Abstract: With the opening of the energy markets, regional integrated energy system (RIES) operators, as the middlemen in both wholesale and retail energy markets, will face such uncertainties as the market energy prices, the renewable energy and load when they participate in the market. However, it is difficult to obtain the exact distribution of some random variables. To solve this problem, this paper constructs a WCVaR-based market transaction model of RIES operators, describing the uncertainty of the random variable distributions by mixing the distributions. This model considers the network constrains to confirm the safety of RIES networks. Meanwhile, the risk adjusted return on capital (RAROC) is cited to model the balance relationship between the risk and the income. Under the discrete bound constraint distribution, the dual theorem is used to transform the original max-min problem into a semidefinite programming problem. Finally, the validity of the model and algorithm is verified by the modified 33-bus electricity-7-node gas-6-node heat distribution network. The impacts of the network constraints, the integrated demand response, the RAROC threshold, the bound constraint disturbance size and the prediction errors on the income of the regional integrated energy operators are analyzed. The results provide the theoretical guidance for the trading strategy of the RIES operators.