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Robust THRO-Optimized PIDD2-TD Controller for Hybrid Power System Frequency Regulation

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The large-scale adoption of renewable energy sources, while environmentally beneficial, introduces significant frequency fluctuations due to the inherent variability of wind and solar output. Electric vehicle (EV) integration with substantial battery storage and bidirectional charging capabilities offers potential mitigation for these fluctuations. This study addresses load frequency regulation in multi-area interconnected power systems incorporating diverse generation resources: renewables (solar/wind), conventional plants (thermal/gas/hydro), and EV units. A hybrid controller combining the proportional–integral–derivative with second derivative (PIDD2) and tilted derivative (TD) structures is proposed, with parameters tuned using an innovative optimization method called the Tianji’s Horse Racing Optimization (THRO) technique. The THRO-optimized PIDD2-TD controller is evaluated under realistic conditions including system nonlinearities (generation rate constraints and governor deadband). Performance is benchmarked against various combination structures discussed in earlier research, such as PID-TID and PIDD2-PD. THRO’s superiority in optimization has also been proven against several recently published optimization approaches, such as the Dhole Optimization Algorithm (DOA) and Water Uptake and Transport in Plants (WUTPs). The simulation results show that the proposed controller delivers markedly better dynamic performance across load disturbances, system uncertainties, operational constraints, and high-renewable-penetration scenarios. The THRO-based PIDD2-TD controller achieves optimal overshoot, undershoot, and settling time metrics, reducing overshoot by 76%, undershoot by 34%, and settling time by 26% relative to other controllers, highlighting its robustness and effectiveness for modern hybrid grids.
Title: Robust THRO-Optimized PIDD2-TD Controller for Hybrid Power System Frequency Regulation
Description:
The large-scale adoption of renewable energy sources, while environmentally beneficial, introduces significant frequency fluctuations due to the inherent variability of wind and solar output.
Electric vehicle (EV) integration with substantial battery storage and bidirectional charging capabilities offers potential mitigation for these fluctuations.
This study addresses load frequency regulation in multi-area interconnected power systems incorporating diverse generation resources: renewables (solar/wind), conventional plants (thermal/gas/hydro), and EV units.
A hybrid controller combining the proportional–integral–derivative with second derivative (PIDD2) and tilted derivative (TD) structures is proposed, with parameters tuned using an innovative optimization method called the Tianji’s Horse Racing Optimization (THRO) technique.
The THRO-optimized PIDD2-TD controller is evaluated under realistic conditions including system nonlinearities (generation rate constraints and governor deadband).
Performance is benchmarked against various combination structures discussed in earlier research, such as PID-TID and PIDD2-PD.
THRO’s superiority in optimization has also been proven against several recently published optimization approaches, such as the Dhole Optimization Algorithm (DOA) and Water Uptake and Transport in Plants (WUTPs).
The simulation results show that the proposed controller delivers markedly better dynamic performance across load disturbances, system uncertainties, operational constraints, and high-renewable-penetration scenarios.
The THRO-based PIDD2-TD controller achieves optimal overshoot, undershoot, and settling time metrics, reducing overshoot by 76%, undershoot by 34%, and settling time by 26% relative to other controllers, highlighting its robustness and effectiveness for modern hybrid grids.

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