接入的电能超出配电网接纳裕度时，为使充电接纳裕度最大化，风光出力波动最小化，提出混合交直流主动配电网接纳裕度双重不确定性优化模型。获取双重不确定因素，以电动汽车充电接纳裕度最大化、风光出力波动最小化为目标，以节点电压、风光出力以及接纳裕度等为约束，构建配电网优化模型，并通过混沌二进制粒子群算法求解优化模型，得到迭代后的最佳优化结果，实现配电网接纳裕度双重不确定性优化。经试验验证：通过该方法优化后，配电网的平均接纳容量从1 200 kW达到了2 000 kW左右，且始终保持在接纳裕度的优质区间内；接入不确定性电能类型后，节点的电压越限概率均最高在2.7%，各节点产生的弃能均保持在6 MW·h以下；各节点在峰时接入风、光机组时，风、光出力的最高波动值依然低于3.5 kW·h；当配电网处于恶劣环境下，日常接入不确定性电能时，配电网的有功网损处于0.25~0.40 MW之间。

In order to maximize the charging acceptance margin and minimize the fluctuation of wind and solar output, a dual uncertainty optimization model of hybrid AC/DC active distribution network acceptance margin is proposed when the connected power exceeds the distribution network acceptance margin. In order to obtain the dual uncertainty, take the maximization of electric vehicle charging acceptance margin and the minimization of wind and solar power output fluctuation as the goal, and take the node voltage, the wind and solar power output and acceptance margin as the constraints, the distribution network optimization model is built. The solution of optimization model through chaotic binary particle swarm optimization algorithm is introduced to obtain the optimal optimization results after iteration, so the dual uncertainty optimization of distribution network acceptance margin is achieved. The experimental results show that after optimization by this method, the average acceptance capacity of the distribution network increases from 1 200 kW to about 2 000 kW, and it is always within the highquality range of acceptance margin. After the uncertain power type is connected, the maximum voltage out of limit probability of all nodes is 2.7%, and the discarded energy generated by all nodes is kept below 6 MW·h. When all nodes are connected to wind and solar units at peak time, the maximum fluctuation value of wind and solar output is still lower than 3.5 kW·h. When the distribution network is in a harsh environment and the uncertain electric energy is connected daily, the active network loss of the distribution network is between 0.25 MW and 0.40 MW.