{"title":"用阿基米德优化算法求解配电系统中电容器的布置和尺寸问题","authors":"Rajkumar Kaushik, Chirag Arora, A. Soni, Saloni Upadhyay, Mansi Saini, Vijay Khatik","doi":"10.1109/IATMSI56455.2022.10119290","DOIUrl":null,"url":null,"abstract":"Electric power distribution is the last stage in providing power from power plant to end-clients. Low-voltage profile and high power misfortunes are the significant issues in distribution networks because of load extension and inductive nature of load. Low voltages, which bring about unusual activity of the machines and influence their lifetime, are more antagonistic for customers situated at the far closes from the inventory side. A distributed systems is alluded as a connection point among massive power system and buyers. Different issues are loss of force during transmission, variable voltage profile, expanding cost of system and so on capacitors are utilized for execution upgrade of the system. Because all of these issues straightforwardly impacted by execution or energy proficiency of the system. There are different strategies which are utilized for ideal position of the capacitors in distributed power system. In this article the Archimedes optimization algorithm will be implemented for finding the optimal value of capacitor and then placement of optimized capacitor value at IEEE 15 bus test system to improve the performance of the system. The results of the optimization and system performance will be compared with the Polar Bear Optimization Techniques.","PeriodicalId":221211,"journal":{"name":"2022 IEEE Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Solution of Placement and Sizing of Capacitor Problem in Distribution System using Hybrid Approach of Archimedes Optimization Algorithm\",\"authors\":\"Rajkumar Kaushik, Chirag Arora, A. Soni, Saloni Upadhyay, Mansi Saini, Vijay Khatik\",\"doi\":\"10.1109/IATMSI56455.2022.10119290\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Electric power distribution is the last stage in providing power from power plant to end-clients. Low-voltage profile and high power misfortunes are the significant issues in distribution networks because of load extension and inductive nature of load. Low voltages, which bring about unusual activity of the machines and influence their lifetime, are more antagonistic for customers situated at the far closes from the inventory side. A distributed systems is alluded as a connection point among massive power system and buyers. Different issues are loss of force during transmission, variable voltage profile, expanding cost of system and so on capacitors are utilized for execution upgrade of the system. Because all of these issues straightforwardly impacted by execution or energy proficiency of the system. There are different strategies which are utilized for ideal position of the capacitors in distributed power system. In this article the Archimedes optimization algorithm will be implemented for finding the optimal value of capacitor and then placement of optimized capacitor value at IEEE 15 bus test system to improve the performance of the system. The results of the optimization and system performance will be compared with the Polar Bear Optimization Techniques.\",\"PeriodicalId\":221211,\"journal\":{\"name\":\"2022 IEEE Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI)\",\"volume\":\"93 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IATMSI56455.2022.10119290\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IATMSI56455.2022.10119290","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Solution of Placement and Sizing of Capacitor Problem in Distribution System using Hybrid Approach of Archimedes Optimization Algorithm
Electric power distribution is the last stage in providing power from power plant to end-clients. Low-voltage profile and high power misfortunes are the significant issues in distribution networks because of load extension and inductive nature of load. Low voltages, which bring about unusual activity of the machines and influence their lifetime, are more antagonistic for customers situated at the far closes from the inventory side. A distributed systems is alluded as a connection point among massive power system and buyers. Different issues are loss of force during transmission, variable voltage profile, expanding cost of system and so on capacitors are utilized for execution upgrade of the system. Because all of these issues straightforwardly impacted by execution or energy proficiency of the system. There are different strategies which are utilized for ideal position of the capacitors in distributed power system. In this article the Archimedes optimization algorithm will be implemented for finding the optimal value of capacitor and then placement of optimized capacitor value at IEEE 15 bus test system to improve the performance of the system. The results of the optimization and system performance will be compared with the Polar Bear Optimization Techniques.