基于改进NSGA-3和不平衡潮流的配电网相序优化

低压配电网存在大量单相负荷，三相负荷不平衡会造成台区线路损耗增加，危害电网运行安全。提出一种基于历史数据的用户相序优化方法。使用台区用户的历史电压、电流数据构建台区不平衡潮流模型。针对台区一天内的运行状况建立用户节点电压平均不平衡度最小、台区线路损耗最小和换相次数最小的目标函数。提出含有正态分布交叉算子(normal distribution crossover,?NDX)的改进非支配遗传算法(non-dominated sorting genetic algorithm-3, NSGA-3)，对用户节点的相序进行优化，以获得较好的种群分布并减少优化时间。然后从解集中选择最符合条件的一组解作为换相策略。最后以安徽省某配电台区实际用户数据为例，验证了所提方法可以有效地降低三相电压不平衡度，减小线路损耗。

Phase sequence optimization of a distribution network based on improved NSGA-3 and unbalanced power flow

There are many single-phase loads in the low-voltage distribution network, such that an unbalanced three-phase load will increase the line loss in the substation distribution network and endanger the safety of power grid operation. In this paper, a method of user phase sequence optimization based on historical data is proposed. The historical voltage and current data of users in the distribution network are used to construct the unbalanced power flow model of the distribution network. The objective function of the minimum average voltage imbalance degree of the user node, the minimum line loss and the minimum commutation times in the station area are established according to the operating conditions of the station area within one day. An improved non-dominated sorting genetic algorithm-3(NSGA-3) with a normal distribution crossover (NDX) operator is proposed, and the phase sequence of the user nodes is optimized to obtain a better population distribution and reduce the optimization time. Then the most suitable set of solutions is selected from the solution set as the phase sequence adjustment strategy. Finally, the results validate that the proposed method can effectively reduce the degree of three-phase voltage imbalance and reduce line loss by taking the actual load data of a distribution station area in Anhui Province as an example. This work is supported by the National Natural Science Foundation of China (No. 51607001, No. 52177027, and No. 52107034).