{"title":"基于Cuckoo搜索算法和Golden Section搜索算法的部分阴影光伏系统MPPT新方法","authors":"Dimas Aji Nugraha, K. Lian, .. Suwarno","doi":"10.1109/CJECE.2019.2914723","DOIUrl":null,"url":null,"abstract":"Partial shading is a common and difficult problem to be solved in a photovoltaic (PV) system. Numerous efforts have been introduced to mitigate this problem. Some commonly used approaches are deploying some metaheuristic (MH) algorithm to track the multiple-peak $P - V$ curve of partially shaded PV system. Cuckoo search (CS) is a new optimization algorithm based on the MH approach. It has been used to solve an optimization problem in many applications, including the maximum power point tracking (MPPT) problem. The CS algorithm performs well in tracking the global maximum power point (GMPP). However, just like any other MH algorithm, there is still a dilemmatic trading between their accuracy and the tracking time needed to find GMPP. This paper proposes a new MPPT algorithm by combining the CS algorithm with golden section search (GSS) to take beneficial features from both the algorithms. To validate the proposed algorithm, it is evaluated with various cases of partial shading. The simulation and experimental results show a noticeable performance improvement compared with the original CS algorithm and other MH algorithms.","PeriodicalId":55287,"journal":{"name":"Canadian Journal of Electrical and Computer Engineering-Revue Canadienne De Genie Electrique et Informatique","volume":null,"pages":null},"PeriodicalIF":1.7000,"publicationDate":"2019-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/CJECE.2019.2914723","citationCount":"57","resultStr":"{\"title\":\"A Novel MPPT Method Based on Cuckoo Search Algorithm and Golden Section Search Algorithm for Partially Shaded PV System\",\"authors\":\"Dimas Aji Nugraha, K. Lian, .. Suwarno\",\"doi\":\"10.1109/CJECE.2019.2914723\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Partial shading is a common and difficult problem to be solved in a photovoltaic (PV) system. Numerous efforts have been introduced to mitigate this problem. Some commonly used approaches are deploying some metaheuristic (MH) algorithm to track the multiple-peak $P - V$ curve of partially shaded PV system. Cuckoo search (CS) is a new optimization algorithm based on the MH approach. It has been used to solve an optimization problem in many applications, including the maximum power point tracking (MPPT) problem. The CS algorithm performs well in tracking the global maximum power point (GMPP). However, just like any other MH algorithm, there is still a dilemmatic trading between their accuracy and the tracking time needed to find GMPP. This paper proposes a new MPPT algorithm by combining the CS algorithm with golden section search (GSS) to take beneficial features from both the algorithms. To validate the proposed algorithm, it is evaluated with various cases of partial shading. The simulation and experimental results show a noticeable performance improvement compared with the original CS algorithm and other MH algorithms.\",\"PeriodicalId\":55287,\"journal\":{\"name\":\"Canadian Journal of Electrical and Computer Engineering-Revue Canadienne De Genie Electrique et Informatique\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2019-07-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1109/CJECE.2019.2914723\",\"citationCount\":\"57\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Canadian Journal of Electrical and Computer Engineering-Revue Canadienne De Genie Electrique et Informatique\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CJECE.2019.2914723\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Canadian Journal of Electrical and Computer Engineering-Revue Canadienne De Genie Electrique et Informatique","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CJECE.2019.2914723","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Engineering","Score":null,"Total":0}
A Novel MPPT Method Based on Cuckoo Search Algorithm and Golden Section Search Algorithm for Partially Shaded PV System
Partial shading is a common and difficult problem to be solved in a photovoltaic (PV) system. Numerous efforts have been introduced to mitigate this problem. Some commonly used approaches are deploying some metaheuristic (MH) algorithm to track the multiple-peak $P - V$ curve of partially shaded PV system. Cuckoo search (CS) is a new optimization algorithm based on the MH approach. It has been used to solve an optimization problem in many applications, including the maximum power point tracking (MPPT) problem. The CS algorithm performs well in tracking the global maximum power point (GMPP). However, just like any other MH algorithm, there is still a dilemmatic trading between their accuracy and the tracking time needed to find GMPP. This paper proposes a new MPPT algorithm by combining the CS algorithm with golden section search (GSS) to take beneficial features from both the algorithms. To validate the proposed algorithm, it is evaluated with various cases of partial shading. The simulation and experimental results show a noticeable performance improvement compared with the original CS algorithm and other MH algorithms.
期刊介绍:
The Canadian Journal of Electrical and Computer Engineering (ISSN-0840-8688), issued quarterly, has been publishing high-quality refereed scientific papers in all areas of electrical and computer engineering since 1976