Predictive optimization of participation factors in energy communities

From 2024 onwards, the participation in more energy communities simultaneously has been possible in Austria. Such opportunity requires the allocation of percentages of the participants’ energy demand and generation (participation factors) to a set of pre-defined energy communities simultaneously. Being the latter not yet optimized, rather based on internal distribution keys, their full potential to increase participants’ revenues results not fully exploited so far. To overcome this issues, price-driven methods to optimize the participation factors are needed This work introduces a novel methodology to optimize individual participation factors and maximize members’ revenues from multiple participation. The framework considers the planning of daily fixed and dynamic participation factors (a unique value or a timeseries) in day ahead, and the subsequent submission to the grid operator, that then performs the ex-post energy allocation for the energy community on the next day (as required by the Austrian legislation). The framework is used to evaluate financial benefits for a consumer and a prosumer under different price conditions. To validate its effectiveness, a comparison with the current implementation of multiple participation and a sequential method to allocate energy shares post measurements is performed. Results show that additional 3.5% cost reduction can be expected for the consumer, whereas up to additional 7% of revenues are obtained by the prosumer. Although affected from forecasting errors, the optimized method presented an almost negligible gap with the reference sequential method, with the advantage that the former can be integrated into the current Austrian framework and bring additional information for energy suppliers (in the form of accurated forecasts) when its execution is more aligned with the energy markets.