Research on optimal design of multi-energy microgrid considering hybrid resilience load management and Carbon emissions

This paper presents an optimal sizing model for the multi-energy microgrid (MEMG) based on mixed-integer linear programming (MILP), intended to minimize the annual total cost (ATC). The MEMG incorporates multi-energy storage systems (MESS) and power-to-gas (P2G) systems considering power-to-hydrogen (P2H) and hydrogen-to-gas (H2G) processes independently. To this end, a novel two-way hybrid resilience load management strategy is introduced and the uncertain behavior of EVs and HVs is modeled via Monte-Carlo Simulations (MCS). In addition, the vehicle-to-grid (V2G) capabilities are enabled for MEMG stability. The proposed design achieves a 4.19% annual total cost reduction rate (ATCRR) and 8.81% annual emission reduction rate (AERR) compared to the design without MESS, O2 revenue, and H2G capabilities. Co-integration of H2G and V2G technologies yields a 7.281% AERR and 0.37% ATCRR. The CCS alone captures 20.35% of the CO2 annually making the system low-carbon. Furthermore, five storage systems improve efficiency and reduce ATC by 1.5%. Besides, the revenue generated from O2 sales and cross-market arbitrage covers 35.56% of MEMG expenses. Notably, the resilience management strategy effectively mitigates incremental cost burden of 1.3% and reduces emissions, ensuring robustness against outages. Therefore, the proposed system provides a clean, resilient, and cost-effective solution to the modern energy sector. [Display omitted] •The MILP model is developed for the optimal design of MEMG with P2H, H2G and MESS.•Novel two-way hybrid resilience load management strategy is proposed for both EVs and HVs.•Uncertainty of vehicle behavior and resilience load is handled with MCS.•Case studies are conducted to show economic and environmental benefits.•A feasible solution is proposed for a clean, cost-efficient, and resilient energy sector.