考虑分布式电源与负荷不确定性的主动配电网重构

Active distribution network reconfiguration considering distributed generation and load uncertainty

主动配电网在接入带有不确定性的分布式电源(DG)和负荷时会影响配电网的重构,本文采用Wasserstein概率距离指标和K-means聚类方法处理DG与负荷的不确定性,划分出典型主动配电网运行场景以及场景概率。通过结合典型场景的网络损耗函数和对应的场景概率,建立了主动配电网多场景重构模型,运用改进的天牛群算法对该模型的期望网络损耗函数进行优化,并提出了网络重构编码策略,提高了该算法的优化效率。最后采用修改后的IEEE33节点配电网结构进行仿真,并验证了所提策略的有效性。

The distributed generation(DG) and load with uncertainty will affect the reconfiguration of an active distribution network.Therefore,the present paper combines the Wasserstein probability distance index with the K-means clustering method to deal with the uncertainty of the distributed energy and load,and divides the typical active distribution network operation scenarios and scenario probability.A multi-scenario reconfiguration model of the active distribution network is constructed by combining the network loss function of the typical scenarios with the corresponding scenario probability.An improved beetle swarm algorithm is proposed to optimize the expected network loss function of the model.A network reconfiguration coding strategy is proposed to improve the optimization efficiency of the algorithm.Finally,the proposed strategy is validated by simulating the modified IEEE33 bus distribution network structure.