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<p>Load Frequency Control (LFC) is an important part of power system management that seeks to maintain a healthy equilibrium between power generation and load demand, guaranteeing a stable power supply. Various optimization strategies have been used in recent years to improve the functionality of LFC systems. This paper presents a thorough examination of three well-known optimization algorithms: Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), and Multiverse Optimization (MVO), and assesses their efficacy in managing the frequency of the power network under varied load situations. The first step of the study is developing a robust LFC model that takes into account actual constraints and power system dynamics. The baseline controller for the LFC system is the Integral (I) controller for observation and checking the working of a basic one area LFC model. Following that, the integral controller is replaced&#xa0;by PID controller. The&#xa0;PSO, GWO, and MVO algorithms are implemented into the controller to improve system performance. During the execution phase, each optimization approach and its parameters are carefully calibrated to provide equitable and precise evaluations. Simulations are carried out on a two area&#xa0;power system testbed, taking into account various situations with dynamic load changes and disturbances. The outcomes of this work add to a better understanding of how sophisticated optimization approaches may be used to improve the dynamic responsiveness and overall stability of the LFC system. The findings of this study can help power system administrators and engineers make well-versed judgements when selecting the best optimization approach for various power system scenarios.</p>

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Impact analysis of multiverse optimization technique for secondary frequency control

  • 期刊论文

  • 发表日期：

    2026年4月15日

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  • Debashish Bhowmik

摘要

Load Frequency Control (LFC) is an important part of power system management that seeks to maintain a healthy equilibrium between power generation and load demand, guaranteeing a stable power supply. Various optimization strategies have been used in recent years to improve the functionality of LFC systems. This paper presents a thorough examination of three well-known optimization algorithms: Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), and Multiverse Optimization (MVO), and assesses their efficacy in managing the frequency of the power network under varied load situations. The first step of the study is developing a robust LFC model that takes into account actual constraints and power system dynamics. The baseline controller for the LFC system is the Integral (I) controller for observation and checking the working of a basic one area LFC model. Following that, the integral controller is replaced by PID controller. The PSO, GWO, and MVO algorithms are implemented into the controller to improve system performance. During the execution phase, each optimization approach and its parameters are carefully calibrated to provide equitable and precise evaluations. Simulations are carried out on a two area power system testbed, taking into account various situations with dynamic load changes and disturbances. The outcomes of this work add to a better understanding of how sophisticated optimization approaches may be used to improve the dynamic responsiveness and overall stability of the LFC system. The findings of this study can help power system administrators and engineers make well-versed judgements when selecting the best optimization approach for various power system scenarios.