To enhance the accommodation capability and operational flexibility of renewable energy systems, address the insufficient architectural integration of existing ammonia-based energy systems, and overcome the limitations of current optimization algorithms in tackling complex nonlinear multi-objective problems, this paper proposes a synergistic integrated energy system with liquid ammonia as the central hub. The system integrates multi-energy flows encompassing electricity, hydrogen, ammonia, and heat, leveraging ammonia fuel cell power generation, ammonia cracking, and ammonia-blended gas turbines for both electricity and heat production. A bi-level optimization model is formulated, coupling upper-layer multi-objective capacity planning with lower-layer stochastic chance-constrained scheduling. To solve this model, a hybrid algorithm, designated as LSDBO-WOA, is developed by integrating an improved dung beetle optimizer (LSDBO) with the whale optimization algorithm (WOA). Case study results demonstrate that the proposed algorithm achieves markedly superior convergence performance compared to benchmark algorithms such as non-dominated sorting genetic algorithm II (NSGA-II), with an improvement of approximately 18.6% in comprehensive performance metrics. Furthermore, the proposed electricity-hydrogen-ammonia-heat system attains an overall energy efficiency exceeding 97.66% and reduces carbon emissions by 7.3% relative to the original system without ammonia integration.
Tu et al. (Wed,) studied this question.