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To settle the large-scale integration of wind power, it is necessary to enhance the wind power hosting capacity of distribution network. To this end, this paper proposes a stochastic mixed-integer linear programming (MILP) model to enhance the hosting capacity of distribution network with active network management (ANM) strategies. The considered ANM strategies include power factor control, reactive power compensation and network reconfiguration. The coordination of these strategies enables the distribution network to accommodate more wind power without violating its constraints. The proposed model relaxes the original nonlinear power flow equations into linear format, so that a near optimal solution can be obtained with moderate computational burden. The wind power and load demand are inherently variable due to the influence of various factors. Moreover, the output powers of multiple wind turbines (WTs) located at adjacent sites of a wind farm are spatially correlated. To represent the uncertain loads, the roulette wheel mechanism is used to generate the load samples. In addition, a combined method of inverse transformation and Nataf transformation is established to deal with the uncertain and correlated wind power. Then, scenario combination and reduction are conducted to generate representative scenarios. Finally, the feasibility and accuracy of the proposed method are verified via numerical tests on the modified IEEE 33bus test system.

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