A distributed low-voltage distribution network status monitoring data compression method

Abstract

The invention discloses a method for monitoring the state of a distributed low-voltage distribution network and compressing data. The method includes the steps that a sampling voltage transformer outputs a signal to obtain a sampling value sequence; the relative difference between the sampling value of each sampling point and the sampling value of the corresponding sampling point before a whole cycle is calculated; when three differences delta u(m) of the sampling points are greater than a setting threshold value A continuously, a data storage is started until it is detected that the three differences delta u(m) of the sampling points are smaller than the setting threshold value A continuously, and then a data storage sequence is formed; a new sequence is obtained by compressing and converting data; the sequence Z(k) is searched for a compression critical point B, all numerical values, behind the compression critical point B, in the sequence Z(k) are filtered out, and data compression is achieved. The method has the advantages that the number of samples is decreased largely on the basis of not losing voltage transient fault characteristics, the requirements for communications are reduced remarkably, and the overall real-time performance of a monitor system is guaranteed.

Description

technical field [0001] The invention belongs to the field of power system operation and monitoring, in particular to a method for compressing distributed low-voltage power distribution network state monitoring data. Background technique [0002] In recent years, more and more distributed power sources represented by photovoltaics, wind power, and electric vehicles have appeared in power distribution systems. In addition, the operation mode of power distribution lines has become more and more complicated. Power grids, grid distribution networks, micro-grids and other operating modes have emerged one after another, and the grounding methods of distribution networks are also complex and diverse, including non-grounding, grounding through arc suppression coils, and grounding through small resistances. ; In particular, there are many branch lines in the distribution network, the load fluctuation is large, and the real-time communication is difficult, which makes the real-time mon...

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Problems solved by technology

[0002] In recent years, more and more distributed power sources represented by photovoltaics, wind power, and electric vehicles have appeared in power distribution systems. In addition, the operation mode of power distribution lines has become more and more complicated. Power grids, grid distribution networks, micro-grids and other operating modes have emerged one after another, and the grounding methods of distribution networks are also complex and diverse, including non-grounding, grounding through arc suppression coils, and grounding through small resistances. ; In particular, there are many branch lines in the distribution network, the load fluctuation is large, and the real-time communication is difficult, which makes the real-time monitoring of the distribution network difficult to solve effectively.

However, for the collection of transient signals, the signal sampling rate will be 100-1000 times that of the steady-state signal sampling rate, which will greatly increase the storage pressure of the sampling data in the monitoring device, especially the pressure of communication, which seriously affects the real-time communication. sex

[0005] Therefore, data compression technology that only retains valuable fault feature information or data has been applied. Data compression technology is divided into two categories: lossy compression and lossless compression. There are many related compression algorithms, including: fast Fourier transform-based Data compression algorithm, wavelet transform data compression algorithm, fractal data compression, etc., but these data compression algorithms are mainly based on the evolution of data compression ideas such as images or audio, and the goal of compression is concentrated on high data compression rate and compression speed. The compression algorithm running CPU is mainly a high-performance computer, not an industrial single-chip microcomputer-related chip, and does not consider the requirements of transient detection of low-voltage distribution network: real-time, low power consumption and low-performance single-chip microcomputer as a carrier chip, etc.

Make existing high-performance data compression algorithms unable to be directly applied

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