A grey wolf optimized fuzzy logic based MPPT for shaded solar photovoltaic systems in microgrids

被引：62

作者：

Laxman, Bhukya ^{[1
]}

Annamraju, Anil ^{[1
]}

Srikanth, Nandiraju Venkata ^{[1
]}

机构：

[1] Natl Inst Technol, Dept Elect Engn, Warangal 506004, Telangana, India

来源：

INTERNATIONAL JOURNAL OF HYDROGEN ENERGY | 2021年 / 46卷 / 18期

关键词：

Grey wolf optimization; Solar photovoltaic system; Adaptive fuzzy logic controller; Maximum power point tracker; Partial shading condition; POWER POINT TRACKING; RENEWABLE-ENERGY-SOURCES; CONTROLLER;

D O I：

10.1016/j.ijhydene.2020.12.158

中图分类号：

O64 [物理化学（理论化学）、化学物理学];

学科分类号：

070304 ; 081704 ;

摘要：

As the solar PV system (SPVS) suffered from an unavoidable complication that it has nonlinearity in I-V curves, the optimum maximum power point (MPP) measurement is difficult under fluctuating climatic conditions. For maximizing SPVS output power, MPP tracking (MPPT) controllers are used. In this paper, a new adaptive fuzzy logic controller (AFLC) based MPPT technique is proposed. In this proposed AFLC, the membership functions (MFs) are optimized using the Grey Wolf Optimization (GWO) technique to generate the optimal duty cycle for MPPT. Four shading patterns are used to experiment with the performance of the proposed AFLC. The proposed approach tracks the global MPP for all shading conditions and also enhances the tracking speed and tracking efficiency with reduced oscillations. The effectiveness and robustness of proposed AFLC based tracker results over P&O and FLC are validated using Matlab/Simulink environment. The proposed AFLC overcome the drawbacks of the classical P&O, and FLC approaches. (c) 2020 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

引用

页码：10653 / 10665

页数：13

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