Deadband Day Ahead Optimization Strategy of Energy Storage Power Station Based on mPSO Algorithm

This study proposes a deadband optimization strategy for energy storage power stations, leveraging a modified particle swarm optimization (mPSO) algorithm. The dual impacts of the primary frequency adjustment deadband size-on the frequency regulation cost and the frequency stability of the power system-are systematically analyzed. By designing an optimal deadband allocation strategy, the economic efficiency and security requirements of power network are simultaneously addressed. This strategy quantitatively evaluates the impact of the deadband setting of the energy storage system on its power output during a frequency regulation, alongside the implications for frequency stability metrics. The optimization framework employs the mPSO to determine the optimal deadband size, aiming to minimize frequency regulation costs while satisfying frequency stability constraints. Finally, the effectiveness of the proposed approach is demonstrated through simulation studies on the IEEE 6-bus system.