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This paper introduces a new control approach based on a butterfly optimization algorithm (BOA)-based tilt-integral-derivative-filter (TIDF) controller for the load frequency control (LFC) of a multi area multi fuel (MAMF) interconnected power system (IPS). The optimization of the TIDF using BOA is undergone with respect to the integral square error (ISE) minimization. However, the performance supremacy of the BOA-tuned TIDF controller is demonstrated by several control approaches reported in the literature recently. Moreover, the investigation on the MAMFIPS is performed by considering the integration of the plug-in electric vehicles in Area 1 for the step load perturbation (SLP) of 10%. Further, the effect of integrating the plug-in-electric vehicles (PEVs) with the IPS in terms of frequency variations is assessed and showcased. Furthermore, MAMFIPS is targeted at the wide variations in the load disturbance to test the robustness of the adopted regulator. The simulation analysis revealed the robustness of the presented control approach, and the deviations in the system behavior for wide variations are hardly noticed.

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Butterfly Optimization Algorithm Tuned Fractional Order Controller for the Load Frequency Control of Multi Area Multi Fuel Power System

  • 会议论文

  • 发表日期：

    2026年

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  • CH. Naga Sai Kalyan,
  • Priyanka Joshi,
  • Mohit Bajaj

摘要

This paper introduces a new control approach based on a butterfly optimization algorithm (BOA)-based tilt-integral-derivative-filter (TIDF) controller for the load frequency control (LFC) of a multi area multi fuel (MAMF) interconnected power system (IPS). The optimization of the TIDF using BOA is undergone with respect to the integral square error (ISE) minimization. However, the performance supremacy of the BOA-tuned TIDF controller is demonstrated by several control approaches reported in the literature recently. Moreover, the investigation on the MAMFIPS is performed by considering the integration of the plug-in electric vehicles in Area 1 for the step load perturbation (SLP) of 10%. Further, the effect of integrating the plug-in-electric vehicles (PEVs) with the IPS in terms of frequency variations is assessed and showcased. Furthermore, MAMFIPS is targeted at the wide variations in the load disturbance to test the robustness of the adopted regulator. The simulation analysis revealed the robustness of the presented control approach, and the deviations in the system behavior for wide variations are hardly noticed.