Abstract: In the context of rapid development of clean energy, the stochasticity and volatility of wind power output have significant impacts on the stability of power system, so wind power fluctuation smoothing is a basic problem for the current clean energy development. A hybrid energy storage capacity allocation strategy based on SCNGO-VMD is proposed to smooth wind power fluctuations. After variational mode decomposition (VMD) of the wind power parameter optimization, the Pearson correlation analysis is used to judge the boundary points of strong and weak correlation, and the grid-connected power and hybrid energy storage power are obtained after two allocations; The hybrid energy storage power is allocated based on T-test frequency division (T-tFD) algorithm, and the capacity configuration of battery/ultra-capacitor is obtained. Based on this strategy, the annual comprehensive cost of energy storage components is used as the model to evaluate the economics through case study. And the fluctuation of grid-connected power and the superiority of the SCNGO are analyzed. The results show that the energy storage capacity allocation strategy based on SCNGO-VMD can effectively smooth wind power fluctuations. The maximum fluctuation of the smoothed grid-connected power for 1 minute and 10 minutes is only 18.2% and 45.52% of the national requirements, and the corresponding energy storage configuration cost is the lowest among traditional configuration strategies. The configured hybrid energy storage capacity is more economical. Meanwhile, it is verified that the SCNGO is superior to the traditional intelligent optimization algorithm in iteration speed and accuracy.