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DC Field | Value | Language |
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dc.contributor.author | Chatuphat Karaaom | en_US |
dc.contributor.author | Peerapol Jirapong | en_US |
dc.contributor.author | Panida Thararak | en_US |
dc.contributor.author | Keerachat Tantrapon | en_US |
dc.date.accessioned | 2020-10-14T08:32:56Z | - |
dc.date.available | 2020-10-14T08:32:56Z | - |
dc.date.issued | 2020-03-01 | en_US |
dc.identifier.other | 2-s2.0-85085028931 | en_US |
dc.identifier.other | 10.1109/iEECON48109.2020.229528 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85085028931&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/70530 | - |
dc.description.abstract | © 2020 IEEE. The increasing penetration of distributed generations (DGs) in distribution systems has become an important generating source for future electricity grids. However, the improper DGs installation and the imbalance between high electrical power supplies from the DGs and low customer demands can cause reverse power flow, which results in a higher system power loss. In this paper, an efficient network reconfiguration technique implemented with an optimal tie switch allocation using particle swarm optimization (PSO) is proposed to minimize the system energy loss from the excess imbalance power in distribution systems. The optimization algorithm is performed using MATLAB and DIgSILENT PowerPFactory to carry out the optimal location of the tie switch. The proposed approach is tested on a practical 22 kV distribution system from the Provincial Electricity Authority, Thailand. The simulation results show that the system energy loss can be significantly reduced from 61.02 to 36.38 MWh, with a percentage reduction of 40.38%. | en_US |
dc.subject | Energy | en_US |
dc.subject | Engineering | en_US |
dc.subject | Materials Science | en_US |
dc.subject | Physics and Astronomy | en_US |
dc.title | Optimal Allocation of Tie Switch in Distribution Systems for Energy Loss Reduction Using Particle Swarm Optimization | en_US |
dc.type | Conference Proceeding | en_US |
article.title.sourcetitle | 2020 8th International Electrical Engineering Congress, iEECON 2020 | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
article.stream.affiliations | Provincial Electricity Authority | en_US |
Appears in Collections: | CMUL: Journal Articles |
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