GWO- and SSA-Tuned PID Control for Frequency Regulation in Multi-Area PowerNetwork Integrated with Plug-in Electric Vehicle

IF 2.4 Q2 MULTIDISCIPLINARY SCIENCES

Smart Science Pub Date : 2023-10-24 DOI:10.1080/23080477.2023.2270668

Gunjan Chorasiya, Vinod Kumar, Sathans Suhag

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引用次数: 0

Abstract

ABSTRACTThe Plug-in Electric Vehicles (PEVs) can be influential in containing power system frequency fluctuations. This study, therefore, investigates the efficacy of frequency regulation for PEV-integrated multi-area power network using Grey Wolf Optimizer (GWO) and Salp Swarm Algorithm (SSA) optimized Proportional-Integral-Derivative (PID) control. Instant investigation not only brings out the relative competence of GWO and SSA but also examines the impact of PEV in improving the system performance. The varying operating conditions are realized by subjecting the system to step and random load variations in either or both of the areas. With the proposed control scheme and involvement of PEV, system frequency and tie-line power excursions settle quicker with their peak swings also getting restricted to a lower value, while the oscillations are arrested as well to a great extent. Further, it’s the SSA that shows its superiority over GWO as per the simulation results executed in MATLAB.KEYWORDS: Multi-area power systemSalp Swarm Algorithm (SSA)frequency excursionsGrey Wolf Optimizer (GWO)Plug-in Electric Vehicles (PEVs) Disclosure statementNo potential conflict of interest was reported by the author(s).

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插电式电动车集成多区域电网频率调节的GWO和ssa调谐PID控制

摘要插电式电动汽车对抑制电力系统频率波动具有重要影响。因此，本研究利用灰狼优化器(GWO)和Salp群算法(SSA)优化的比例-积分-导数(PID)控制来研究pev集成多区域电网的频率调节效果。即时调查不仅揭示了GWO和SSA的相对能力，而且还检验了PEV对提高系统性能的影响。不同的运行条件是通过使系统在其中一个或两个区域承受阶跃和随机负载变化来实现的。在该控制方案和PEV的参与下，系统频率和配线功率漂移更快地稳定下来，其峰值摆动也被限制在一个较低的值，同时振荡也得到了很大程度的抑制。此外，在MATLAB中执行的仿真结果表明，SSA比GWO更具优越性。关键词:多区域电力系统salp群算法(SSA)频率漂移灰狼优化器(GWO)插电式电动汽车(pev)披露声明作者未报告潜在的利益冲突。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Smart Science Engineering-Engineering (all)

CiteScore

4.70

自引率

4.30%

发文量

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