Optimizing Regional Energy Networks: A Hierarchical Multi-energy System Approach for Enhanced Efficiency and Privacy

This research presents a hierarchically synchronized Multi-Energy System (MES) designed for regional communities, incorporating a network of small-scale Integrated Energy Microgrids (IEMs) to augment efficiency and collective advantages. The MES framework innovatively integrates energy complementarity pairing algorithms with efficient iterative optimization processes, significantly curtailing operational expenditures for constituent microgrids and bolstering both community-wide benefits and individual microgrid autonomy. The MES encompasses electricity, hydrogen, and heat resources while leveraging controllable assets such as battery storage systems, fuel cell combined heat and power units, and electric vehicles. A comparative study of six IEMs demonstrates an operational cost reduction of up to 26.72% and a computation time decrease of approximately 97.13% compared to traditional methods like ADMM and IDAM. Moreover, the system preserves data privacy by limiting data exchange to aggregated energy information, thus minimizing direct communication between IEMs and the MES. This synergy of multi-energy complementarity, iterative optimization, and privacy-aware coordination underscores the potential of the proposed approach for scalable, community-centered energy systems.