Optimal component sizing and operational optimisation of a mobile energy system for decentralised electricity supply

The ambitious legislation driven by climate change, makes it necessary to focus more strongly on previously untapped greenhouse gas saving potentials, such as the mobile supply of renewable electrical energy which can create geographical flexibility. Consumers are supplied with electrical energy by the mobile energy system, whereby the energy can potentially come from the photovoltaic modules (PV), the diesel generator (DG), the fuel cell (FC) or the battery (EES) contained in the overall system. Exemplary customers of the service can be, e.g., road construction sites, festivals or other temporary events or also local distribution grid balancing applications. Given exogenous PV production and load profiles, this study determines the cost-optimal sizing of the system components (FC, DG, and EES) while deriving the optimal operating strategy for the overall system using mixed integer linear programming (MILP). In addition to investment and fuel costs, emission costs are integrated, which primarily occur in the context of DG operation. The model is implemented in Python in the optimisation envi- ronment Pyomo and solved by the Gurobi solver. The simulation is based on three scenarios for different combinations of PV production and load profiles as well as various hydrogen and emission price scenarios. It turns out, that the optimal sizes of the FC and the DG are between 0.5 and 2 kW for 60% and 0% demand coverage through PV respectively. For the battery, an optimal size between 1 and 4.8 kWh can be derived analogously