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<p>In our rapidly advancing modern society, automatic generation control (AGC) plays a crucial and essential role in enhancing a country’s standard of living by ensuring a high quality of electrical power. Due to practical restrictions and challenges, researchers worldwide need effective and computationally economical control methods. Therefore, this article presents the implementation of a new fuzzy gain scheduling (FGS) PID controller. The PI controller’s frequency and tie-line power deviation serve as feedback signals. To achieve the most positive outcomes, the input scaling factors (SFs) and output SFs of the FGS-PID controller are simultaneously adjusted using Class topper optimization. To validate the proposed method, we first examine a two-area hydrothermal power plant that may or may not have energy storage units that combine hydrogen aqua electrolyzers (HAEs) with fuel cells (FCs). We investigate hydro, thermal, gas, and wind power plants in the second scenario. When compared to other well-known studies, our proposal’s results show that the CTO-based FGS-PI strategy is the best option because it is simple to implement, yields smaller values for the chosen objective function, and has faster response times with less frequency and tie-line power deviation after a step load disturbance, and multi-step load disturbance.</p>

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The impact of hydrogen energy storage aqua electrolyzer fuels cell on automatic generation control of power system using optimal FGS PID controller

  • 期刊论文

  • 发表日期：

    2025年3月1日

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  • Ankur Rai,
  • Dushmanta Kumar Das

摘要

In our rapidly advancing modern society, automatic generation control (AGC) plays a crucial and essential role in enhancing a country’s standard of living by ensuring a high quality of electrical power. Due to practical restrictions and challenges, researchers worldwide need effective and computationally economical control methods. Therefore, this article presents the implementation of a new fuzzy gain scheduling (FGS) PID controller. The PI controller’s frequency and tie-line power deviation serve as feedback signals. To achieve the most positive outcomes, the input scaling factors (SFs) and output SFs of the FGS-PID controller are simultaneously adjusted using Class topper optimization. To validate the proposed method, we first examine a two-area hydrothermal power plant that may or may not have energy storage units that combine hydrogen aqua electrolyzers (HAEs) with fuel cells (FCs). We investigate hydro, thermal, gas, and wind power plants in the second scenario. When compared to other well-known studies, our proposal’s results show that the CTO-based FGS-PI strategy is the best option because it is simple to implement, yields smaller values for the chosen objective function, and has faster response times with less frequency and tie-line power deviation after a step load disturbance, and multi-step load disturbance.