Clean energy has gradually become the main body of competition in the electricity market. Considering the uncertainty of the wind and photovoltaic output and exploring an efficient market operation mechanism become the key issues in the construction process of the electricity spot market. To describe the uncertainty and spatiotemporal correlation of wind and photovoltaic output, the nonparametric kernel density estimation method and multivariate Gaussian Copula function are used to generate typical output scenarios. The upper model is based on the Nash negotiation theory to maximize the revenue of a wind-solar-storage cooperative alliance. The sparrow search algorithm is adopted to optimize the bidding strategy of the wind and photovoltaic producers. The lower model aims to minimize the total cost of electricity purchase. A clearing mechanism for multi-agent participation in the main and auxiliary joint market with the price-based demand response is designed. Finally, the rationality of a typical scenario of the wind and photovoltaic output and the market clearing results are analyzed. The simulation results demonstrate that the optimization model can improve the income of cooperative individuals, and reduce the total power purchase cost and the peak valley difference of load.