考虑分布式电源出力不确定性的主动配电网量测配置

分布式电源(DG)的接入及网络结构的变化,使得主动配电网(ADN)的状态估计及量测配置更加复杂。在考虑DG出力不确定性的基础上,建立了兼顾经济性和多种网络结构估计精度的多目标量测配置模型;以高斯混合模型(GMM)模拟DG出力的不确定性,并利用量测协方差矩阵的非对角元素表征DG间出力的相关性;基于层次分析法(AHP)确定量测配置费用和含环网的多种网络结构的目标权重,并利用贪婪算法确定ADN的量测配置方案。IEEE 33节点配电系统和119节点配电系统的仿真结果验证了文中方法的有效性和可行性。

Measurement Placement in Active Distribution Networks Considering Output Uncertainty of Distributed Generators

Access to distributed generators(DGs)and changes in network structure have increased the complexity of state estimation and measurement placement in the active distribution network(ADN). A multi-objective mathematical model of measurement placement in the ADN is established that takes into account both the cost of placement and estimation accuracy of different network structures, in which the output uncertainty of DG is also considered. The output uncertainty of DG is modeled as a Gaussian mixed model(GMM), and the correlation of DG is described by the off-diagonal elements in a measurement covariance matrix. In addition, the analytic hierarchy process(AHP)is used to determine the impact factors of the cost of placement, the mesh network as well as other network structures. The measurement placement is determined by the greedy algorithm. Simulation results based on IEEE 33-bus and a 119-bus distribution network have verified the efficiency and feasibility of the method proposed. This work is supported by National Natural Science Foundation of China(No. 51177093).