Probabilistic Optimal Power Flow-Based Spectral Clustering Method Considering Variable Renewable Energy Sources
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Juhwan | - |
dc.contributor.author | Lee, Jaehyeong | - |
dc.contributor.author | Kang, Sungwoo | - |
dc.contributor.author | Hwang, Sungchul | - |
dc.contributor.author | Yoon, Minhan | - |
dc.contributor.author | Jang, Gilsoo | - |
dc.date.accessioned | 2022-12-09T17:42:29Z | - |
dc.date.available | 2022-12-09T17:42:29Z | - |
dc.date.created | 2022-12-08 | - |
dc.date.issued | 2022-07-14 | - |
dc.identifier.issn | 2296-598X | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/146622 | - |
dc.description.abstract | Power system clustering is an effective method for realizing voltage control and preventing failure propagation. Various approaches are used for power system clustering. Graph-theory-based spectral clustering methods are widely used because they follow a simple approach with a short calculation time. However, spectral clustering methods can only be applied in system environments for which the power generation amount and load are known. Moreover, it is often impossible to sufficiently reflect the influence of volatile power sources (e.g., renewable energy sources) in the clustering. To this end, this study proposes a probabilistic spectral clustering algorithm applicable to a power system, including a photovoltaic (PV) model (for volatile energy sources) and a classification method (for neutral buses). The algorithm applies a clustering method that reflects the random outputs of PV sources, and the neutral buses can be reclassified via clustering to obtain optimal clustering results. The algorithm is verified through an IEEE 118-bus test system, including PV sources. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | FRONTIERS MEDIA SA | - |
dc.subject | HIGH PENETRATION | - |
dc.subject | SYSTEM | - |
dc.subject | GENERATION | - |
dc.subject | NETWORKS | - |
dc.title | Probabilistic Optimal Power Flow-Based Spectral Clustering Method Considering Variable Renewable Energy Sources | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Jang, Gilsoo | - |
dc.identifier.doi | 10.3389/fenrg.2022.909611 | - |
dc.identifier.scopusid | 2-s2.0-85135112864 | - |
dc.identifier.wosid | 000886966600001 | - |
dc.identifier.bibliographicCitation | FRONTIERS IN ENERGY RESEARCH, v.10 | - |
dc.relation.isPartOf | FRONTIERS IN ENERGY RESEARCH | - |
dc.citation.title | FRONTIERS IN ENERGY RESEARCH | - |
dc.citation.volume | 10 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | Y | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Energy & Fuels | - |
dc.relation.journalWebOfScienceCategory | Energy & Fuels | - |
dc.subject.keywordPlus | HIGH PENETRATION | - |
dc.subject.keywordPlus | SYSTEM | - |
dc.subject.keywordPlus | GENERATION | - |
dc.subject.keywordPlus | NETWORKS | - |
dc.subject.keywordAuthor | hierarchical spectral clustering | - |
dc.subject.keywordAuthor | electric power system | - |
dc.subject.keywordAuthor | photovolataics | - |
dc.subject.keywordAuthor | power system analysis | - |
dc.subject.keywordAuthor | expansion | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
145 Anam-ro, Seongbuk-gu, Seoul, 02841, Korea+82-2-3290-2963
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.