An Optimal Customization and Operation Strategy of Reserve-oriented Virtual Power Plant Based on CVaR

Virtual power plant (VPP) integrates demand response (DR) resources to provide reserve service for power system. VPP's profit can be maximized by optimizing the internal DR portfolios. A day-ahead portfolio optimization-based customization strategy of reserve-oriented VPP is proposed in this paper according to the forecast data of power system's reserve demand. Multi-scenario method is used to describe uncertainties associated with calling up reserve capacity and conditional value at risk (CVaR) is used to evaluate risk of VPP's profit. DRs' operating points are optimally adjusted to minimize the cost of being called up based on those scheduled day ahead. Results of case study show that qualified DR portfolios of VPP can be selected not only subject to DRs' operating constraints, but also benefiting both VPP and DRs, which features excellent incentive compatibility.