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All Journal Bulletin of Electrical Engineering and Informatics International Journal of Robotics and Control Systems
Obma, Jagraphon
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Control & Systems Engineering Electrical & Electronics Engineering

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Journal : International Journal of Robotics and Control Systems

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Strategic Chess Algorithm-Based PI Controller Optimization for Load Frequency Control in Two-Area Hybrid Photovoltaic–Thermal Power Systems Obma, Jagraphon; Audomsi, Sitthisak; Ardhan, Kittipong; Sa-Ngiamvibool, Worawat; Chansom, Natpapha
International Journal of Robotics and Control Systems Vol 5, No 2 (2025)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v5i2.1844

Abstract

Maintaining frequency stability in hybrid renewable-integrated power systems remains a critical challenge due to the inherent variability and uncertainty of photovoltaic–thermal (PV–T) energy sources. Traditional proportional–integral (PI) controllers, optimized using conventional metaheuristic algorithms such as the Whale Optimization Algorithm (WOA), Firefly Algorithm (FA), and Salp Swarm Algorithm (SSA), often suffer from limitations including slow convergence, premature convergence to local optima, and reduced robustness under severe load disturbances. The research contribution is the development and systematic evaluation of a chess algorithm (CA)-based PI controller tuning approach for enhancing load frequency control (LFC) in hybrid PV–T systems. Unlike population-based methods, the CA employs chess-inspired strategic decision-making processes, which improve the search efficiency and the ability to escape local optima in high-dimensional optimization problems. In this study, the proposed CA-based optimization method is applied to a two-area hybrid PV–T power system, where the system is subject to various operating conditions, including solar radiation fluctuations and step load perturbations. The tuning of PI controller parameters is performed using the integral of time-weighted absolute error (ITAE) as the objective function. Simulation results demonstrate that the CA-optimized PI controller achieves superior performance in minimizing overshoot, undershoot, and settling time when compared with controllers optimized by WOA, FA, and SSA. Specifically, the CA approach achieves faster stabilization and lower frequency deviations, highlighting its potential for real-time implementation and enhanced grid reliability. Future work will explore the scalability of the proposed method to multi-area power systems and evaluate its computational efficiency through hardware-in-the-loop validation.
Chess Optimizer for Load Frequency Control of Three-Area Multi-Source Renewable Energy Based on PID Plus Second Order Derivative Controller Areeyat, Chatmongkol; Audomsi, Sitthisak; Obma, Jagraphon; Yang, Xiaoqing; Sa-Ngiamvibool, Worawat
International Journal of Robotics and Control Systems Vol 5, No 3 (2025)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v5i3.2052

Abstract

Renewable energy sources such as solar and wind are increasingly integrated into multi-area power systems. However, their fluctuating and unpredictable characteristics pose challenges for sustaining system stability. Therefore, automatic generation control (AGC) is essential for the continual regulation of power and frequency in the system. This article presents the use of a Proportional–Integral–Derivative plus second-order derivative (PID+DD) controller for load frequency control in a three-area multi-source power system, which includes a thermal reheat power plant with a generation rate constraint (GRC) representing the maximum permissible change rate of generation output of 5% per min , a hydroelectric power plant with a  GRC of 370% per min, and a wind power plant where wind speeds vary across areas. The power generation ratio of the three areas is 1:2:4. The controller parameters were tuned using a Chess Optimizer (CO), a metaheuristic inspired by chess move complexity and planning, with specific weights assigned to each type of chess piece. Two load change scenarios were studied: a 10% step load perturbation (10% SLP) and a random load pattern (RLP).  Furthermore, experimental results based on the Integral of Time-weighted Absolute Error (ITAE) indicate that the PID+DD controller tuned by the Chess Optimizer achieved the lowest steady-state error in both scenarios (10% SLP and RLP). In Case 1 (SLP), it achieved an ITAE of 25.5072, representing a 9.70% reduction compared to the PID controller and a 1.96% reduction compared to the PI controller. In Case 2 (RLP), it achieved an ITAE of 88.0654, representing a 1.14% reduction compared to the PID controller and a 2.03% reduction compared to the PI controller. These improvements contribute to enhanced oscillation damping, reduced overshoot and undershoot, and improved frequency stability, demonstrating the practical applicability of the proposed approach in future smart grids with high renewable energy penetration.
Co-Authors Ardhan, Kittipong Areeyat, Chatmongkol Audomsi, Sitthisak Chansom, Natpapha Sa-ngiamvibool, Worawat Yang, Xiaoqing