Multi-objective battery sizing optimisation for renewable energy communities with distribution-level constraints: A prosumer-driven perspective

A Renewable Energy Community (REC) is a legal entity aggregating different users sharing their own resources to reduce both electricity bills and CO2 emissions. This paper presents and analyses the impact of a bi-objective strategy to optimise the capacity of the Battery Energy Storage Systems (BESSs) of REC prosumers equipped with photovoltaic (PV) generators. The optimisation problem is solved through a custom implementation of the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and has two contrasting objectives: maximising the self-sufficiency of the REC from the main grid, while minimising the BESS capacity of all REC members. A key novelty of this study is the prosumer-driven perspective, which allows to exclude the REC members who do not want to install a BESS through a linear optimisation constraint. Moreover, the proposed approach ensures that probabilities of over- or under-voltages are compliant with the limits specified by Distribution System Operators (DSOs). Such probabilities, as well as the line and BESS losses, are estimated within the optimisation loop through grid-level simulations performed in OpenDSS. Both a standard peer-to-grid (P2G) and a more REC-oriented peer-to-peer (P2P) energy sharing policy are analysed and their performance is assessed in different seasons and considering both the current energy demand and a possible future scenario, in which electrical heat pumps are widely used. The results of a case study based on a modified version of the IEEE 906-bus European Low Voltage distribution grid show that a if the total BESS capacity assigned to all REC prosumers exceeds a given threshold value, the benefits for the REC become minor. Assuming to choose the optimal BESS capacity solutions corresponding to the threshold value in the summer season (i.e., when PV and BESSs are most exploited), the overall energy losses are reduced roughly by 20%-40% for both P2G and P2P battery controls. The CO2 emissions instead, are reduced by 10% to 50% with the P2P policy having a slight edge over the P2G one. The P2P energy sharing policy spreads the economic benefits of energy savings more evenly among REC members, and the return on investment is generally higher if the electricity demand increases.

Automated summary

This paper investigates a bi-objective strategy for optimizing the capacity of Battery Energy Storage Systems (BESSs) for REC prosumers with PV generators, using the Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The strategy aims to maximize self-sufficiency from the main grid while minimizing BESS capacity. Results show that a P2P energy sharing policy slightly outperforms P2G in reducing CO2 emissions, and returns on investment are generally higher with increasing electricity demand.