A Novel Nature-Inspired Maximum Power Point Tracking (MPPT) Controller Based on SSA-GWO Algorithm for Partially Shaded Photovoltaic Systems

Yihao Wan,Xinze Xi,Chen Zheng,Lin Zhou,Qianjin Zhang,Mingxuan Mao

doi:10.3390/electronics8060680

Yihao Wan, Xinze Xi + Show 4 more

Open Access

https://doi.org/10.3390/electronics8060680

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Journal: Electronics	Publication Date: Jun 15, 2019
Citations: 39	License type: CC BY 4.0

Affiliation: Chongqing University

Abstract

To overcome the real-time problem of maximum power point tracking (MPPT) for partially shaded photovoltaic (PV) systems, a novel nature-inspired MPPT controller with fast convergence and high accuracy is proposed in this paper. The proposed MPPT controller is achieved by combining salp swarm algorithm (SSA) with grey wolf optimizer (GWO) (namely, SSA-GWO). The leader structure of the GWO algorithm is introduced into the basic SSA algorithm to enhance the global search capability. Numerical simulation on 13 benchmark functions was done to evaluate the proposed SSA-GWO algorithm. Finally, the MPPT performance on PV system with the proposed SSA-GWO algorithm under static and dynamic partial shading conditions was investigated and compared with conventional MPPT algorithms. The quantitative and simulation results validated the effectiveness and superiority of the proposed method.

Highlights

Over the past decades, the development of renewable energy, especially solar energy, has gained much attention worldwide due to its sustainability, maintenance-free and noise-free characteristics, etc.the operation of photovoltaic (PV) systems is highly dependent on external factors, such as solar irradiance and temperature, which has huge implications for the output of PV systems
When the PV array is exposed to non-uniform radiation, i.e., partial shading conditions (PSCs), the P-V characteristic curve would exhibit multiple peaks and the conventional maximum power point tracking (MPPT) methods mentioned above will be trapped in local maximum power point (LMPP), resulting in high power losses of the PV system [5]
The proposed algorithm still maintains the adaptive mechanism of the basic salp swarm algorithm (SSA) algorithm, which is able to avoid stagnating in local best solutions

Summary

Introduction

The development of renewable energy, especially solar energy, has gained much attention worldwide due to its sustainability, maintenance-free and noise-free characteristics, etc.the operation of photovoltaic (PV) systems is highly dependent on external factors, such as solar irradiance and temperature, which has huge implications for the output of PV systems. Maximum power point tracking (MPPT) controllers are essential to maintain efficient operation of PV modules in a PV system [1]. In the case of uniform irradiance, the PV array characteristics curve exhibits single peak which can be tracked using conventional MPPT algorithms such as Perturb & Observe (P&O) method [2], Incremental Conductance (IC) method [3], and Hill Climbing method [4]. When the PV array is exposed to non-uniform radiation, i.e., partial shading conditions (PSCs), the P-V characteristic curve would exhibit multiple peaks and the conventional MPPT methods mentioned above will be trapped in local maximum power point (LMPP), resulting in high power losses of the PV system [5]

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