Coordinated Secondary Frequency Regulation Control Strategy for Thermal Power–Flywheel Energy Storage System Based on Improved Ant Colony Algorithm

With the increasing integration of high-penetration renewable energy into the power grid, conventional thermal power units are required to transition from serving as baseload power sources to flexible regulating sources. This shift presents challenges such as slow response, large tracking errors, and increased equipment wear. This paper proposes a coordinated control strategy for a thermal power-flywheel energy storage system based on a dynamically constrained improved Ant Colony Optimization (ACO) algorithm. A joint simulation model is developed, comprising a 660 MW thermal power unit and a 20MW/5MWh flywheel energy storage system. An optimized hierarchical scheduling framework is designed, integrating ramped AGC (Automatic Generation Control) commands with state-of-charge (SOC)based flywheel coordination, to achieve multi-objective dynamic control. By incorporating chaotic disturbance and penalty factor mechanisms, the global search capability of the ant colony algorithm is enhanced for handling complex coupled systems. A comparative study is also conducted between the proposed method and the Particle Swarm Optimization (PSO) algorithm. The results demonstrate that the improved ACO algorithm exhibits superior performance in frequency regulation stability and adaptability under extreme operating conditions. Simulation results confirm that the developed coordinated control strategy effectively enhances the secondary frequency regulation capability of thermal power units and mitigates equipment degradation.