{"title":"基于卡尔曼滤波的直流微电网光伏能源最大功率点跟踪","authors":"H. AbdEl-Gawad, V. Sood","doi":"10.1109/EPEC.2017.8286161","DOIUrl":null,"url":null,"abstract":"The variable output from a PV array needs to be maximized with a MPPT algorithm. Numerous algorithms exist but have some difficulties when faced with rapid changes in environmental conditions that affect the PV output. In this paper a novel algorithm using a Kalman Filter is developed. Matlab simulations show that the algorithm is capable of tracking the PV output for maximizing the power. Comparison with the traditional Perturb and Observe (P&O) MPPT method show the superior performance of the KF algorithm.","PeriodicalId":141250,"journal":{"name":"2017 IEEE Electrical Power and Energy Conference (EPEC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Kalman filter-based maximum power point tracking for PV energy resources supplying DC microgrid\",\"authors\":\"H. AbdEl-Gawad, V. Sood\",\"doi\":\"10.1109/EPEC.2017.8286161\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The variable output from a PV array needs to be maximized with a MPPT algorithm. Numerous algorithms exist but have some difficulties when faced with rapid changes in environmental conditions that affect the PV output. In this paper a novel algorithm using a Kalman Filter is developed. Matlab simulations show that the algorithm is capable of tracking the PV output for maximizing the power. Comparison with the traditional Perturb and Observe (P&O) MPPT method show the superior performance of the KF algorithm.\",\"PeriodicalId\":141250,\"journal\":{\"name\":\"2017 IEEE Electrical Power and Energy Conference (EPEC)\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE Electrical Power and Energy Conference (EPEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EPEC.2017.8286161\",\"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 Electrical Power and Energy Conference (EPEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EPEC.2017.8286161","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Kalman filter-based maximum power point tracking for PV energy resources supplying DC microgrid
The variable output from a PV array needs to be maximized with a MPPT algorithm. Numerous algorithms exist but have some difficulties when faced with rapid changes in environmental conditions that affect the PV output. In this paper a novel algorithm using a Kalman Filter is developed. Matlab simulations show that the algorithm is capable of tracking the PV output for maximizing the power. Comparison with the traditional Perturb and Observe (P&O) MPPT method show the superior performance of the KF algorithm.
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