The determination of the optimal wind power integration capacity of a large-scale wind farm has become an important issue in power system operation and planning. Reasonable wind power integration capacity can improve the wind energy utilization and save investment for wind farm construction. This paper builds a mathematical model for determining wind farm optimal integration capacity by taking the maximization of the wind farm annual generation net benefits the objective function and the security operation requirements as the model constraints. The scenario tree construction method is proposed to deal with the random characteristics of wind power in one year based on the probability theory. The discretization principles of wind speed probability distribution and the scenario tree construction processes of wind power are proposed. Hierarchical optimization algorithm combining w-particle swarm optimization algorithm and social emotional optimization algorithm is used to solve the optimization model in this paper. The effects caused by the variation of factors correlated with the optimal wind power integration capacity results are investigated using the proposed model. The detailed solution steps are given. The correctness of the model and the validity of the algorithms for solving are verified according to the simulation on the IEEE-30 nodes system.
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