Stochastic operational scheduling of distributed energy resources in a large scale virtual power plant

Abstract

Virtual Power Plant (VPP) is introduced as a tool for the integration of distributed generations, energy storages and participation of consumers in demand response programs. In this paper, a probabilistic model using a modified scenario-based decision making method for optimal day ahead scheduling of electrical and thermal energy resources in a VPP is proposed. In the proposed model, energy and reserve is simultaneously scheduled and the presence of energy storage devices and demand response resources are also investigated. Moreover, the market prices, electrical demand and intermittent renewable power generation are considered as uncertain parameters in the model. A modified scenario-based decision making method is developed in order to model the uncertainties in VPP’s scheduling problem. The results demonstrated that the optimal scheduling of VPP’s resources by the proposed method leads VPP to make optimal decisions in the energy/reserve market and to play a dual role as a demand/generation unit from the perspective of the upstream network in some time periods.