Analysis of distributed power generation forecasting model for power distribution planning
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Cho, J. | - |
dc.contributor.author | Kim, H. | - |
dc.contributor.author | Ryu, H. | - |
dc.contributor.author | Son, Y. | - |
dc.contributor.author | Choi, S. | - |
dc.date.accessioned | 2022-03-10T02:42:14Z | - |
dc.date.available | 2022-03-10T02:42:14Z | - |
dc.date.created | 2022-02-09 | - |
dc.date.issued | 2021 | - |
dc.identifier.issn | 1975-8359 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/138417 | - |
dc.description.abstract | This paper researches a model that predicts a growth in distributed power, taking into account the recent increase in renewable energy interconnected in the distribution system. This paper describes the current state of distributed power and discusses the process of selecting input and output variables for the forecasting model. The, this paper defines various models that can be used for distributed power forecasting and analyze strengths and examples. Finally, this paper compares the utilization of input variables and forecasting models that can be used as mid to long-term distributed power forecasting. Copyright © The Korean Institute of Electrical Engineers. | - |
dc.language | Korean | - |
dc.language.iso | ko | - |
dc.publisher | Korean Institute of Electrical Engineers | - |
dc.title | Analysis of distributed power generation forecasting model for power distribution planning | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Choi, S. | - |
dc.identifier.doi | 10.5370/KIEE.2021.70.9.1248 | - |
dc.identifier.scopusid | 2-s2.0-85115064929 | - |
dc.identifier.bibliographicCitation | Transactions of the Korean Institute of Electrical Engineers, v.70, no.9, pp.1248 - 1262 | - |
dc.relation.isPartOf | Transactions of the Korean Institute of Electrical Engineers | - |
dc.citation.title | Transactions of the Korean Institute of Electrical Engineers | - |
dc.citation.volume | 70 | - |
dc.citation.number | 9 | - |
dc.citation.startPage | 1248 | - |
dc.citation.endPage | 1262 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.identifier.kciid | ART002751471 | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scopus | - |
dc.description.journalRegisteredClass | kci | - |
dc.subject.keywordAuthor | Deep learning model | - |
dc.subject.keywordAuthor | Distribution planning | - |
dc.subject.keywordAuthor | Mid to long-term forecasting | - |
dc.subject.keywordAuthor | Renewable energy resources | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(02841) 서울특별시 성북구 안암로 14502-3290-1114
COPYRIGHT © 2021 Korea University. All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.