基于算术优化算法的光伏系统最大功率点跟踪并网。

Arithmetic optimization algorithm based maximum power point tracking for grid-connected photovoltaic system.

机构信息

Department of Electrical Engineering, Faculty of Engineering at Shoubra, Benha University, Cairo, Egypt.

Department of Electrical Engineering, El Shorouk High Institute of Engineering, Cairo, Egypt.

出版信息

Sci Rep. 2023 Apr 12;13(1):5961. doi: 10.1038/s41598-023-32793-0.

DOI:10.1038/s41598-023-32793-0

PMID:37045948

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10097651/

Abstract

This paper suggests an optimal maximum power point tracking (MPPT) control scheme for a grid-connected photovoltaic (PV) system using the arithmetic optimization algorithm (AOA). The parameters of the proportional-integral (PI) controller-based incremental conductance (IC) MPPT are optimally selected using AOA. To accomplish this study, a 100-kW benchmark PV system connected to a medium distribution utility is constructed and analyzed employing MATLAB/SIMULINK. The optimization framework seeks to minimize four standard benchmark performance indices, then select the best of the best among them. To verify the efficacy of the recommended methodology, a comprehensive comparison is conducted between AOA-based PI-IC-MPPT, modified incremental conductance MPPT (MIC), grey wolf optimization (GWO), genetic algorithm (GA), and particle swarm optimization (PSO)-based MPPT. The proposed control approach has achieved a reduction of 61, 3, 4.5, and 26.9% in the rise time and a decrease of 94, 84.7, 86.6, and 79.3% in the settling time compared with MIC, GWO, GA, and PSO in extracting MPPT of the proposed system, respectively.

摘要

本文提出了一种使用算术优化算法 (AOA) 的并网光伏 (PV) 系统最大功率点跟踪 (MPPT) 的优化控制方案。使用 AOA 对基于比例积分 (PI) 控制器的增量电导 (IC) MPPT 的参数进行了优化选择。为了完成这项研究，构建并分析了一个连接到中型配电公用事业的 100kW 基准 PV 系统，使用 MATLAB/SIMULINK。优化框架旨在最小化四个标准基准性能指标，然后从中选择最佳指标。为了验证所提出方法的有效性，对基于 AOA 的 PI-IC-MPPT、改进的增量电导 MPPT (MIC)、灰狼优化 (GWO)、遗传算法 (GA) 和基于粒子群优化 (PSO) 的 MPPT 进行了全面比较。与 MIC、GWO、GA 和 PSO 相比，所提出的控制方法在提取所提出系统的 MPPT 时，分别将上升时间缩短了 61%、3%、4.5%和 26.9%，将稳定时间缩短了 94%、84.7%、86.6%和 79.3%。