Optimization Modeling and Performance Evaluation of Wind-Solar-Coupled Hydrogen-Ammonia Systems with Storage: A Full-Year Operational Simulation and Cost-Benefit Analysis

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Chinese explanation / 中文解读

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Original abstract

Against global warming and the need to reduce reliance on fossil fuels, green ammonia produced from renewable hydrogen has emerged as a promising energy carrier for integrating intermittent wind and solar power. This study develops an integrated wind–solar–storage–hydrogen–ammonia optimization model based on phased linear programming, simulating 8,760 hours of annual operation while incorporating renewable generation, energy storage, water electrolysis, hydrogen storage, and ammonia synthesis under operational constraints. Results show that an optimal 7:3 wind-to-photovoltaic ratio combined with 15%/4 h energy storage reduces the green ammonia production cost to approximately 2,800 CNY/ton, achieves an internal rate of return of 12–15%, and shortens the payback period to 8–10 years. The optimized configuration also lowers the levelized cost of electricity to 0.15 CNY/kWh, limits renewable curtailment to below 3%, and demonstrates that a 300,000 Nm³ hydrogen storage system can effectively stabilize ammonia synthesis. Sensitivity analysis across nine representative locations, categorized as wind-dominant, photovoltaic-dominant, and wind–solar complementary regions, reveals that system performance is most sensitive to wind power cost, followed by photovoltaic, energy storage, power storage, and hydrogen storage costs. Wind-dominant regions are particularly affected by wind cost fluctuations, photovoltaic-dominant regions benefit most from energy storage optimization, while complementary regions exhibit balanced sensitivity due to resource complementarity. The proposed phased linear programming framework provides an effective approach for dynamic optimization of integrated renewable-hydrogen-ammonia systems and offers a practical techno-economic benchmark for region-specific green ammonia deployment and cost reduction.

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