Optimized Fuzzy Controller for MPPT of Grid-connected PV Systems in Rapidly Changing Atmospheric Conditions

被引：79
作者：
Dehghani, Majid [1 ]
Taghipour, Mohammad [1 ]
Gharehpetian, Gevork B. [1 ]
Abedi, Mehrdad [1 ]
机构：
[1] Amirkabir Univ Technol, Dept Elect Engn, Tehran, Iran
来源：
JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY | 2021年 / 9卷 / 02期
关键词：
Maximum power point trackers; Genetic algorithms; Fuzzy systems; Fuzzy logic; Power measurement; Temperature; Photovoltaic (PV); maximum power point tracking (MPPT); fuzzy; particle swarm optimization (PSO); genetic algorithm (GA); incremental conductance; perturb and observe; MAXIMUM POWER POINT; PHOTOVOLTAIC SYSTEMS; LOGIC CONTROL; TRACKING; ALGORITHM; DESIGN; MODEL; SIMULATION; NETWORK;
D O I：
10.35833/MPCE.2019.000086
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Due to nonlinear behavior of power production of photovoltaic (PV) systems., it is necessary to apply the maximum power point tracking (MPPT) techniques to generate the maximum power. The conventional MPPT methods do not function properly in rapidly changing atmospheric conditions. In this study., a fuzzy logic controller (FLC) optimized by a combination of particle swarm optimization (PSO) and genetic algorithm (GA) is proposed to obtain the maximum power point (MPP). The proposed FLC uses the ratio of power variations to voltage variations and the derivative of power variations to voltage variations as inputs and uses the duty cycle as the output. The range of changes in fuzzy membership functions and fuzzy rules are proposed as an optimization problem optimized by the PSO-GA. The proposed design is validated for MPPT of a PV system using MATLAB/Simulink software. The results indicate a better performance of the proposed FLC compared to the common methods.
引用
收藏
页码：376 / 383
页数：8
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