Abstract: Virtual power plants aggregate distributed energy resources and participate in the market as third-party subjects. There are various uncertainties and risk factors. It is particularly important to identify and effectively assess their trading risks accurately. Firstly, the paper identifies risk factors based on text mining technology, uses failure mode and impact analysis to determine key factors, and then designs a risk assessment index system. Secondly, the subjective and objective combination of key risk factors is weighted by combining game theory. Then, a two-dimensional cloud model for risk assessment is constructed to describe the randomness of risk occurrence probability and the ambiguity of risk consequences. Finally, the proposed evaluation method calculates and ranks the overall risk level of multi-scenario virtual power plants participating in market transactions. It is also compared with technique for order preference by similarity to ideal solution (TOPSIS), rank sum ratio (RSR), and multi-criteria optimization and compromise solution (VIKOR) methods to verify the feasibility and effectiveness of the model. The research provided a useful reference for VPP transaction management and risk prevention. It has engineering application value.