Enhanced Load Frequency Control for Standalone Multi-Source Power Systems Using GWO and GA Optimized

This study focuses on optimizing a PID classical controller for Load Frequency Control in a multi-source power system that integrates gas, thermal, and hydro units. Each component, such as the steam turbine, reheater, and governor in thermal systems, as well as the penstock turbine, drop compensation, and governor in hydro systems, is modeled to represent dynamic responses. Additionally, gas turbine components like the valve positioner, speed governor, and combustion reaction are characterized by specific parameters. Genetic Algorithm (GA) and Grey Wolf Optimizer (GWO) are applied to fine-tune the PID gains, aiming to enhance system stability during load fluctuations. It exhibited a settling time of 8.92 seconds, with an overshoot of 0.012 and an undershoot of 0.0268. This marked a significant improvement over the performance of the PID controller, which had a settling time of 46.93 seconds, an overshoot of 0.045, and an undershoot of 0.055. Additionally, the GA demonstrated robust performance, achieving its best result under the IAE cost function with a settling time of 8.63 seconds, an overshoot of 0.000998, and an undershoot of 0.0268-slightly outperforming GWO in terms of settling time under IAE. However, GWO struck the best balance between rapid convergence and minimal overshoot for precision control, making it the most suitable choice for LFC in multi-source power systems.