This chapter proposes a planning method based on an improved solution algorithm to minimize the energy cost and thus realize the optimal configuration of the system for example a distributed integrated energy system (IES) in a certain region. The model takes into account the technical and economic parameters of the equipment, the user’s multi-energy load profile, the minimization of the system energy cost as the goal, and the comprehensive consideration of the equipment capacity configuration as well as the economic operation. The uncertainty analysis of the equipment parameters is solved by adopting the Latin hypercube sampling (LHS) method for the key equipment parameters, and the Monte Carlo algorithm is improved by combining with the convex optimization method to solve the above planning problems, and the global optimal results are found. The optimization results show that the proposed method can improve the operation efficiency of model solving and effectively reduce the operation cost of the system, which verifies the feasibility of the method.