Dynamic variable-weight least squares for state estimation of distribution network based on data fusion

Abstract

In recent years, Micro Phasor Measurement Unit (PMU) has been gradually applied to distribution system. In this paper, dynamic variable-weight state estimation of distribution network has been achieved by the measurement data from Micro-PMU combined with Supervisory Control and Data Acquisition (SCADA). Firstly, this paper analyzed three sampling states and fused the measurement data, based on the difference in the sampling step between Micro-PMU and SCADA. Then, on the basis of the fused data above, we propose an algorithm called Dynamic Variable-Weight Least Squares for state estimation of distribution network, which can check whether the accuracy of the Micro-PMU measurement and the corresponding state estimation value is high or not, and adjust the weight of measurement dynamically according to the source of the measurement data from different sampling time, to ensure the precision of state estimation. At last, the effectiveness of the proposed algorithm is validated by the numerical results on the IEEE 33-bus power system.