Method for fast state estimation of power distribution network based on three pieces of measurement data

Abstract

The invention belongs to the technical field of power distribution network scheduling automation, and particularly relates to a method for fast state estimation of a power distribution network based on three pieces of measurement data. The method comprises the following steps of setting the taking time of SCADA measurement to be Eb+Tk in order to enable the sampling time of the SCADA measurement data to be consistent with the time of PMU data, wherein Eb is an expectation of SCADA measurement delay, and Tk is the occurrence time of the PMU data; adopting a linear extrapolation method to supplement high-precision pseudo measurement data in order to fuse PMU, SCADA and AMI measurement data; and establishing a mixed measurement state estimation model, computing a Jacobi equation H matrix, adding the active power and the reactive power for compensation decoupling, and obtaining a state estimation result after iteration solution. According to the method, a problem of data alignment of time-scale-free measurement and long-delay measurement is solved, the observability, the estimated accuracy and the computation convergence of the system are improved, and the problems of high mixed measurement dimension and slow convergence are solved.

Description

technical field [0001] The invention belongs to the technical field of distribution network scheduling automation, and in particular relates to a fast state estimation method of a distribution network based on three kinds of measurement data. Background technique [0002] At this stage, the data acquisition and supervisory control system (SCADA), the power system synchrophasor measurement unit (PMU), and the advanced measurement system (AMI) can all provide measurement data for the power system, but considering the economy, PMU coverage poor. SCADA has good coverage, but low data accuracy; AMI has high coverage, high data accuracy, but the sampling period is long, which cannot meet the real-time requirements of the power system. In this case, on the one hand, it is necessary to fuse multi-source measurement data; on the other hand, it is necessary to select an appropriate state estimation method to rationally use various measurement data for calculation, and to know the ope...

AI Technical Summary

Problems solved by technology

There are mainly the following difficulties. On the one hand, the distribution network measurement device is insufficient, the measurement data is incomplete, the three-phase imbalance, the impedance ratio is large, and the convergence is slow. The conventional least squares state estimation speed is slow, but due to the large impedance ratio It is also impossible to use fast decoupling state estimation; on the other hand, the time sections of different measurement sources are not synchronized, and some measurement sources do not even have time scales, and there are measurement delays

If the time is not synchronized and the fusion is performed, it will not only fail to achieve the effect of data fusion, but also pollute the original measurement data

The fusion of three data sources is more complicated than the two data sources, and the amount of calculation is large. It needs to be studied in specific situations, and whether it will affect the practical value due to calculation time

Images