{"title":"Impact analysis of capacitive energy storage integration on load frequency control performance of microgrids employing a new dual-stage controller","authors":"Bhuvnesh Khokhar , Krishna Pal Singh Parmar","doi":"10.1016/j.isatra.2025.04.003","DOIUrl":null,"url":null,"abstract":"<div><div>A microgrid (MG) with inherent low inertia and renewable energy sources (RES)-based generators may encounter difficulties in maintaining frequency stability due to load changes. In order to mitigate frequency stability concerns, it is imperative to use energy storage units (ESUs). Objective of this study is to analyze the impact of capacitive energy storage unit (CESU) integration on the load frequency control (LFC) performance of two distinct MG systems. A new dual-stage <span><math><mrow><msup><mrow><mi>PI</mi></mrow><mrow><mi>λ</mi></mrow></msup><mo>−</mo><mrow><mo>(</mo><mn>1</mn><mo>+</mo><msup><mrow><mi>PD</mi></mrow><mrow><mi>μ</mi></mrow></msup><mi>F</mi><mo>)</mo></mrow></mrow></math></span> controller is proposed as a secondary controller for the LFC study. Parameters of the controller are optimized employing a recently developed arithmetic optimization algorithm (AOA). Performance of the suggested control approach is evaluated against several standard control approaches. Simulation findings demonstrate that with CESU integration the suggested controller markedly enhances frequency and tie-line power deviation responses and their transient characteristics for both the MG systems. A maximum improvement of 98.50% in peak overshoot, 94.88% in peak undershoot, and 77.18% in settling time is observed with the suggested control approach. This study further justifies the robustness of the proposed control approach against the MG systems parameter variations, impact of CESU integration through statistical analysis, small signal stability of both the MG systems, and convergence performance of the AOA.</div></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"162 ","pages":"Pages 162-178"},"PeriodicalIF":6.3000,"publicationDate":"2025-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ISA transactions","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0019057825001806","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
A microgrid (MG) with inherent low inertia and renewable energy sources (RES)-based generators may encounter difficulties in maintaining frequency stability due to load changes. In order to mitigate frequency stability concerns, it is imperative to use energy storage units (ESUs). Objective of this study is to analyze the impact of capacitive energy storage unit (CESU) integration on the load frequency control (LFC) performance of two distinct MG systems. A new dual-stage controller is proposed as a secondary controller for the LFC study. Parameters of the controller are optimized employing a recently developed arithmetic optimization algorithm (AOA). Performance of the suggested control approach is evaluated against several standard control approaches. Simulation findings demonstrate that with CESU integration the suggested controller markedly enhances frequency and tie-line power deviation responses and their transient characteristics for both the MG systems. A maximum improvement of 98.50% in peak overshoot, 94.88% in peak undershoot, and 77.18% in settling time is observed with the suggested control approach. This study further justifies the robustness of the proposed control approach against the MG systems parameter variations, impact of CESU integration through statistical analysis, small signal stability of both the MG systems, and convergence performance of the AOA.
期刊介绍:
ISA Transactions serves as a platform for showcasing advancements in measurement and automation, catering to both industrial practitioners and applied researchers. It covers a wide array of topics within measurement, including sensors, signal processing, data analysis, and fault detection, supported by techniques such as artificial intelligence and communication systems. Automation topics encompass control strategies, modelling, system reliability, and maintenance, alongside optimization and human-machine interaction. The journal targets research and development professionals in control systems, process instrumentation, and automation from academia and industry.