FTTA-CEEMDAN-Based Optimal Allocation Strategy of Independent FM Capacity for Hybrid Energy Storage

The current large-scale new energy system connected to the grid leads to power grid frequency fluctuation. For the hybrid energy storage system as the main body of FM to independently participate in the power system FM scenario, a soccer team training algorithm (FTTA) optimization based on adaptive noise Complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) capacity optimization allocation strategy is proposed. decomposition with adaptive noise (CEEMDAN) as a strategy for optimal allocation of independent FM capacity for hybrid energy storage. Firstly, the white noise amplitude weights and the number of noise additions of CEEMDAN are optimized using FTTA algorithm, and the FM command signal is decomposed and reconstructed into high and low-frequency signals; taking into account the different crossover parameters as well as constraints such as the output power and charge state of the storage device, and with the goal of the lowest cost in the whole life cycle, the FTTA is adopted for the optimization of the hybrid storage capacity configuration; combining with the FTTA-based CEEMDN-based parameter optimization strategy and FTTA-based capacity optimization allocation strategy to solve the optimal crossover coefficients and the corresponding capacity allocation scheme. The ACE data of a typical day in a regional power grid company is simulated and verified, which confirms that the capacity allocation strategy proposed in this paper can effectively reduce the whole life cycle cost of hybrid energy storage, and at the same time is more advantageous and feasible compared with single energy storage.