<![CDATA[This article presents load frequency control for a nonlinear multi-source power system divided into three areas, consisting of thermal reheat power plants, hydropower, and wind generation, while considering generation rate constraints (GRC). A proportional–integral–derivative (PID) plus second-order derivative (PID+DD) controller optimized using the chess algorithm (CA) is proposed. The effectiveness of CA is validated against hippopotamus optimization (HO), grey wolf optimizer (GWO), and ant lion optimizer (ALO) under two scenarios: a 10% step load perturbation (SLP) and a random load pattern (RLP). Simulation results indicate that the proposed CA significantly improves dynamic performance. In scenario 1 (10% SLP), CA achieves a reduction of approximately 30.5% in integral weight time absolute error (ITSE) compared to GWO and 43.7% compared to HO, while also reducing frequency undershoot in Area 2 by 15.2% compared to HO. In scenario 2 RLP, CA maintains robustness, limiting tie-line power deviations to ±8 MW, whereas HO exhibits deviations exceeding ±12 MW. Overall, the CA-tuned PID+DD controller demonstrates superior damping, reduced overshoot and undershoot, and enhanced stability across multi-area interconnected renewable systems, making it a promising approach for future real-time load frequency control (LFC) applications with higher renewable penetration.]]>
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