Multi-criteria decision framework and capacity sizing optimization for multi-energy storage synergy schemes in regional integrated energy systems

The form of electrical, thermal and cold storage into regional integrated energy systems (RIES) offers a promising route to overcome the limitations of single‐building efficiency and advance carbon neutrality. However, the absence of a systematic configuration methodology has hindered the reliable deployment of such multi-energy storage (MES) systems. This study proposes a two-stage “decision–optimization” framework for MES design. In the first stage, a suitability decision model based on fuzzy analytic hierarchy process and fuzzy comprehensive evaluation (FAHP-FCE) ranks candidate storage configurations. In the second stage, a multi-objective capacity co-optimization model simultaneously maximizes source-load matching, net present value (NPV), and carbon emissions reduction, incorporating differentiated storage prioritization. The coupled model is solved through dynamic simulation in TRNSYS and multi-objective optimization via NSGA-II on the jEPlus + EA platform. A case study of a community in northern China validates the proposed approach. Compared with a system without storage, the optimized battery-cold water tank-hot water tank configuration increases source-load matching by 32.0% and achieves a 62.9% reduction in carbon emissions. Relative to a conventional peak based sizing method, matching and emission‐reduction metrics improve by 13.9% and 21.6%, respectively, while yielding a positive lifecycle NPV. The results provide theoretical foundations and practical guidance for the scientific configuration of MES in regional building energy networks.