{"title":"总结了在部分遮阳条件下光伏系统全局最大功率跟踪的几种智能算法的基础上,提出了一种新的最大功率跟踪算法","authors":"Youjie Ma, Xuesong Zhou, Zhiqiang Gao, Tianqi Bai","doi":"10.1109/ICMA.2017.8015834","DOIUrl":null,"url":null,"abstract":"Energy efficient conversion is always a hot topic in the field of photovoltaic power generation. Contract to traditional algorithm, the lasted research showed intelligent algorithms have remarkable advantages in multiple-peak output power characteristics affected by partial shading. This article presents some popular intelligent algorithms such as particle swarm optimization(PSO), genetic algorithm(GA), ant colony optimization (ACO), etc. When PV systems are affected by partial shading, these GMPPT (global maximum power point tracking) algorithm is required to increase the energy harvesting capability of the system. By analyze and discuss the search efficiency and convergence property of several intelligent optimization methods mentioned above, multiple problem still exist and the GMPP can not usually be tracked exactly and quickly. Thus, this article point out it is great significance that several hybrid intelligent algorithms are put forward to compensate the deficiency of single algorithms, and modified the optimization is also required.","PeriodicalId":124642,"journal":{"name":"2017 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Summary of the novel MPPT (maximum power point tracking) algorithm based on few intelligent algorithms specialized on tracking the GMPP (global maximum power point) for photovoltaic systems under partially shaded conditions\",\"authors\":\"Youjie Ma, Xuesong Zhou, Zhiqiang Gao, Tianqi Bai\",\"doi\":\"10.1109/ICMA.2017.8015834\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Energy efficient conversion is always a hot topic in the field of photovoltaic power generation. Contract to traditional algorithm, the lasted research showed intelligent algorithms have remarkable advantages in multiple-peak output power characteristics affected by partial shading. This article presents some popular intelligent algorithms such as particle swarm optimization(PSO), genetic algorithm(GA), ant colony optimization (ACO), etc. When PV systems are affected by partial shading, these GMPPT (global maximum power point tracking) algorithm is required to increase the energy harvesting capability of the system. By analyze and discuss the search efficiency and convergence property of several intelligent optimization methods mentioned above, multiple problem still exist and the GMPP can not usually be tracked exactly and quickly. Thus, this article point out it is great significance that several hybrid intelligent algorithms are put forward to compensate the deficiency of single algorithms, and modified the optimization is also required.\",\"PeriodicalId\":124642,\"journal\":{\"name\":\"2017 IEEE International Conference on Mechatronics and Automation (ICMA)\",\"volume\":\"70 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE International Conference on Mechatronics and Automation (ICMA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMA.2017.8015834\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Conference on Mechatronics and Automation (ICMA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMA.2017.8015834","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Summary of the novel MPPT (maximum power point tracking) algorithm based on few intelligent algorithms specialized on tracking the GMPP (global maximum power point) for photovoltaic systems under partially shaded conditions
Energy efficient conversion is always a hot topic in the field of photovoltaic power generation. Contract to traditional algorithm, the lasted research showed intelligent algorithms have remarkable advantages in multiple-peak output power characteristics affected by partial shading. This article presents some popular intelligent algorithms such as particle swarm optimization(PSO), genetic algorithm(GA), ant colony optimization (ACO), etc. When PV systems are affected by partial shading, these GMPPT (global maximum power point tracking) algorithm is required to increase the energy harvesting capability of the system. By analyze and discuss the search efficiency and convergence property of several intelligent optimization methods mentioned above, multiple problem still exist and the GMPP can not usually be tracked exactly and quickly. Thus, this article point out it is great significance that several hybrid intelligent algorithms are put forward to compensate the deficiency of single algorithms, and modified the optimization is also required.