Risk-constrained community battery utilisation optimisation for electric vehicle charging with photovoltaic resources

High penetration of renewable energy generation in the electricity grid presents power system operators with challenges, including voltage instability, mainly due to fluctuating power generation. To address the challenges that arise from intermittent renewable generation, we explore the introduction of community batteries to provide an elegant solution for storing excess generation of renewable energy resources (RESs) and reverting to the grid in peak demand periods. In particular, determining the optimal battery type and size along with the minimum costs is challenging. Moreover, the growth in adapting electrical vehicles (EVs) imposes additional demand-related challenges on the power system, compared to the traditional industrial and household demands. This paper introduces a long-term planning strategy for community batteries to capture the surplus generation of rooftop photovoltaic (PV) panels in a given area, and direct the stored energy to charge EVs, without injecting to the upstream grid. For long-term investment planning on batteries, we consider 15 years’ worth of historical data associated with solar irradiance, temperature, EV demands, and household demands. A novel stochastic mathematical model is proposed for decision-making on battery specifications (the type and capacity of the batteries needed per year) based on the four standard battery types (based on capacity) provided by the Commonwealth Scientific and Industrial Research Organisation (CSIRO) in Australia. Uncertainties related to the EVs and RESs are captured by a non-parametric robust technique, namely the information gap decision theory, from optimistic and pessimistic perspectives. The investment decision determining component is formulated as a mixed-integer linear programming problem, incorporating the GUROBI optimisation tool, that provides a feasible global solution with a low computational burden. Our proposed solution not only determines the optimal battery installation strategies to improve the stability profile of the grid by capturing the excess power of PV generation but also facilitates EV integration in the community towards reaching the net-zero emissions target. For example, our analysis indicates that the community batteries bring significant cost advantage, in excess of $6 million, by installing type 4 batteries (4-hour capacity batteries) with over 6000 capacity, in a community inside a PV-rich residential area considered for the analysis, in comparison to scenarios without the community battery inclusion.