The invention provides a virtual power plant (VPP) optimization scheduling modeling method based on a conditional risk value (CVaR). The risk theory is utilized to discuss a VPP scheduling optimization problem, the VPP contains a large number of renewable energy such as wind and light, the output is different from conventional energy, strong gap and volatility exist, a VPP scheduling optimizationproblem is an uncertainty problem, so VPP scheduling is made to face a possible risk, the CVaR theory can be utilized to accurately measure the risk of the VPP in scheduling operation, and thereby economical efficiency and the risk are balanced. In a target function of traditional VPP scheduling operation, a CVaR item for measuring the risk is added, the target function of a mathematical model ofthe problem is made to not only consider minimum total cost, but also the least risk, the CVaR is multiplied by a weight coefficient and is then added to the target function, and a multi-target problem is converted into a single-target problem for solution. The method is advantaged in that operators with different risk preferences are further graded, and instructive solutions are provided for theVPP operators with the different risk preferences.