Multi-Objective Optimization of a Photovoltaic–Hydrogen Integrated Energy System for Residential Communities

To achieve low-carbon and low-cost energy supply while meeting the dynamic electricity, heating, and cooling demands of residential communities, an integrated energy system combining solar energy and hydrogen energy is proposed. The start-up characteristics of electrolyzers are incorporated into the system model. With key equipment capacities selected as decision variables, a four-objective optimization framework integrating the non-dominated sorting genetic algorithm II with an elitist strategy and the technique for order preference by similarity to an ideal solution is established to optimize equipment capacity configuration and system operation performance. The proposed model is applied to compare three operation strategies and different electrolyzer configuration schemes. The results demonstrate that the system performs optimally under the following electrical load strategy, with a carbon dioxide reduction rate of 63.43%, an annual cost saving rate of 65.44%, and a comprehensive index of 60.67%. The single-electrolyzer hydrogen production scheme outperforms the multi-electrolyzer schemes, achieving an annual hydrogen production of 79,820.72 kg. Sensitivity analysis further shows that photovoltaic capacity strongly affects system performance, whereas natural gas and electricity prices exert opposite effects on economic performance.