PMU准实时数据对主动配电网抗差估计的影响

由于相量测量单元(PMU)因成本问题无法在配电网中大规模配置，且不同设备向主站传输数据时存在客观的通信延迟、带宽限制等因素，因此状态估计器输入端存在不良数据。提出一种基于同步相量量测的主动配电网抗差估计方法，并提出以虚拟PMU量测模型补充大量的高精度冗余数据。将数据采集与监视控制(SCADA)量测系统、PMU量测和虚拟PMU量测构成的混合量测系统作为状态估计的输入端。考虑网络和量测数据不确定度对抗差M估计算法进行改进，避免了传统加权最小二乘估计中删除坏数据的残差判断和迭代过程，降低了估计耗时，提高了状态估计的可靠性和抗差性能。改进IEEE 14和IEEE 33节点配电网算例的仿真分析，验证了所提方法的有效性和普适性。

Influence of PMU quasi-real-time data on robust estimation of active distribution network

PMU(Phasor Measurement Unit) cannot be allocated in distribution network on a large scale because of the cost problem, and there exist factors of objective communication delay and bandwidth limit and so on when different devices transmit data to the master station, so there exists bad data at the input terminal of state estimator. A robust estimation method of active distribution network is proposed based on synchronous phasor measurement, and the virtual PMU measurement model is proposed to supply massive redundant data with high precision. The mixed measurement system composed of SCADA(Supervisory Control And Data Acquisition) measurement system, PMU measurement and virtual PMU measurement is taken as the input terminal of state estimation. The uncertainty of network and measured data is considered to improve the robust M-estimation algorithm, which avoids the residual judgment and iteration process of deleting bad data in the traditional weighted least squares estimation, reduces estimation time and improves the reliability of state estimation and robust performance. The simulative analysis of IEEE 14-and 33-bus distribution network examples verifies the effectiveness and universality of the proposed method.