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This work pioneered the comparative performance assessment of the generation rate constraint (GRC) models for optimal load frequency control (LFC). The two popularized models of the GRC reported in the literature, the open-loop GRC (OLGRC) and the closed-loop GRC (CLGRC), are deliberated for the three-area thermal power system network. Moreover, the fractional order (FO) proportional–integral–derivative (FOPID) is considered for the three-area thermal system for secondary regulation based on the water cycle optimization (WCO) algorithm and carried out the performance assessment of the OLGRC and CLGRC models in attaining the optimal LFC. The simulation results deliberated the dominance of the CLGRC model over the OLGRC structure for the dynamic stability of the large-area thermal system. Further, the robustness of the CLGRC structure for the multi-area thermal system is validated with a subjection of wide range of load variations and parameter uncertainty.

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Optimizing Load Frequency Control: A GRC Modeling Approach for Multi-area Thermal Power Networks

  • 会议论文

  • 发表日期：

    2025年

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  • Ch. Naga Sai Kalyan,
  • Navneet Joshi,
  • Mohit Bajaj

摘要

This work pioneered the comparative performance assessment of the generation rate constraint (GRC) models for optimal load frequency control (LFC). The two popularized models of the GRC reported in the literature, the open-loop GRC (OLGRC) and the closed-loop GRC (CLGRC), are deliberated for the three-area thermal power system network. Moreover, the fractional order (FO) proportional–integral–derivative (FOPID) is considered for the three-area thermal system for secondary regulation based on the water cycle optimization (WCO) algorithm and carried out the performance assessment of the OLGRC and CLGRC models in attaining the optimal LFC. The simulation results deliberated the dominance of the CLGRC model over the OLGRC structure for the dynamic stability of the large-area thermal system. Further, the robustness of the CLGRC structure for the multi-area thermal system is validated with a subjection of wide range of load variations and parameter uncertainty.