Two-layer optimal scheduling of integrated electric-hydrogen energy system with seasonal energy storage

Hydrogen is characterized by zero carbon emissions and high energy density, which can effectively support the consumption of a high proportion of intermittent new energy. Considering the seasonal nature of renewable energy sources, a seasonal hydrogen storage model is incorporated in an electric-hydrogen integrated energy system (EH-IES). In this paper, a two-layer optimization method is proposed for EH-IES with seasonal hydrogen storage. The problem of co-optimizing the equipment capacity and configuration in the proposed system is coordinated by establishing a two-layer optimization framework. Specifically, the system is optimized to minimize cost and carbon emissions at the upper layer using the multi-objective stochastic paint optimizer (MOSPO) algorithm, with the capacity configuration results being transmitted to the lower layer. The lower layer, aiming to reduce the total system cost, utilizes a commercial solver to obtain the optimal economic scheduling results for a typical day. The final analysis of the four scenarios shows that the increase in renewable energy reduces the purchasing cost of electricity by 1.89%, while in contrast, the total cost increases by 4.4% in the system with a lower proportion of renewable energy. In the case of higher heating and cooling loads, the increase in renewables reduces the purchase cost of natural gas by 9.10%. The results demonstrate that the proposed method can leverage the seasonal complementary benefits to drive new energy consumption, enhance system operation efficiency, and effectively reduce EH-IES's total operation cost and carbon emission.