{"title":"基于afcpoa的径向配电网PV-wind混合dg优化调度","authors":"Sunil Ankeshwarapu","doi":"10.1016/j.nxener.2025.100347","DOIUrl":null,"url":null,"abstract":"<div><div>This study proposes the Adaptive Fuzzy Campus Placement-based Optimization Algorithm (AFCPOA) for optimal dispatch of Renewable Distributed Generators (RDGs) — Solar PV, Wind, and Hybrid (PV<!--> <!-->+<!--> <!-->Wind) in a Radial Distribution Network (RDN) considering dynamic hourly and seasonal load variations. AFCPOA minimizes total power losses and enhances voltage stability using a Network Topology-based Load Flow approach. Its performance was evaluated on the IEEE 33-bus system and benchmarked against Hybrid Genetic Algorithm (GA)-Jaya, Jaya Algorithm, Shuffled Frog-Leaping Algorithm (SFLA), Particle Swarm Optimization (PSO), and GA. Results show that AFCPOA achieved a 42.6% reduction in total losses compared to the base case and outperformed other algorithms by 9–18% in loss reduction, with an average voltage profile improvement of 5.3%. These findings demonstrate AFCPOA’s superior ability to handle seasonal load variability and optimize RDG integration efficiently.</div></div>","PeriodicalId":100957,"journal":{"name":"Next Energy","volume":"8 ","pages":"Article 100347"},"PeriodicalIF":0.0000,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"AFCPOA-based optimal dispatch of hybrid PV-wind DGs for voltage stability and loss reduction in radial distribution network\",\"authors\":\"Sunil Ankeshwarapu\",\"doi\":\"10.1016/j.nxener.2025.100347\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This study proposes the Adaptive Fuzzy Campus Placement-based Optimization Algorithm (AFCPOA) for optimal dispatch of Renewable Distributed Generators (RDGs) — Solar PV, Wind, and Hybrid (PV<!--> <!-->+<!--> <!-->Wind) in a Radial Distribution Network (RDN) considering dynamic hourly and seasonal load variations. AFCPOA minimizes total power losses and enhances voltage stability using a Network Topology-based Load Flow approach. Its performance was evaluated on the IEEE 33-bus system and benchmarked against Hybrid Genetic Algorithm (GA)-Jaya, Jaya Algorithm, Shuffled Frog-Leaping Algorithm (SFLA), Particle Swarm Optimization (PSO), and GA. Results show that AFCPOA achieved a 42.6% reduction in total losses compared to the base case and outperformed other algorithms by 9–18% in loss reduction, with an average voltage profile improvement of 5.3%. These findings demonstrate AFCPOA’s superior ability to handle seasonal load variability and optimize RDG integration efficiently.</div></div>\",\"PeriodicalId\":100957,\"journal\":{\"name\":\"Next Energy\",\"volume\":\"8 \",\"pages\":\"Article 100347\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-06-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Next Energy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2949821X25001103\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Next Energy","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2949821X25001103","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
AFCPOA-based optimal dispatch of hybrid PV-wind DGs for voltage stability and loss reduction in radial distribution network
This study proposes the Adaptive Fuzzy Campus Placement-based Optimization Algorithm (AFCPOA) for optimal dispatch of Renewable Distributed Generators (RDGs) — Solar PV, Wind, and Hybrid (PV + Wind) in a Radial Distribution Network (RDN) considering dynamic hourly and seasonal load variations. AFCPOA minimizes total power losses and enhances voltage stability using a Network Topology-based Load Flow approach. Its performance was evaluated on the IEEE 33-bus system and benchmarked against Hybrid Genetic Algorithm (GA)-Jaya, Jaya Algorithm, Shuffled Frog-Leaping Algorithm (SFLA), Particle Swarm Optimization (PSO), and GA. Results show that AFCPOA achieved a 42.6% reduction in total losses compared to the base case and outperformed other algorithms by 9–18% in loss reduction, with an average voltage profile improvement of 5.3%. These findings demonstrate AFCPOA’s superior ability to handle seasonal load variability and optimize RDG integration efficiently.