采用FS-MPC控制器,提出了一种基于元启发式算法的光伏系统并网新方法

Sami Meddour , Djamel Rahem , Ali Yahia Cherif , Walid Hachelfi , Laib Hichem
{"title":"采用FS-MPC控制器,提出了一种基于元启发式算法的光伏系统并网新方法","authors":"Sami Meddour ,&nbsp;Djamel Rahem ,&nbsp;Ali Yahia Cherif ,&nbsp;Walid Hachelfi ,&nbsp;Laib Hichem","doi":"10.1016/j.egypro.2019.04.007","DOIUrl":null,"url":null,"abstract":"<div><p>Since the ambient temperature and solar irradiance are not constant, and the P-V characteristic curve of a photovoltaic (PV) module is nonlinear, it is hard for a photovoltaic system to operate at the maximum power point (MPP). In fact, using a maximum power point tracking algorithm (MPPT) to reach the MPP is significant when the climatic conditions change during the day. This paper presents a novel approach for grid-connected PV systems based on a Practical Swarm Optimization (PSO) metaheuristic algorithm to ensure the MPPT functionality as well as generating the reference power for the DC-Bus voltage regulation. The proposed method is compared with the conventional MPPT method Perturb and Observe (P&amp;O) under different irradiance variations. The three-phase, two-level voltage source inverter (VSI) is controlled by a finite set model predictive controller (FS-MPC). The simulation results show that the proposed system is more efficient than the conventional method and has good dynamic performances.</p></div>","PeriodicalId":11517,"journal":{"name":"Energy Procedia","volume":"162 ","pages":"Pages 57-66"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.egypro.2019.04.007","citationCount":"10","resultStr":"{\"title\":\"A novel approach for PV system based on metaheuristic algorithm connected to the grid using FS-MPC controller\",\"authors\":\"Sami Meddour ,&nbsp;Djamel Rahem ,&nbsp;Ali Yahia Cherif ,&nbsp;Walid Hachelfi ,&nbsp;Laib Hichem\",\"doi\":\"10.1016/j.egypro.2019.04.007\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Since the ambient temperature and solar irradiance are not constant, and the P-V characteristic curve of a photovoltaic (PV) module is nonlinear, it is hard for a photovoltaic system to operate at the maximum power point (MPP). In fact, using a maximum power point tracking algorithm (MPPT) to reach the MPP is significant when the climatic conditions change during the day. This paper presents a novel approach for grid-connected PV systems based on a Practical Swarm Optimization (PSO) metaheuristic algorithm to ensure the MPPT functionality as well as generating the reference power for the DC-Bus voltage regulation. The proposed method is compared with the conventional MPPT method Perturb and Observe (P&amp;O) under different irradiance variations. The three-phase, two-level voltage source inverter (VSI) is controlled by a finite set model predictive controller (FS-MPC). The simulation results show that the proposed system is more efficient than the conventional method and has good dynamic performances.</p></div>\",\"PeriodicalId\":11517,\"journal\":{\"name\":\"Energy Procedia\",\"volume\":\"162 \",\"pages\":\"Pages 57-66\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.egypro.2019.04.007\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Energy Procedia\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1876610219313669\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy Procedia","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1876610219313669","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10

摘要

由于环境温度和太阳辐照度不是恒定的,光伏组件的P-V特性曲线是非线性的,光伏系统很难在最大功率点(MPP)运行。事实上,当白天的气候条件发生变化时,使用最大功率点跟踪算法(MPPT)来达到最大功率点是非常重要的。本文提出了一种基于实用群优化(PSO)元启发式算法的并网光伏系统的新方法,以确保最大功率的功能,并为直流母线电压调节产生参考功率。将该方法与传统的MPPT方法在不同辐照度变化下的扰动和观测(P&O)进行了比较。采用有限集模型预测控制器(FS-MPC)控制三相双电平电压源逆变器(VSI)。仿真结果表明,该系统比传统方法效率更高,具有良好的动态性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A novel approach for PV system based on metaheuristic algorithm connected to the grid using FS-MPC controller

Since the ambient temperature and solar irradiance are not constant, and the P-V characteristic curve of a photovoltaic (PV) module is nonlinear, it is hard for a photovoltaic system to operate at the maximum power point (MPP). In fact, using a maximum power point tracking algorithm (MPPT) to reach the MPP is significant when the climatic conditions change during the day. This paper presents a novel approach for grid-connected PV systems based on a Practical Swarm Optimization (PSO) metaheuristic algorithm to ensure the MPPT functionality as well as generating the reference power for the DC-Bus voltage regulation. The proposed method is compared with the conventional MPPT method Perturb and Observe (P&O) under different irradiance variations. The three-phase, two-level voltage source inverter (VSI) is controlled by a finite set model predictive controller (FS-MPC). The simulation results show that the proposed system is more efficient than the conventional method and has good dynamic performances.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信