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<p>Strong electrical connections between countries and regions are essential for large-scale energy investments and for mitigating power deficits caused by generation and demand uncertainties. However, interconnected power systems are highly vulnerable to load disturbances, which can lead to significant frequency deviations and undesired power exchanges, threatening system stability and operational reliability. Load frequency control (LFC) plays a critical role in maintaining stable frequency and tie-line power in such interconnected environments. Although metaheuristics have been widely applied for LFC controller design, many existing approaches suffer from limited population diversity, resulting in premature convergence and reduced solution accuracy. To address these limitations, this paper suggests memory-based political optimizer (mPO) to optimize fractional-order proportional integral derivative (PID) controller for LFC in multi-sources, multi-interconnected microgrids. The optimal-guidance random-based exploration method and memory-based election campaign strategy are proposed to prevent local minima and achieve exploration/exploitation balance. Several CEC benchmarks have been analyzed to assess the suggested mPO in comparison to other approaches of traditional PO, sand cat swarm optimization algorithm (SCSO), Chernobyl disaster optimizer (CDO), smell agent optimization (SAO), sinh cosh optimizer (SCHO), grey wolf optimizer (GWO), and sine cosine algorithm (SCA). Two and four interconnected microgrids are the two systems under consideration. Each microgrid includes thermal, hydro, and wind turbines (WT) in addition to energy storage systems (ESSs) of redox flow batteries (RFB) and hydrogen aqua-electrolyzer fuel cells (HAFC). The integral time absolute error (ITAE) of the frequency and exchanged power deviations is the fitness function to be minimized under load disruption. Numerous topologies of the interconnected system as well as different load disruptions are analyzed. In the presence of the HAFC-RFB storage system, the proposed mPO decreased the fitness value in the two-interconnected system by 8.023% as compared to the traditional one. However, in the case of four interconnected microgrids, it decreased the ITAE by 20.071% instead of the PO. The obtained findings validated the mPO-optimized recommended controller’s superiority over the others.</p>

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Optimal fractional order PID-load frequency controller for multi-interconnected microgrids including renewable energy and storage system

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月20日

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  • Ahmed Alshahir,
  • Ahmed Fathy,
  • Fatma A. Hashim,
  • Kaiguang Wang,
  • Shahr Alshahr,
  • Hossam Hassan Ali

摘要

Strong electrical connections between countries and regions are essential for large-scale energy investments and for mitigating power deficits caused by generation and demand uncertainties. However, interconnected power systems are highly vulnerable to load disturbances, which can lead to significant frequency deviations and undesired power exchanges, threatening system stability and operational reliability. Load frequency control (LFC) plays a critical role in maintaining stable frequency and tie-line power in such interconnected environments. Although metaheuristics have been widely applied for LFC controller design, many existing approaches suffer from limited population diversity, resulting in premature convergence and reduced solution accuracy. To address these limitations, this paper suggests memory-based political optimizer (mPO) to optimize fractional-order proportional integral derivative (PID) controller for LFC in multi-sources, multi-interconnected microgrids. The optimal-guidance random-based exploration method and memory-based election campaign strategy are proposed to prevent local minima and achieve exploration/exploitation balance. Several CEC benchmarks have been analyzed to assess the suggested mPO in comparison to other approaches of traditional PO, sand cat swarm optimization algorithm (SCSO), Chernobyl disaster optimizer (CDO), smell agent optimization (SAO), sinh cosh optimizer (SCHO), grey wolf optimizer (GWO), and sine cosine algorithm (SCA). Two and four interconnected microgrids are the two systems under consideration. Each microgrid includes thermal, hydro, and wind turbines (WT) in addition to energy storage systems (ESSs) of redox flow batteries (RFB) and hydrogen aqua-electrolyzer fuel cells (HAFC). The integral time absolute error (ITAE) of the frequency and exchanged power deviations is the fitness function to be minimized under load disruption. Numerous topologies of the interconnected system as well as different load disruptions are analyzed. In the presence of the HAFC-RFB storage system, the proposed mPO decreased the fitness value in the two-interconnected system by 8.023% as compared to the traditional one. However, in the case of four interconnected microgrids, it decreased the ITAE by 20.071% instead of the PO. The obtained findings validated the mPO-optimized recommended controller’s superiority over the others.