模糊逻辑
普朗克
空格(标点符号)
计算机科学
物理
数学
控制理论(社会学)
数学优化
人工智能
天体物理学
控制(管理)
操作系统
作者
Adithya Ballaji,Ritesh Dash,Vivekanandan Subburaj,Kalvakurthi Jyotheeswara Reddy,Durgamadhab Swain,Sarat Chandra Swain
出处
期刊:IEEE Access
[Institute of Electrical and Electronics Engineers]
日期:2022-01-01
卷期号:10: 80764-80783
被引量:39
标识
DOI:10.1109/access.2022.3195036
摘要
Production of clean, green solar PV (SPV) power in developing countries now becomes a trend because of their economic and technical benefits. Therefore, generating maximum power out of the SPV is a key searchable area. The SPV must produce power at its terminal at their maximum possible power. To reach to the maximum possible power, maximum power point tracker is used in conjunction with SPV. Extracting maximum power from SPV under varying partial shading condition is one of the important factor in performance improvement of SPV. The characteristics of classical MPPT controller is not acceptable under variable shading condition. A clear distinction between global maxima power point from global minima using MPPT technique must be needed for extracting maximum power. This paper proposes a PO MPPT based particle swarm optimization with improved search space, optimised through Fuzzy Fokker Planck solution. The pre-defined search space has been introduced to provide fine tune to membership function used in Fuzzy logic controller. The partial shading performance has been examined under four different condition such as active partial shading, colour spectrum, dust level and GHG concentration. Both hardware and simulation studies has been carried out for the proposed techniques. The MATLAB simulation result and that of proposed MPPT, offer more and better performance in terms of algorithm convergence by enhancing the efficiency of system under varying shading condition.
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