Open Access

ARTICLE

A Novel Aquila Optimizer Based PV Array Reconfiguration Scheme to Generate Maximum Energy under Partial Shading Condition

Dong An¹, Junqing Jia¹, Wenchao Cai¹, Deyu Yang¹, Chao Lv¹, Jiawei Zhu², Yingying Jiao^3,*

1 Inner Mongolia Power Research Institute, Huhhot, 010020, China
2 School of Information Engineering, Chang’an University, Xi’an, 710064, China
3 School of Information and Electrical Engineering, Shandong Jianzhu University, Jinan, 250101, China

* Corresponding Author: Yingying Jiao. Email:

(This article belongs to the Special Issue: Key Technologies of Renewable Energy Consumption and Optimal Operation under )

Energy Engineering 2022, 119(4), 1531-1545. https://doi.org/10.32604/ee.2022.019284

Received 14 September 2021; Accepted 24 February 2022; Issue published 23 May 2022

Abstract

This paper develops a real-time PV arrays maximum power harvesting scheme under partial shading condition (PSC) by reconfiguring PV arrays using Aquila optimizer (AO). AO is based on the natural behaviors of Aquila in capturing prey, which can choose the best hunting mechanism ingeniously and quickly by balancing the local exploitation and global exploration via four hunting methods of Aquila: choosing the searching area through high soar with the vertical stoop, exploring in different searching spaces through contour flight with quick glide attack, exploiting in convergence searching space through low flight with slow attack, and swooping through walk and grabbing prey. In general, PV arrays reconfiguration is a problem of discrete optimization, thus a series of discrete operations are adopted in AO to enhance its optimization performance. Simulation results based on 10 cases under PSCs show that the mismatched power loss obtained by AO is the smallest compared with genetic algorithm, particle swarm optimization, ant colony algorithm, grasshopper optimization algorithm, and butterfly optimization algorithm, which reduced by 4.34% against butterfly optimization algorithm.

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