A Stochastic Programming approach for the optimal management of aggregated distributed energy resources

The paper focuses on the optimal management of distributed energy resources aggregated within a coalition. The problem is analyzed from the viewpoint of an aggregator, seen as an entity called to optimize the available resources so to satisfy the aggregated demand by eventually trading in the Day-Ahead Electricity Market. Both a full and a residual perspective in the management of the integrated resources is investigated and compared. The inherent uncertainty affecting the optimal decision problem is dealt by adopting the stochastic programming framework as modeling paradigm. Two recourse formulations (different for the full and residual case) are defined and included within a rolling horizon scheme so to account for the dynamic nature of the problem. The overall approach has been preliminary tested on test instances designed starting from a real aggregation of prosumers. The analysis of the numerical results clearly shows the effectiveness of the approach as support tool in a real-setting.