Risk-based profit allocation to DERs integrated with a virtual power plant using cooperative Game theory

Distributed energy resources (DERs) play a key role in the deregulated power systems with environmental concerns. Their scales and the uncertainty pertaining to intermittent generation of renewable resources are the major challenges of participating in wholesale electricity markets. The concept of virtual power plant (VPP) makes their integration possible and also allows covering the risk due to uncertainties. It yields a surplus profit in comparison to profits made by uncoordinated DERs. In this paper, using a novel stochastic programming approach, the participation of a VPP in the day-ahead market (DAM) and the balancing (real-time) market (BM) is considered. The uncertainties involved in the electricity price, generation of renewables, consumption of loads, and the losses allocation are taken into account. The desired risk-aversion level of each independent DER owner is used to compute the conditional value-at-risk (CVaR) as a well-known risk measure. The role of each DER in covering the risk and making the total profit is evaluated. The Nucleolus and the Shapley value methods as the cooperative Game theory approaches are implemented to allocate VPP's profit to the DERs. The results of a numerical study are presented and concluded.