Hybrid energy storage power allocation strategy for flywheel array and lithium battery based on GWO-CEEMDAN-HHT

Oriented to reduce the impact of renewable energy on grid access stability of the power system, it was an inevitable choice to study energy storage technology with regulation capabilities. A hybrid energy storage system (HESS) integrated flywheel and lithium battery was becoming an important research direction, which could leverage the complementary advantages of different energy storage technologies. First, the analytical model of the flywheel and lithium battery was investigated, and then charging and discharging control methods were simulated by MATLAB/Simulink, respectively. A complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) method based on the grey wolf optimization (GWO) algorithm was adopted to approach the first power allocation. Considering the coordination mechanism of flywheel arrays, a dynamic weighted power allocation strategy based on state of charge (SOC) deviation was proposed to achieve secondary power allocation within the flywheel array system, which could prompt SOC of each flywheel unit to exhibit progressive convergence. To address the power allocation problem in a flywheel-lithium HESS, experimental verification of the first and secondary allocation methods was conducted. The GWO-CEEMDAN was employed to decompose the power signal into intrinsic mode functions (IMFs), and cutoff frequencies were identified by analyzing the marginal spectra derived from the Hilbert–Huang transform of each IMF. Then IMFs were reconstructed to allocate to the flywheel array and lithium battery. Based on case studies, it demonstrated that the proposed method realized a coordinated control of the flywheel array and rational power allocation of HESS, which could improve the overall capacity and lifecycle of flywheel-lithium HESS, and showed a potential application in practical engineering.