Miftakhul Fauzia Hakim, M. Pujiantara, V. Lystianingrum
{"title":"Optimal Setting of Overcurrent Relay on Industrial Power System Using Particle Swarm Optimization","authors":"Miftakhul Fauzia Hakim, M. Pujiantara, V. Lystianingrum","doi":"10.1109/CENIM56801.2022.10037484","DOIUrl":null,"url":null,"abstract":"Overcurrent relay (OCR) setting in the industrial power system is a challenge for some engineers. The problem is not only determining the curve type and the value of the time dial setting (TDS) but also the number of relays that must be set. The relays are installed starting from the load side (downstream) to the power source (upstream). Thus, it takes a long time to set all the installed relays. One of solution to this problem is changing the form of the relay setting problem into an optimization problem. Recently, many studies have been using particle swarm optimization (PSO) to solve optimization problems. However, there are still few of them that use PSO to optimize relay setting problems in an industrial power system. This paper uses PSO as an optimization algorithm to solve OCR setting problem. PSO is a swarm-based algorithm that is easy to implement for various optimization problems but has some drawbacks in solving problems. Therefore, this paper proposes a new form of adaptive PSO, namely modified adaptive particle swarm optimization (MAPSO). In contrast to PSO, the MAPSO algorithm provides more optimal results than the original PSO.","PeriodicalId":118934,"journal":{"name":"2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CENIM56801.2022.10037484","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Overcurrent relay (OCR) setting in the industrial power system is a challenge for some engineers. The problem is not only determining the curve type and the value of the time dial setting (TDS) but also the number of relays that must be set. The relays are installed starting from the load side (downstream) to the power source (upstream). Thus, it takes a long time to set all the installed relays. One of solution to this problem is changing the form of the relay setting problem into an optimization problem. Recently, many studies have been using particle swarm optimization (PSO) to solve optimization problems. However, there are still few of them that use PSO to optimize relay setting problems in an industrial power system. This paper uses PSO as an optimization algorithm to solve OCR setting problem. PSO is a swarm-based algorithm that is easy to implement for various optimization problems but has some drawbacks in solving problems. Therefore, this paper proposes a new form of adaptive PSO, namely modified adaptive particle swarm optimization (MAPSO). In contrast to PSO, the MAPSO algorithm provides more optimal results than the original PSO.