With the advancement of the electricity spot market and demand response trading in various provinces of China, electricity retailers and virtual power plants face the risk of electricity price fluctuations and deviation penalties. In response to the new pattern of the integration of electricity sales and virtual power plant business, this paper constructs a multi-scenario risk aversion model based on conditional value at risk (CVaR), and proposes a day-ahead and real-time two-stage power trading decision-making method for the integrated operation of the electricity retailer and virtual power plant. To simultaneously measure the dual impacts of price fluctuations and tail losses, the proposed model explicitly introduces CVaR constraints in the objective function and extends to multi-scenario stochastic programming, which can be solved based on the primal-dual interior-point method. The currently commonly used deterministic point prediction model is optimized based on single-point power price predictions, ignoring uncertainties such as market price fluctuations and deviations in renewable power generation. In contrast, considering the price distributions and multiple scenarios of risks, the proposed multi-scenario risk aversion model based on CVaR not only retains the motivation of maximizing expected returns, but also effectively suppresses extreme losses caused by day-ahead and real-time price differences and uncertainties in demand response. The simulation results show that the multi-scenario risk aversion model based on CVaR can increase the expected return to the theoretical upper limit in the absence of perfect information, and at the same time convert the loss of the VaR and the CVaR into a return, greatly reducing the tail loss. The results verified the dual-excellent performance of return and risk of the multi-scenario risk aversion model based on CVaR in the day-ahead and real-time two-stage trading in Guangdong, which can provide technical support for the power trading decision-making and risk management of the integrated operation of the electricity retailer and virtual power plant.