Distribution network pseudo measurement generating method based on kernel density estimation

Abstract

The invention relates to an interpolation method applied to pseudo measurement generating and belongs to the fields of electricity system dispatching automation technologies and power grid simulation technologies. The method comprises the steps that firstly, load data collected by an electric quantity metering system are used as load measurement; an unknown predicted value is obtained by utilizing a certain algorithm; afterwards, the predicted value is utilized, historical data serve as a basis, and then an efficient equidistant-node interpolation method is combined; accordingly, the defects of a distribution network measurement device are made up for. According to the pseudo measurement generating method, the load data in the distribution network metering system are fully utilized, and the algorithm of the method is simple, and convergence performance is guaranteed; required accuracy can be always obtained based on an equidistant-node method as long as the distances between nodes are small enough; calculation is fast, the accuracy of a pseudo measurement load of a non-measurement point can reach or approach an actual measured value, the smoothness of the load data is maintained, and then the state estimation accuracy of a distribution network is improved.

Description

technical field [0001] The invention relates to a generation method of distribution network pseudo-measurement based on kernel density estimation, which uses the historical data of the power grid, the predicted value of a regression load prediction method of kernel density estimation and the equidistant interpolation method to obtain pseudo-measurement, which belongs to electric power System scheduling automation and power grid simulation technology. Background technique [0002] Distribution network state estimation is one of the most basic and important functions of the distribution network management system, but the amount of data collected in the current distribution network is huge and complex, and the hardware installation of the measuring points requires a lot of money and energy. It is neither economical nor realistic to install measurement at each node, which leads to a serious shortage of measurement data in the distribution network. Therefore, it is necessary to i...

AI Technical Summary

Problems solved by technology

However, the common feature of these data is that the real-time performance is poor, and the load pseudo-measurement accuracy obtained by using these data is not high.

At the same time, due to the requirements of computational efficiency, the pseudo-measurement data cannot achieve the same frequency of real-time measurement, so the unpredicted pseudo-measurement data needs to be obtained by interpolation

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