Novel Hybrid Stochastic-Robust Optimal Trading Strategy for a Demand Response Aggregator in the Wholesale Electricity Market

The close interaction between the electricity market and end-users can assist demand response (DR) aggregator in handling managing various uncertain parameters simultaneously to reduce their effect on aggregator's operation. As DR main responsibility is aggregate obtained from individual consumers trade it into wholesale market. Another of proposing programs (DRPs) end-users. This article proposes a model handle these uncertainties through development novel hybrid stochastic-robust optimization approach that incorporates around prices participation rate consumers. behavior engaging DRPs addressed stochastic programming. Additionally, volatility modeled robust method. Two are considered this include both time-based incentive-based DRPs, i.e., time-of-use program study three sectors consumers, namely industrial, commercial, residential An energy storage system also assumed be operated by maximize its profit. proposed mixed-integer linear improves evaluation scheduling for probable worst-case scenario. Finally, demonstrate effectiveness approach, thoroughly simulated real case study.