{"title":"改进时不变最大功率点跟踪方法的性能","authors":"H. Galligan, S. Lyden","doi":"10.1109/AUPEC.2017.8282452","DOIUrl":null,"url":null,"abstract":"This paper presents an improved reinitialisation condition for time invariant maximum power point tracking (MPPT) methods used in photovoltaic (PV) systems experiencing partial shading conditions (PSC). Time invariant (MPPT) methods, such as Particle Swarm Optimisation (PSO), overcome the limitations of existing MPPT by tracking the global maximum power point (GMPP) of a PV system operating under PSC. However, due to the time invariant structure of these MPPT methods, they also require a reinitialisation condition to be defined for when a change in irradiance or temperature occurs. Testing was performed using simulations of a model built in Matlab/ Simulink, where the performance of existing and developed conditions was evaluated using test cases with changes in solar irradiance. Limitations of existing conditions were identified and a more robust reinitialisation condition developed. The developed reinitialisation condition used sentry particles to monitor the PV voltage range for changes in the measured power of any sentry. The developed condition had a 96 % rate of successful detection, as compared to as low as 68 % successful detection for existing methods, demonstrating improved performance and robustness.","PeriodicalId":155608,"journal":{"name":"2017 Australasian Universities Power Engineering Conference (AUPEC)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Improving the performance of time invariant maximum power point tracking methods\",\"authors\":\"H. Galligan, S. Lyden\",\"doi\":\"10.1109/AUPEC.2017.8282452\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an improved reinitialisation condition for time invariant maximum power point tracking (MPPT) methods used in photovoltaic (PV) systems experiencing partial shading conditions (PSC). Time invariant (MPPT) methods, such as Particle Swarm Optimisation (PSO), overcome the limitations of existing MPPT by tracking the global maximum power point (GMPP) of a PV system operating under PSC. However, due to the time invariant structure of these MPPT methods, they also require a reinitialisation condition to be defined for when a change in irradiance or temperature occurs. Testing was performed using simulations of a model built in Matlab/ Simulink, where the performance of existing and developed conditions was evaluated using test cases with changes in solar irradiance. Limitations of existing conditions were identified and a more robust reinitialisation condition developed. The developed reinitialisation condition used sentry particles to monitor the PV voltage range for changes in the measured power of any sentry. The developed condition had a 96 % rate of successful detection, as compared to as low as 68 % successful detection for existing methods, demonstrating improved performance and robustness.\",\"PeriodicalId\":155608,\"journal\":{\"name\":\"2017 Australasian Universities Power Engineering Conference (AUPEC)\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 Australasian Universities Power Engineering Conference (AUPEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AUPEC.2017.8282452\",\"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 Australasian Universities Power Engineering Conference (AUPEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AUPEC.2017.8282452","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Improving the performance of time invariant maximum power point tracking methods
This paper presents an improved reinitialisation condition for time invariant maximum power point tracking (MPPT) methods used in photovoltaic (PV) systems experiencing partial shading conditions (PSC). Time invariant (MPPT) methods, such as Particle Swarm Optimisation (PSO), overcome the limitations of existing MPPT by tracking the global maximum power point (GMPP) of a PV system operating under PSC. However, due to the time invariant structure of these MPPT methods, they also require a reinitialisation condition to be defined for when a change in irradiance or temperature occurs. Testing was performed using simulations of a model built in Matlab/ Simulink, where the performance of existing and developed conditions was evaluated using test cases with changes in solar irradiance. Limitations of existing conditions were identified and a more robust reinitialisation condition developed. The developed reinitialisation condition used sentry particles to monitor the PV voltage range for changes in the measured power of any sentry. The developed condition had a 96 % rate of successful detection, as compared to as low as 68 % successful detection for existing methods, demonstrating improved performance and robustness.