{"title":"部分遮阳条件下基于粒子群算法的MPPT光伏设计","authors":"Efendi S Wirateruna, Annisa Fitri Ayu Millenia","doi":"10.25139/ijair.v4i1.4327","DOIUrl":null,"url":null,"abstract":"\n \n \n \nFossil energy sources experience a decrease each year when the demand increases significantly. In the case of environmental issues, renewable energy sources (RES) can be energy alternatives. The photovoltaic module is RES with unique characteristics, especially partial shading conditions. This condition leads to the PV characteristic curve experiencing multiple peaks. The paper conducted the simulation of the PV solar panel module using MATLAB Simulink. The Maximum Power Point Tracking (MPPT) PV is also described based on a particle swarm optimization (PSO) algorithm. The proposed algorithm can address multiple peak curve problems due to partial shading conditions. For comparison, the conventional algorithm, perturb & observe, is presented. The PV module is divided into three group cells with irradiance differences for each group to illustrate the partial shading condition. The result shows that the PSO algorithm guarantees optimal and fast response for the operating PowerPoint. It needs about 0.04 seconds to maintain at the optimal power point, 129 Watt, compared with the perturb and observe algorithm performance that only kept at the lower operating power point, 67 Watt at 0.06 second. Thus, the PSO algorithm can tackle the partial shading condition with a fast response to maintain the maximum PowerPoint. Therefore, the PSO algorithm is the proper solution for tracking the optimum operating power point under partial shading conditions. \n \n \n \n","PeriodicalId":208192,"journal":{"name":"International Journal of Artificial Intelligence & Robotics (IJAIR)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Design of MPPT PV using Particle Swarm Optimization Algorithm under Partial Shading Condition\",\"authors\":\"Efendi S Wirateruna, Annisa Fitri Ayu Millenia\",\"doi\":\"10.25139/ijair.v4i1.4327\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n \\n \\n \\nFossil energy sources experience a decrease each year when the demand increases significantly. In the case of environmental issues, renewable energy sources (RES) can be energy alternatives. The photovoltaic module is RES with unique characteristics, especially partial shading conditions. This condition leads to the PV characteristic curve experiencing multiple peaks. The paper conducted the simulation of the PV solar panel module using MATLAB Simulink. The Maximum Power Point Tracking (MPPT) PV is also described based on a particle swarm optimization (PSO) algorithm. The proposed algorithm can address multiple peak curve problems due to partial shading conditions. For comparison, the conventional algorithm, perturb & observe, is presented. The PV module is divided into three group cells with irradiance differences for each group to illustrate the partial shading condition. The result shows that the PSO algorithm guarantees optimal and fast response for the operating PowerPoint. It needs about 0.04 seconds to maintain at the optimal power point, 129 Watt, compared with the perturb and observe algorithm performance that only kept at the lower operating power point, 67 Watt at 0.06 second. Thus, the PSO algorithm can tackle the partial shading condition with a fast response to maintain the maximum PowerPoint. Therefore, the PSO algorithm is the proper solution for tracking the optimum operating power point under partial shading conditions. \\n \\n \\n \\n\",\"PeriodicalId\":208192,\"journal\":{\"name\":\"International Journal of Artificial Intelligence & Robotics (IJAIR)\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-05-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Artificial Intelligence & Robotics (IJAIR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.25139/ijair.v4i1.4327\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Artificial Intelligence & Robotics (IJAIR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.25139/ijair.v4i1.4327","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Design of MPPT PV using Particle Swarm Optimization Algorithm under Partial Shading Condition
Fossil energy sources experience a decrease each year when the demand increases significantly. In the case of environmental issues, renewable energy sources (RES) can be energy alternatives. The photovoltaic module is RES with unique characteristics, especially partial shading conditions. This condition leads to the PV characteristic curve experiencing multiple peaks. The paper conducted the simulation of the PV solar panel module using MATLAB Simulink. The Maximum Power Point Tracking (MPPT) PV is also described based on a particle swarm optimization (PSO) algorithm. The proposed algorithm can address multiple peak curve problems due to partial shading conditions. For comparison, the conventional algorithm, perturb & observe, is presented. The PV module is divided into three group cells with irradiance differences for each group to illustrate the partial shading condition. The result shows that the PSO algorithm guarantees optimal and fast response for the operating PowerPoint. It needs about 0.04 seconds to maintain at the optimal power point, 129 Watt, compared with the perturb and observe algorithm performance that only kept at the lower operating power point, 67 Watt at 0.06 second. Thus, the PSO algorithm can tackle the partial shading condition with a fast response to maintain the maximum PowerPoint. Therefore, the PSO algorithm is the proper solution for tracking the optimum operating power point under partial shading conditions.