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This paper extends a new concept of energy-water-hydrogen (EWH) nexus, whichwas recently developed as a solution for reducing carbon emissions from thegeneration side of power systems, to the distribution side. Under the conceptof distribution-level EWH (micro EWH) nexus, renewable energy sources (RES) areutilized to meet the energy needs of a small community. To avoid theuncertainty caused by RESs, this paper aims to investigate the real-timeoptimal operation of the micro EWH nexus which is however a challengingoptimization problem. First, such a large-scale mixed-integer nonlinearprogramming problem is relaxed into a mixed-integer convex program (MICP) byleveraging the effective convex-hull relaxation technique. Second, a fastdata-driven solution method based on active constraint and integer variableprediction is presented, which can solve the MICP problem very fast since itutilizes historical optimization data to quickly predict binary variable valuesand a limited set of active constraints.

Micro Energy-Water-Hydrogen Nexus: Data-driven Real-time Optimal Operation