{"title":"GMPP跟踪算法在不同辐照和温度条件下的概率分布","authors":"K. Cao, V. Boitier","doi":"10.1109/PowerMEMS54003.2021.9658331","DOIUrl":null,"url":null,"abstract":"A photovoltaic (PV) array having multiple cells in series with bypass diodes may exhibit multiple power peaks under uneven irradiation, therefore an algorithm is required to reach the global maximum power point (GMPP). While a lot of methods for GMPP tracking have been proposed in the literature, they are too complex for a system around 1–100W operating under partial shading and fast-varying irradiation conditions of around 100ms. This paper first highlights a rapid and efficient mathematical simulation of the PV array using MATLAB to find the probability distribution of GMPP under multiple irradiation conditions and different temperatures. The resulting GMPP distribution for an example of 4 PV macro cells with 4 bypass diodes in series is presented, both under the assumption of equal probability as well as a real-world operating condition. From the obtained result, we simulated a simple GMPPT algorithm capable of predicting which zone GMPP is located up to 96% of the time for both distributions.","PeriodicalId":165158,"journal":{"name":"2021 IEEE 20th International Conference on Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Probability distribution of GMPP under different irradiation and temperature conditions for GMPP tracking algorithm\",\"authors\":\"K. Cao, V. Boitier\",\"doi\":\"10.1109/PowerMEMS54003.2021.9658331\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A photovoltaic (PV) array having multiple cells in series with bypass diodes may exhibit multiple power peaks under uneven irradiation, therefore an algorithm is required to reach the global maximum power point (GMPP). While a lot of methods for GMPP tracking have been proposed in the literature, they are too complex for a system around 1–100W operating under partial shading and fast-varying irradiation conditions of around 100ms. This paper first highlights a rapid and efficient mathematical simulation of the PV array using MATLAB to find the probability distribution of GMPP under multiple irradiation conditions and different temperatures. The resulting GMPP distribution for an example of 4 PV macro cells with 4 bypass diodes in series is presented, both under the assumption of equal probability as well as a real-world operating condition. From the obtained result, we simulated a simple GMPPT algorithm capable of predicting which zone GMPP is located up to 96% of the time for both distributions.\",\"PeriodicalId\":165158,\"journal\":{\"name\":\"2021 IEEE 20th International Conference on Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS)\",\"volume\":\"45 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 20th International Conference on Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PowerMEMS54003.2021.9658331\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 20th International Conference on Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PowerMEMS54003.2021.9658331","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Probability distribution of GMPP under different irradiation and temperature conditions for GMPP tracking algorithm
A photovoltaic (PV) array having multiple cells in series with bypass diodes may exhibit multiple power peaks under uneven irradiation, therefore an algorithm is required to reach the global maximum power point (GMPP). While a lot of methods for GMPP tracking have been proposed in the literature, they are too complex for a system around 1–100W operating under partial shading and fast-varying irradiation conditions of around 100ms. This paper first highlights a rapid and efficient mathematical simulation of the PV array using MATLAB to find the probability distribution of GMPP under multiple irradiation conditions and different temperatures. The resulting GMPP distribution for an example of 4 PV macro cells with 4 bypass diodes in series is presented, both under the assumption of equal probability as well as a real-world operating condition. From the obtained result, we simulated a simple GMPPT algorithm capable of predicting which zone GMPP is located up to 96% of the time for both distributions.