Optimal Scheduling of VPP Based on Wasserstein Uncertainty Set

In the face of increasing environmental pollution and depletion of fossil fuels, the proportion of renewable energy sources such as wind turbines and photovoltaics connected to the grid is increasing. However, there is uncertainty in the output of renewable energy resources, which can lead to scheduling difficulties and increased costs. Virtual power plants provide an efficient solution to these problems as a technology that can efficiently integrate resources within a certain area through communication technology. Therefore, this study proposes an optimal scheduling model for virtual power plants to reduce the uncertainty cost of renewable energy resources. The worst case uncertainty of renewable energy resources is quantified through Wasserstein uncertainty set. The experimental results demonstrate that the VPP optimal scheduling model proposed in this study can reduce the cost for each unit.