Constrained optimal design of a reversible solid oxide cell-based multiple load renewable microgrid

Electrical energy storage systems are indispensable elements in a renewable power generation plant, since sources such as solar and wind are by nature intermittent and therefore not always available when necessary. Reversible solid oxide cells (rSOCs) can be fruitfully integrated within renewable microgrids, thus providing an effective solution to the mismatch between energy demand and production from renewable sources. The ob-jective of this work is the development of a modeling tool enabling both optimal sizing and proper year-through energy management of an rSOC-based renewable microgrid, supplying electricity and hydrogen to a residential complex and a passenger car fleet consisting of both electric and fuel cell vehicles. This innovative multiple load energy system entails developing suitable modeling tools to properly account for the randomness of both renewable energy production and load demand, the latter being treated via historical data and Monte Carlo-based procedures. To this aim, both hydrogen and thermal storage systems are involved in the plant design, whereas their charge sustaining management, here adopted to guarantee self-sufficiency features as required by robust and resilient distributed systems, are addressed through suited constraints. The resulting constrained optimization tool yields both design data and control guidelines, which can serve as a basis for subsequent development of low-level control strategies, as well as the refined design of grid-connected rSOC-based microgrids. A technoeconomic assessment shows that the payback period is reasonable, ranging between 6 and 10 years depending on the rSOC cost scenario.