基于遗传算法优化模糊控制器的太阳能光伏系统MPPT技术建模与仿真

Q2 Social Sciences
Afshan Ilyas, M. Ayyub, M. R. Khan
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引用次数: 1

摘要

研究了在不同环境条件下太阳能光伏发电系统最大功率点的智能跟踪技术。简要讨论了应用最广泛的扰动与观测(P&O)最大功率点跟踪(MPPT)技术,并与智能跟踪技术进行了比较。采用基于模糊逻辑控制器(FLC)的MPPT算法对SPV系统进行控制,并采用遗传算法对其各参数进行优化。将遗传算法优化后的FLC性能与P&O和基于模糊的MPPT技术进行了比较。利用MATLAB/simulink软件对MPPT控制器的不同阶段进行了设计。仿真结果表明,遗传算法优化后的FLC比基于P&O和模糊逻辑的MPPT控制器性能要好得多。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modelling and simulation of MPPT techniques for solar photovoltaic system using genetic algorithm optimised fuzzy logic controller
This paper focuses on the intelligent techniques used for tracking the maximum power point of the solar photovoltaic (SPV) system for varying environmental conditions. The most widely used perturb and observe (P&O) maximum power point tracking (MPPT) technique is discussed briefly for the comparison with the intelligent techniques. The paper proposes control technique for the SPV system by using fuzzy logic controller (FLC)-based MPPT algorithm and the optimisation of its various parameters by genetic algorithm (GA). The performance of the FLC optimised with GA is compared with the P&O and the fuzzy-based MPPT technique. MATLAB/simulink software is used to design the different stages of the MPPT controllers. Simulation results reported that GA optimised FLC perform much better than the P&O and fuzzy logic-based MPPT controllers.
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来源期刊
International Journal of Energy Technology and Policy
International Journal of Energy Technology and Policy Social Sciences-Geography, Planning and Development
CiteScore
1.50
自引率
0.00%
发文量
16
期刊介绍: The IJETP is a vehicle to provide a refereed and authoritative source of information in the field of energy technology and policy.
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