An interactive cooperation model for neighboring virtual power plants

Future distribution systems will accommodate an increasing share of distributed energy resources (DERs). Facing with this new reality, virtual power plants (VPPs) play a key role to aggregate DERs with the aim of facilitating their involvement in wholesale electricity markets. In this paper, the trading strategies of a VPP in cooperation with its neighboring VPPs are addressed. Toward this aim, a portfolio of inter-regional contracts is considered to model this cooperation and maximize the energy trade opportunities of the VPP within a medium-term horizon. To hedge against profit variability caused by market price uncertainties, two efficient risk management approaches are also implemented in the VPP decision-making problem based on the concepts of conditional value at risk (CVaR) and second-order stochastic dominance constraints (SSD). The resulting models are formulated as mixed-integer linear programming (MILP) problems that can be solved using off-the-shelf software packages. The efficiency of the proposed risk-hedging models is analyzed through a detailed case study, and thereby relevant conclusions are drawn.