Abstract: The interaction of multiple integrated energy systems through electrical energy can effectively improve the level of wind power consumption in the system. It will become a necessary research work to seek the optimal strategy of multi-regional energy management under the uncertainty of wind power. In view of the random output characteristics of wind power and the safety and reliability of electrical energy transmission between regions， random optimization and hierarchical coordination techniques are combined to establish a distributed optimization model of multiple electricity-gas interconnected integrated energy systems on the basis of chance-constrained goal programming. The model firstly refines the modeling of a single electricity-gas interconnected integrated energy system. From the perspective of system economics， it introduces the opportunity constraint on the flexibility of interregional tie lines. The second-order cone relaxation and deterministic equivalent methods are further used to transform the model into a mixed integer second-order cone programming model. Using the general Benders decomposition （GBD） method， the model is decomposed into main and sub-problems and iteratively solved. Finally， the calculation example shows that the solution method has better convergence characteristics and computational efficiency， effectively guarantees the privacy of user information in different regions and has strong adaptability； and the establishment of the chance constrained goal programming model has a better economy and flexibility than the traditional chance constrained method.

Key words: multi-area interconnected integrated energy systems, wind power accommodation, chance constrained goal programming, general Benders decomposition （GBD） method, day-ahead dispatch scheduling