{"title":"考虑dg和并联电容的配电系统预定义性能模糊蚁群优化技术","authors":"Preetham Goli, Suresh Makkena, S. Gampa, D. Das","doi":"10.1109/NAPS46351.2019.9000250","DOIUrl":null,"url":null,"abstract":"This paper presents a Fuzzy Ant Colony Optimization (ACO) based approach for optimum allocation and sizing of Distributed Generation units (DGs) and Shunt Capacitors (SCs) in order to improve the predefined performance of the distribution system. The DG units are considered to be operating at lagging power factor and capable of supplying both real and reactive power. The penalty functions are developed for total DG penetration limit, total reactive power injection limit, real power loss reduction target and voltage profile improvement. The fuzzy multi-objective function is formulated by developing the fuzzy membership functions for each penalty function considered for performance improvement. Ant colony optimization technique is used for obtaining the optimum size of DG units and shunt capacitors in order to achieve the predefined performance. The simulation results are demonstrated for a 51 node distribution system to show the effectiveness of the proposed methodology compared to conventional multi-objective function based approach.","PeriodicalId":175719,"journal":{"name":"2019 North American Power Symposium (NAPS)","volume":"31 4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fuzzy Ant Colony Optimization Technique for Predefined Performance of Distribution Systems Considering DGs and Shunt Capacitors\",\"authors\":\"Preetham Goli, Suresh Makkena, S. Gampa, D. Das\",\"doi\":\"10.1109/NAPS46351.2019.9000250\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a Fuzzy Ant Colony Optimization (ACO) based approach for optimum allocation and sizing of Distributed Generation units (DGs) and Shunt Capacitors (SCs) in order to improve the predefined performance of the distribution system. The DG units are considered to be operating at lagging power factor and capable of supplying both real and reactive power. The penalty functions are developed for total DG penetration limit, total reactive power injection limit, real power loss reduction target and voltage profile improvement. The fuzzy multi-objective function is formulated by developing the fuzzy membership functions for each penalty function considered for performance improvement. Ant colony optimization technique is used for obtaining the optimum size of DG units and shunt capacitors in order to achieve the predefined performance. The simulation results are demonstrated for a 51 node distribution system to show the effectiveness of the proposed methodology compared to conventional multi-objective function based approach.\",\"PeriodicalId\":175719,\"journal\":{\"name\":\"2019 North American Power Symposium (NAPS)\",\"volume\":\"31 4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 North American Power Symposium (NAPS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NAPS46351.2019.9000250\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 North American Power Symposium (NAPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAPS46351.2019.9000250","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fuzzy Ant Colony Optimization Technique for Predefined Performance of Distribution Systems Considering DGs and Shunt Capacitors
This paper presents a Fuzzy Ant Colony Optimization (ACO) based approach for optimum allocation and sizing of Distributed Generation units (DGs) and Shunt Capacitors (SCs) in order to improve the predefined performance of the distribution system. The DG units are considered to be operating at lagging power factor and capable of supplying both real and reactive power. The penalty functions are developed for total DG penetration limit, total reactive power injection limit, real power loss reduction target and voltage profile improvement. The fuzzy multi-objective function is formulated by developing the fuzzy membership functions for each penalty function considered for performance improvement. Ant colony optimization technique is used for obtaining the optimum size of DG units and shunt capacitors in order to achieve the predefined performance. The simulation results are demonstrated for a 51 node distribution system to show the effectiveness of the proposed methodology compared to conventional multi-objective function based approach.