考虑多负载运行的电制氨系统优化调度

Abstract Power-to-ammonia (PtA) systems offer several benefits in terms of energy storage and may aid in the transition to net-zero carbon emissions, but the fluctuations and intermittency of renewable energy often induce a temporal and spatial mismatch between the electricity supply and chemical production. This study proposes an optimal scheduling framework by integrating the response surface methodology with mixed-integer nonlinear programming. Explicit formulas describing the Habor–Bosch process are provided in response surface models, which are simple, exhibit high fidelity, and help ensure optimal performance. In the optimization process, capacity is allocated based on the supply and utilization of renewable power, electricity, and hydrogen. This framework departs from traditional single-load production models, effectively minimizing curtailment and addressing the intermittency of renewable energy sources. The results show that multi-load operations achieve a favorable balance between economic benefits (profit of 33.8 million CNY·y −1 ) and renewable energy utilization efficiency (0.4 % curtailment). The industrial case studies considered herein validate the feasibility of PtA systems and support the development of other power-to-X systems.