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기상변수를 이용한 도서지역 전력수요 예측 모형의 적합성에 관한 연구

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dc.contributor.author김영은-
dc.contributor.author조용성-
dc.contributor.author김경남-
dc.date.accessioned2021-09-03T12:39:25Z-
dc.date.available2021-09-03T12:39:25Z-
dc.date.created2021-06-17-
dc.date.issued2017-
dc.identifier.issn1738-3935-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/85552-
dc.description.abstractLong and short-term load demand forecasting are of great importance in the process of electricity policy formulation. Inparticular, load forecasting in an energy-independence island is essential for an appropriate investment in off-grid electrical powersystems using renewable energy sources. The purpose of this study was to evaluate the performance of three models in forecasting theelectricity load demand in an island area: the multiple regression model, ARIMA model, and Reg-ARIMA model, which is thecombined model of the two preceding ones. Using the Root Mean Square Error (RMSE) and Mean Absolute Percentage Error(MAPE) as a forecasting accuracy criterion and comparing the predicted and real values of the three islands in 2015, the studyconcluded that the combined method is a more appropriate model.-
dc.languageKorean-
dc.language.isoko-
dc.publisher한국신·재생에너지학회-
dc.title기상변수를 이용한 도서지역 전력수요 예측 모형의 적합성에 관한 연구-
dc.title.alternativeA Study on the Suitability of Load Demand Forecasting Models for Island Area Using Weather Variables-
dc.typeArticle-
dc.contributor.affiliatedAuthor조용성-
dc.contributor.affiliatedAuthor김경남-
dc.identifier.bibliographicCitation신재생에너지, v.13, no.2, pp.84 - 93-
dc.relation.isPartOf신재생에너지-
dc.citation.title신재생에너지-
dc.citation.volume13-
dc.citation.number2-
dc.citation.startPage84-
dc.citation.endPage93-
dc.type.rimsART-
dc.identifier.kciidART002231163-
dc.description.journalClass2-
dc.description.journalRegisteredClasskci-
dc.subject.keywordAuthorLoad demand forecasting-
dc.subject.keywordAuthorARIMA modelling-
dc.subject.keywordAuthorMultiple regression model-
dc.subject.keywordAuthorRegression-ARIMA mode-
dc.subject.keywordAuthorEnergy-independence island-
dc.subject.keywordAuthor전력 수요 예측-
dc.subject.keywordAuthorARIMA 모델링-
dc.subject.keywordAuthor다중 회귀 모형-
dc.subject.keywordAuthor회귀-ARIMA 모형-
dc.subject.keywordAuthor에너지자립섬-
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College of Life Sciences and Biotechnology > Department of Food and Resource Economics > 1. Journal Articles
Graduate School of Energy and Environment (KU-KIST GREEN SCHOOL) > Department of Energy and Environment > 1. Journal Articles

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