Md Akib Hasan , Md Showkot Hossain , Mohd Azrik Roslan , Azralmukmin Azmi , Leong Jenn Hwai , Ahmad Afif Nazib , Noor Syafawati Ahmad
{"title":"孤岛交流微电网效率提升的优化下垂控制策略","authors":"Md Akib Hasan , Md Showkot Hossain , Mohd Azrik Roslan , Azralmukmin Azmi , Leong Jenn Hwai , Ahmad Afif Nazib , Noor Syafawati Ahmad","doi":"10.1016/j.ifacsc.2025.100319","DOIUrl":null,"url":null,"abstract":"<div><div>The increasing integration of renewable energy sources has accelerated the adoption of microgrids, necessitating efficient power-sharing and control techniques for reliable operation. This study proposes an optimized droop control technique for parallel inverters in islanded AC microgrids, focusing on improving system efficiency. Conventional droop methods often encounter challenges in power-sharing accuracy under varying load conditions due to mismatched feeder impedances and differing power loss characteristics of distributed generators (DGs). To address these issues, the proposed method dynamically adjusts droop coefficients using Particle Swarm Optimization (PSO) to optimize power distribution, reduce circulating currents, and improve energy conversion efficiency while maintaining system modularity. A system-level microgrid efficiency model is designed to identify optimal operating points under diverse load profiles. Comparative analysis demonstrates that the proposed PSO-based controller consistently outperforms conventional droop methods, achieving system efficiency improvements ranging from 0.11% to 0.52% across various load conditions and power factors. Simulation results from PSIM and MATLAB/Simulink further highlight reduced circulating currents, enhanced energy conversion efficiency, and improved system stability. These findings underscore the potential of PSO-driven control as a scalable and communication-free solution for efficiency optimization in decentralized microgrids.</div></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"33 ","pages":"Article 100319"},"PeriodicalIF":1.8000,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimized droop control strategy for efficiency improvement in islanded AC microgrid\",\"authors\":\"Md Akib Hasan , Md Showkot Hossain , Mohd Azrik Roslan , Azralmukmin Azmi , Leong Jenn Hwai , Ahmad Afif Nazib , Noor Syafawati Ahmad\",\"doi\":\"10.1016/j.ifacsc.2025.100319\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The increasing integration of renewable energy sources has accelerated the adoption of microgrids, necessitating efficient power-sharing and control techniques for reliable operation. This study proposes an optimized droop control technique for parallel inverters in islanded AC microgrids, focusing on improving system efficiency. Conventional droop methods often encounter challenges in power-sharing accuracy under varying load conditions due to mismatched feeder impedances and differing power loss characteristics of distributed generators (DGs). To address these issues, the proposed method dynamically adjusts droop coefficients using Particle Swarm Optimization (PSO) to optimize power distribution, reduce circulating currents, and improve energy conversion efficiency while maintaining system modularity. A system-level microgrid efficiency model is designed to identify optimal operating points under diverse load profiles. Comparative analysis demonstrates that the proposed PSO-based controller consistently outperforms conventional droop methods, achieving system efficiency improvements ranging from 0.11% to 0.52% across various load conditions and power factors. Simulation results from PSIM and MATLAB/Simulink further highlight reduced circulating currents, enhanced energy conversion efficiency, and improved system stability. These findings underscore the potential of PSO-driven control as a scalable and communication-free solution for efficiency optimization in decentralized microgrids.</div></div>\",\"PeriodicalId\":29926,\"journal\":{\"name\":\"IFAC Journal of Systems and Control\",\"volume\":\"33 \",\"pages\":\"Article 100319\"},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2025-06-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IFAC Journal of Systems and Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2468601825000252\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IFAC Journal of Systems and Control","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2468601825000252","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
Optimized droop control strategy for efficiency improvement in islanded AC microgrid
The increasing integration of renewable energy sources has accelerated the adoption of microgrids, necessitating efficient power-sharing and control techniques for reliable operation. This study proposes an optimized droop control technique for parallel inverters in islanded AC microgrids, focusing on improving system efficiency. Conventional droop methods often encounter challenges in power-sharing accuracy under varying load conditions due to mismatched feeder impedances and differing power loss characteristics of distributed generators (DGs). To address these issues, the proposed method dynamically adjusts droop coefficients using Particle Swarm Optimization (PSO) to optimize power distribution, reduce circulating currents, and improve energy conversion efficiency while maintaining system modularity. A system-level microgrid efficiency model is designed to identify optimal operating points under diverse load profiles. Comparative analysis demonstrates that the proposed PSO-based controller consistently outperforms conventional droop methods, achieving system efficiency improvements ranging from 0.11% to 0.52% across various load conditions and power factors. Simulation results from PSIM and MATLAB/Simulink further highlight reduced circulating currents, enhanced energy conversion efficiency, and improved system stability. These findings underscore the potential of PSO-driven control as a scalable and communication-free solution for efficiency optimization in decentralized microgrids.