综合考虑电动汽车充电与储能及可中断负荷调度的配电网两阶段灵活性提升优化方法

分布式电源出力的强波动性及电动汽车(EV)的无序充电使配电网的灵活性不足问题日益凸显，因此非常有必要通过灵活性资源的有效调度提高配电网灵活适应性。在充分分析配电网灵活性提升措施的基础上，提出了能够表征配电网灵活性的净负荷峰值裕度、净负荷谷值裕度、净负荷允许波动裕度3个灵活性评价指标；建立了综合考虑EV充电与储能及可中断负荷调度的配电网两阶段灵活性提升优化模型，阶段1构建了基于蒙特卡洛树搜索的EV有序充电策略，合理引导EV负荷在谷时段进行充电；阶段2在阶段1的基础上，建立了计及储能及可中断负荷的优化调度模型，并采用粒子群优化算法进行优化求解。IEEE 33节点系统算例验证了所提灵活性指标及EV有序充电模型的有效性，结果表明配电网两阶段灵活性提升优化方法能有效提升配电网的灵活性且整体经济性最优。

Two-stage flexibility improvement optimization method of distribution network considering EV charging and scheduling of energy storage and interruptible loads

The frequent fluctuation of distributed generation output and the disordered charging of EVs(Electric Vehicles) make the insufficient flexibility of distribution network become more and more prominent. Therefore, it is necessary to improve the flexibility and adaptability of distribution network by scheduling the flexible resources effectively. On the basis of fully analyzing the flexibility improvement measures of distribution network, three flexibility evaluation indexes of net load peak margin, net load valley margin and net load allowable fluctuation margin are presented. A two-stage flexibility improvement optimization model of distribution network is established, which considers the EV charging and the scheduling of energy sto-rage and interruptible loads comprehensively. In the first stage, the ordered charging strategy of EV based on Monte Carlo tree search is constructed to reasonably guide the EV loads to charge in the valley period. Based on the first stage, an optimal scheduling model considering energy storage and interruptible loads is established in the second stage, which is solved by using particle swarm optimization algorithm. The example of IEEE 33-bus system verifies the effectiveness of the proposed flexibility indexes and the EV ordered charging model, and the results show that the two-stage flexibility improvement optimization method can effec-tively improve the flexibility of distribution network and the overall economy is optimal.