nonIdAuthorJung, Heedae-
dc.contributor.nonIdAuthorCho, Jintae-
dc.contributor.nonIdAuthorHong, Junhee-
dc.contributor.nonIdAuthorLee, Sangmin-
dc.description.isOpenAccessN-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorPower management-
dc.subject.keywordAuthorNanogrid-
dc.subject.keywordAuthorPeak load shifting-
dc.subject.keywordAuthorLocation detection-
dc.subject.keywordAuthorMulti-objective optimization-
dc.subject.keywordPlusMULTIOBJECTIVE OPTIMIZATION-
dc.subject.keywordPlusSTOCHASTIC-MODEL-
dc.subject.keywordPlusENERGY-
dc.subject.keywordPlusBUILDINGS-
dc.subject.keywordPlusDESIGN-
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