Robust decentralized optimization of Multi-Microgrids integrated with Power-to-X technologies

Nowadays, the enormous rising demand for hydrogen fuel cell vehicles (HFCVs) and electric (EVs) in transportation sector has a significant contribution growing of multi-energy microgrids (MEMGs) accompanied by refueling stations (HRSs), EV parking lots (EVPLs) power-to-hydrogen (P2H2) technologies. The competency to enhance efficiency reliability MEMG systems leads form networked structure called multi-microgrids (MMG). In this paper, robust decentralized energy management framework is proposed optimal day-ahead scheduling set interconnected hydrogen, heat, power-based (MGs) presence HRSs EVPLs. MMG collaborative provider company (HPC) electricity markets with novel technologies such as power-to-heat (P2H), (P2H2), combined heat power (CHP) units, multiple storages response improve system flexibility meeting demands. necessity data privacy preservation methods MGs emerged when are operated an satisfy different demands minimum cost. Therefore, iterative-based algorithm alternating direction method multipliers (ADMM) utilized decompose problem minimize total daily cost while protecting MEMGs. structure, optimization model able manage uncertainty considering worst-case scenario price conservativeness levels MEMGs sensitive fluctuations. Finally, simulation results represent effectiveness under worst case market meet electricity, hydrogen.