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Optimal Placement and Sizing Algorithm for BESS to Enhance the Renewable Energy Hosting Capacity of Power Systems
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Lee, Donghyun | - |
| dc.contributor.author | Jeon, Seungchan | - |
| dc.contributor.author | Lee, Changhee | - |
| dc.contributor.author | Hwang, Sungyu | - |
| dc.contributor.author | Bae, Sungwoo | - |
| dc.contributor.author | Kim, Sihwan | - |
| dc.contributor.author | Kwak, Joosik | - |
| dc.date.accessioned | 2025-03-05T07:30:12Z | - |
| dc.date.available | 2025-03-05T07:30:12Z | - |
| dc.date.issued | 2025-02 | - |
| dc.identifier.issn | 1975-8359 | - |
| dc.identifier.issn | 2287-4364 | - |
| dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/206682 | - |
| dc.description.abstract | This paper proposes an algorithm for determining the optimal location and sizing of a battery energy storage system (BESS) to enhance the grid hosting capacity when integrating renewable energy sources. The proposed algorithm optimizes the BESS by considering both active power absorption and reactive power supply functions, utilizing the particle swarm optimization (PSO) algorithm. By incorporating voltage sensitivity analysis, the computation time and convergence to the optimal solution of the PSO were improved. To validate the effectiveness of the proposed method, simulations were conducted based on the IEEE 300-Bus system. The P-V curve analysis indicated that the integration of BESS led to a 50.8% increase in grid capacity for renewable energy sources. Furthermore, compared to conventional methods that considered only active power, the proposed approach achieved a 9.8% increase in grid capacity. | - |
| dc.format.extent | 8 | - |
| dc.language | 한국어 | - |
| dc.language.iso | KOR | - |
| dc.publisher | 대한전기학회 | - |
| dc.title | Optimal Placement and Sizing Algorithm for BESS to Enhance the Renewable Energy Hosting Capacity of Power Systems | - |
| dc.title.alternative | 전력 계통의 재생에너지 수용 능력 향상을 위한 BESS의 위치 및 용량 최적화 알고리즘 | - |
| dc.type | Article | - |
| dc.publisher.location | 대한민국 | - |
| dc.identifier.doi | 10.5370/KIEE.2025.74.2.221 | - |
| dc.identifier.scopusid | 2-s2.0-85218112854 | - |
| dc.identifier.bibliographicCitation | 전기학회논문지, v.74, no.2, pp 221 - 228 | - |
| dc.citation.title | 전기학회논문지 | - |
| dc.citation.volume | 74 | - |
| dc.citation.number | 2 | - |
| dc.citation.startPage | 221 | - |
| dc.citation.endPage | 228 | - |
| dc.type.docType | Article | - |
| dc.identifier.kciid | ART003169504 | - |
| dc.description.isOpenAccess | N | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.description.journalRegisteredClass | kci | - |
| dc.subject.keywordPlus | Particle swarm optimization (PSO) | - |
| dc.subject.keywordPlus | Sensitivity analysis | - |
| dc.subject.keywordAuthor | Battery Energy Storage System | - |
| dc.subject.keywordAuthor | P-V Curve | - |
| dc.subject.keywordAuthor | Particle Swarm Optimization | - |
| dc.subject.keywordAuthor | Renewable Energy | - |
| dc.subject.keywordAuthor | Voltage Sensitivity | - |
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