Abstract: [Objectives] With the continuous advancement of technological capabilities and the ongoing upgrading of industrial structure in China, the demand for clean energy continues to rise. In this context, new energy power generation and energy storage technologies have attracted extensive attention as key pathways for achieving the energy transition. To effectively enhance the local consumption capacity of new energy and reduce wind and solar power curtailment, a bi-level optimal configuration method for microgrids centered on electricity-heat-hydrogen is proposed. [Methods] First, the microgrid structure is determined, and a multi-energy coupled microgrid model is constructed. Second, a bi-level optimal configuration model is designed, with the upper layer maximizing the system’s net revenue and the lower layer maximizing daily operational revenue. The genetic algorithm is employed to iteratively solve for the optimal configuration and strategy. Finally, taking a specific region in Xinjiang as an example, typical daily four-season scenarios are generated based on a probabilistic scenario reduction method, and the bi-level optimal configuration model is simulated and verified. [Results] The simulation results show that the proposed method can increase the net revenue of the system by about 18%, and improve the wind and solar consumption rate by about 13%, which verifies the effectiveness of the model in optimizing capacity configuration and operational strategy. [Conclusions] The proposed method achieves improvements in system net revenue and wind-solar consumption rate, providing a reference for the planning, design, and economic operation of microgrids with hydrogen energy storage.

Key words: microgrid, new energy, energy storage, hydrogen energy, genetic algorithm, capacity configuration, bi-level optimization