J. Camarillo-Peñaranda, Daniel González Montoya, C. Ramos-Paja
{"title":"Reconfiguration of Photovoltaic Arrays Based on a GPU-Accelerated Exhaustive Search Algorithm","authors":"J. Camarillo-Peñaranda, Daniel González Montoya, C. Ramos-Paja","doi":"10.1109/APCASE.2015.58","DOIUrl":null,"url":null,"abstract":"This paper proposes a parallel exhaustive search algorithm to find the best electrical configuration of PV arrays. This information is required to reconfigure, in real-time, the PV array in order to mitigate the power losses caused by partial shading and other mismatching conditions. The algorithm is based on a parameterized model of the PV system, and it is designed to run in commercial graphic processing units (GPU). This GPU-accelerated approach provides a significant reduction in the processing time compared with the classical CPU-only serial algorithm. Hence, the proposed GPU-based reconfiguration enables to reconfigure, in real-time, PV systems much larger contrasted with the CPU-only approach.","PeriodicalId":235698,"journal":{"name":"2015 Asia-Pacific Conference on Computer Aided System Engineering","volume":"352 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Asia-Pacific Conference on Computer Aided System Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APCASE.2015.58","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper proposes a parallel exhaustive search algorithm to find the best electrical configuration of PV arrays. This information is required to reconfigure, in real-time, the PV array in order to mitigate the power losses caused by partial shading and other mismatching conditions. The algorithm is based on a parameterized model of the PV system, and it is designed to run in commercial graphic processing units (GPU). This GPU-accelerated approach provides a significant reduction in the processing time compared with the classical CPU-only serial algorithm. Hence, the proposed GPU-based reconfiguration enables to reconfigure, in real-time, PV systems much larger contrasted with the CPU-only approach.