Balance group optimization by scenario-based day-ahead scheduling and demand response

Balance Groups (BGs) have to provide a day-ahead consumption schedule and buy Balancing Energy (BE) to cover deviations. Demand Response (DR) can be used to reduce BE consumption and associated costs. However, this flexibility to mitigate deviations is limited and depends on the dispatch of the loads participating in DR. In this paper, a scenario-based approach and stochastic programming are used to optimize the dispatch of the BG. We assess the influence on BG cost of different formulations: 1) optimization of BG schedule taking into account the varying prices and uncertainty, 2) optimization of schedule of flexible loads taking into account the possibility to react during the day, 3) combination of 1) and 2). These formulations are compared to a benchmark representing current practice. We find a clear improvement compared to the benchmark, but the relative difference between 1) to 3) to be rather small.