Whale inspired algorithm based MPPT controllers for grid-connected solar photovoltaic system

Energy Procedia Pub Date : 2019-04-01 DOI:10.1016/j.egypro.2019.04.009

M.A. Ebrahim , Adham Osama , Khaled Mohamed Kotb , Fahmy Bendary

{"title":"Whale inspired algorithm based MPPT controllers for grid-connected solar photovoltaic system","authors":"M.A. Ebrahim , Adham Osama , Khaled Mohamed Kotb , Fahmy Bendary","doi":"10.1016/j.egypro.2019.04.009","DOIUrl":null,"url":null,"abstract":"<div><p>Over the past decades, meta-heuristic optimization techniques have become surprisingly very popular due to their flexibility and local optima avoidance capability. This paper uses the Whale Optimization Algorithm (WOA), a swarm-based technique to tune the Proportional-Integral (PI) based Maximum Power Point Tracking (MPPT) controllers of a grid-connected solar Photovoltaic (PV) system. The results of the PI-based Incremental Conductance (IC) MPPT technique are compared with both the conventional incremental conductance and the Perturb & Observe (P&O) MPPT techniques. Various modes of the PI controller are used. I, PI and Fractional order PI (FOPI) gain parameters are determined using WOA. Performance indices are applied to estimate the best parameters of the PI controller. This paper aims to show the effect of using PI-based MPPT controllers on enhancing the performance of a 400-kW grid-connected PV system. Simulation results show the capability of PI-based MPPT controllers on improving the performance of the PV system. It demonstrates the superiority of FOPI controllers over the other modes in enhancing system performance. The proposed work is simulated using MATLAB SIMULINK.</p></div>","PeriodicalId":11517,"journal":{"name":"Energy Procedia","volume":"162 ","pages":"Pages 77-86"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.egypro.2019.04.009","citationCount":"27","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy Procedia","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1876610219313682","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 27

Abstract

Over the past decades, meta-heuristic optimization techniques have become surprisingly very popular due to their flexibility and local optima avoidance capability. This paper uses the Whale Optimization Algorithm (WOA), a swarm-based technique to tune the Proportional-Integral (PI) based Maximum Power Point Tracking (MPPT) controllers of a grid-connected solar Photovoltaic (PV) system. The results of the PI-based Incremental Conductance (IC) MPPT technique are compared with both the conventional incremental conductance and the Perturb & Observe (P&O) MPPT techniques. Various modes of the PI controller are used. I, PI and Fractional order PI (FOPI) gain parameters are determined using WOA. Performance indices are applied to estimate the best parameters of the PI controller. This paper aims to show the effect of using PI-based MPPT controllers on enhancing the performance of a 400-kW grid-connected PV system. Simulation results show the capability of PI-based MPPT controllers on improving the performance of the PV system. It demonstrates the superiority of FOPI controllers over the other modes in enhancing system performance. The proposed work is simulated using MATLAB SIMULINK.

查看原文本刊更多论文

基于鲸鱼启发算法的并网太阳能光伏系统MPPT控制器

在过去的几十年里，元启发式优化技术由于其灵活性和局部最优避免能力而变得非常受欢迎。本文采用基于群体的鲸鱼优化算法(Whale Optimization Algorithm, WOA)对并网太阳能光伏系统中基于比例积分(PI)的最大功率点跟踪(MPPT)控制器进行了优化。将基于pi的增量电导(IC) MPPT技术的结果与传统的增量电导和微扰(Perturb &观察(P&O) MPPT技术。使用了PI控制器的各种模式。利用WOA确定I、PI和分数阶PI (FOPI)增益参数。应用性能指标来估计PI控制器的最佳参数。本文旨在展示使用基于pi的MPPT控制器对提高400千瓦并网光伏系统性能的影响。仿真结果表明，基于pi的MPPT控制器能够提高光伏系统的性能。验证了FOPI控制器在提高系统性能方面的优越性。利用MATLAB SIMULINK对所提出的工作进行了仿真。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Energy Procedia

自引率

0.00%

发文量