Investment Planning Optimization for Energy Communities With Photovoltaic and Storage

The energy communities’ framework is changing, with new regulations that promote the incorporation of Battery Energy Storage Systems (BESS) for self-consumption from Photovoltaic (PV) production, Virtual Net Billing (VNB) strategies, and dynamic tariffs. These changes pose a challenge for the energy communities, who now need to decide upon the size of their PVs and BESS. Therefore, the purpose of this paper is to propose an integrated planning framework for the optimal sizing of PV and BESS for energy communities operating under the VNB scheme with dynamic pricing, using an indicative past year as a reference. The methodology is based on a sequence of day ahead optimizations for the community’s cost minimization. Each year, the BESS degradation is assessed, considering both static and dynamic ageing. The process is repeated for a 20-year time horizon, in order to assess the Net Present Value (NPV), including a BESS replacement plan, either with or without selling the degraded BESS. Moreover, the paper examines the grid operator’s perspective, with power flow analyses, aiming to identify the most advantageous installation node, depending on the topology, voltage drops, losses, substations’ loading, etc. The examined community is based on Greek consumption data, with a peak around 5 MW during summer period. According to the results, the optimal resources, to maximize the community’s economic indicators, are a 5 MW PV and a 3 MW / 9MWh BESS, with NPV equal to 7,742,819 €. Regarding the grid installation, the power flow analyses are conducted on CIGRE’s MV European benchmark network, for both radial and mesh configuration, showcasing that the installation on the $3^{\mathrm {rd}}$ and $8^{\mathrm {th}}$ node, respectively, improves the technical indicators and minimizes the losses. The proposed solution is developed in python programming language and the optimizer uses python’s pyomo optimization environment.