Grid-friendly optimization of energy communities through enhanced multiple participation

Energy communities have been designed to promote sustainable development in the form of improved and affordable energy access, sustainable generation, and social inclusion. As their legislative background continues to evolve, future upgrades are expected to increase the benefits that these novel energy concepts offer. In Austria, from 2024 onwards, it will be possible to participate in more than one energy community at the same time; as such, it is necessary to evaluate the potential benefits for participants and the existing electricity grid. Thus, in this study, an optimization model is proposed to allocate the demand and production of each participant, generation unit, and storage initially belonging to different communities that are implemented under the same distribution transformer and engage in multiple participation. Both energy- and grid-related costs are minimized, and the benchmark independent energy community case is compared with the novel multiple participation. The influence of participants’ acceptance on providing flexibility (in the form of load shedding) is assessed through sensitivity analysis. The results show that, compared to the independent case, multiple participation could provide additional reductions in terms of emissions (3.5%), costs (up to 10%), and peak demand (up to 29%) at the transformer level. However, communities with higher generation shares could be individually disadvantaged compared to those with lower generation shares. Storage could also assist in reducing costs and peak demand, but at the cost of faster aging and with relatively small differences between the independent and multiple participation cases. • Optimal allocation of energy shares between different energy communities. • Comparison between independent ECs and multiple participation ECs. • Analysis on the peak load reduction behind the transformer and single-EC level. • Sensitivity of the grid to different load shedding acceptance. • Analysis on the number of cycles performed by the storages.