Uncertain factors are gradually increasing with the frequent interactions between power,natural gas and thermal system in the context of integrated energy system(IES). Considering the coupling and randomness therein,a comprehensive profit model,i.e.,integrated energy system-combined cooling,heating and power(IES-CCHP),is established to encourage more CCHPs to participate in energy dispatching actively. In this paper,a Nataf transformationbased self-correction particle swarm optimization(PSO)algorithm is proposed to solve this model. First,a multi-point estimation method based on Nataf transformation is adopted to generate a sample matrix,which satisfies the coupling relationship and is close to the actual values. Then,the dynamic correction of the inertia weights of particles is calculated. A numerical example shows that IES-CCHP can generate more comprehensive profit in consideration of the coupling and randomness characteristics;Moreover,the proposed algorithm reduces the randomness obviously,and has a strong global search capability.