Network-constrained unit commitment-based virtual power plant model in the day-ahead market according to energy management strategy

Energy management of a virtual power plant (VPP) that consists of wind farm (WF), energy storage systems and a demand response program is discussed in the present study. The introduced strategy is realized at the electrical power transmission level and takes into account the collaboration between VPPs in day-ahead energy and reserve markets. One notable feature of the proposed strategy is attempting to make the revenue of VPPs close to the operating cost of generating units as much as possible. The objective function is subjected to the network-constrained unit commitment model, up and down reserve requirements and the proposed VPP constraints. This method is taking into account the uncertainty in system and VPP loads, day-ahead market energy and reserve price and WF power generation. This strategy is applied as hybrid stochastic-robust scheduling to the VPP at the electrical power transmission level, where the scenario-based stochastic programming models the uncertainty of day-ahead market prices, and the bounded uncertainty-based robust optimization has been adopted to model the uncertainties related to the load and WF power. Scheme has been tested on IEEE systems. According to the obtained results, the proposed coordination of VPPs in the mentioned markets demonstrates capability of suggested strategy. Energy management of a virtual power plant (VPP) that consists of wind farm, energy storage systems and a demand response program is discussed in the present study. The introduced strategy is realized at the electrical power transmission level and takes into account the collaboration between VPPs in day-ahead energy and reserve markets.image