Stochastic MILP-based optimization of an ammonia-fueled energy hub with renewable energy uncertainty and load flexibility

The growing global energy demand, combined with the variability of renewable energy resources (RERs), necessitates the development of flexible and sustainable multi-energy systems. Hydrogen is widely regarded as a clean energy carrier; however, ammonia (NH3) has recently gained increasing attention due to its high storage density, ease of transport, and ability to serve as a carbon-free hydrogen vector. Despite these advantages, the integration of NH3 into energy hub operation under renewable uncertainty and demand-side flexibility remains underexplored. This paper addresses this gap by proposing a stochastic mixed-integer linear programming (MILP) framework for the day-ahead scheduling of an ammonia-fueled combined cooling–hydrogen–heat–power (CCHHP) energy hub. The novelty of the study lies in: (i) embedding NH3 as a central energy carrier for simultaneously meeting electricity, heat, hydrogen, and cooling demands; (ii) employing Monte Carlo–based scenario generation with statistical distribution tests to rigorously capture renewable intermittency; and (iii) integrating demand response programs across multiple loads to enhance flexibility. Case studies show that the proposed model reduces operational costs by 11 %, decreases natural gas consumption by 11.8 %, eliminates electricity imports, increases exports by 29.5 %, and lowers storage losses by nearly 30 %. These findings confirm NH3's potential as a sustainable vector for future low-carbon energy systems.