Abstract: With the increasing penetration of renewable energy sources, traditional deterministic pricing mechanisms may not fully capture their unpredictable characteristics. This paper proposes a pricing and allocation mechanism for the integrated heat and electricity market considering renewable energy uncertainties. It employs distributionally robust chance constraints based on Wasserstein distance to model the renewable energy uncertainties endogenously. Then, an integrated energy market clearing model is developed, considering system operational constraints such as heat transfer time delay. The shadow price of uncertainties from renewable energy, reserves provided by energy sources, and the locational marginal price of nodes where energy sources are located are derived through shadow price theory. Based on the pricing method, an integrated heat and electricity market value allocation mechanism with clear rewards and penalties is proposed, which rewards power output, reserve capacity, and real-time reserve provided by energy sources while charging a reasonable fee for renewable energy uncertainties and loads separately. This paper proves the proposed pricing mechanism guarantees incentive compatibility, individual rationality and social welfare maximization in a perfectly competitive market. Case studies validate that compared with distributionally robust pricing based on moment information, the proposed method ensures reasonable revenue for renewable energy resources and promotes their orderly participation in the market by characterizing their uncertainties more accurately and formulating the price component of uncertainty separately.