BWO Strategy for Power Quality Improvement in HRES Grid-Connected DPFC System

IF 2.4 Q2 MULTIDISCIPLINARY SCIENCES Smart Science Pub Date : 2021-05-05 DOI:10.1080/23080477.2021.1920142
S. B
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引用次数: 2

Abstract

ABSTRACT Hybrid renewable energy sources (HRES) integrated with the grid connection is tremendously increasing its importance in the current scenario to meet the huge demand for electrical power. This integration is further decreasing the usage of fossil fuel and reducing the problems related to the environment. HRES such as the photovoltaic (PV) system, wind turbine (WT), and the battery energy storage system (BESS) in grid-connected systems are causing power quality (PQ). To overcome such issues in the HRES system, black widow optimization (BWO) with distributed power flow controller (DPFC) is proposed. DPFC is one among the various custom power devices, which are effectively used to mitigate the PQ issues, such as voltage/current sag, swell, and total harmonic distortions. Fractional order PID controller is designed to drive DPFC whose control parameters are generated with BWO technique. The analysis is compared with various techniques like PI, P&O, GSA, ASO, RFA, EVORFA, and BWO and obtained the best results. The test system is simulated in MATLAB/Simulink software. GRAPHICAL ABSTRACT
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改善HRES并网DPFC系统电能质量的BWO策略
混合可再生能源(HRES)与电网连接集成在当前场景中,以满足巨大的电力需求,其重要性大大增加。这种整合进一步减少了化石燃料的使用,减少了与环境有关的问题。并网系统中的光伏(PV)系统、风力发电机组(WT)、电池储能系统(BESS)等HRES引起了电能质量(PQ)问题。为了克服这些问题,提出了基于分布式潮流控制器(DPFC)的黑寡妇优化(BWO)。DPFC是各种定制功率器件中的一种,可有效地用于缓解PQ问题,如电压/电流凹陷、膨胀和总谐波失真。设计了分数阶PID控制器来驱动DPFC, DPFC的控制参数由BWO技术生成。分析比较了PI、P&O、GSA、ASO、RFA、EVORFA、BWO等多种技术,获得了最佳效果。在MATLAB/Simulink软件中对测试系统进行了仿真。图形抽象
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来源期刊
Smart Science
Smart Science Engineering-Engineering (all)
CiteScore
4.70
自引率
4.30%
发文量
21
期刊介绍: Smart Science (ISSN 2308-0477) is an international, peer-reviewed journal that publishes significant original scientific researches, and reviews and analyses of current research and science policy. We welcome submissions of high quality papers from all fields of science and from any source. Articles of an interdisciplinary nature are particularly welcomed. Smart Science aims to be among the top multidisciplinary journals covering a broad spectrum of smart topics in the fields of materials science, chemistry, physics, engineering, medicine, and biology. Smart Science is currently focusing on the topics of Smart Manufacturing (CPS, IoT and AI) for Industry 4.0, Smart Energy and Smart Chemistry and Materials. Other specific research areas covered by the journal include, but are not limited to: 1. Smart Science in the Future 2. Smart Manufacturing: -Cyber-Physical System (CPS) -Internet of Things (IoT) and Internet of Brain (IoB) -Artificial Intelligence -Smart Computing -Smart Design/Machine -Smart Sensing -Smart Information and Networks 3. Smart Energy and Thermal/Fluidic Science 4. Smart Chemistry and Materials
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