• It is based on an improved sigmoid function to construct a maximum output dynamic adjustment coefficient, which adaptively adjusts the maximum charging/discharging power of the flywheel energy storage system. • Based on the available power of each energy storage unit, real-time dispatchable power constraints are introduced for each energy storage system. Then, under the conditions of satisfying the maximum charge/discharge power constraints of the flywheel energy storage system and the real-time dispatchable power constraints of each energy storage system, a coordinated allocation strategy of flywheel prioritization-battery replenishment is adopted. • It constructs a multi-objective optimization model for minimizing energy loss and balancing SOC in energy storage systems, and solves it using a multi-objective genetic algorithm. • It comprehensively considers the frequency regulation power undertaken by the energy storage system and the degree of SOC consistency among various energy storage units to construct adaptive weighting coefficients, which are used to select the optimal solution from the Pareto solution set. Hybrid energy storage systems (HESSs) involved in secondary frequency regulation (FR) can overcome the technical limitations of single energy storage systems (ESSs). However, coordinating the control of ESSs with differing characteristics remains a major challenge. In this study, we propose a cooperative control strategy for HESSs in automatic generation control FR. First, the maximum output dynamic adjustment factor of the flywheel energy storage system (FESS) and the real-time dispatchable power of ESSs are introduced to constrain the charge/discharge power of ESSs. Subsequently, a coordinated allocation strategy of prioritizing the FESS, i.e., battery energy storage system (BESS) supplementation, is adopted to pre-allocate the FR power of HESSs between BESSs and FESSs. Second, we minimized the energy loss and balanced the state of charge (SOC) of each ESS to redistribute the pre-allocated FR power of each ESS among the internal energy storage units. Finally, we conducted a simulation analysis using actual operational data. The findings indicate that the proposed strategy can reduce the lifetime loss of the BESS and enhance the continuous operating capability of the FESS. This system can also reduce the energy loss in each ESS, thereby effectively maintaining the SOC equilibrium of each system.
Li et al. (Wed,) studied this question.