Power grid electric energy quality detection method

Abstract

The invention discloses a power grid electric energy quality detection method, belongs to the field of electric energy detection, and aims to solve the problems that the existing electric energy quality detection method is mainly a neural network detection method, the sample extraction is difficult, the detection efficiency is low, the index is single, and the overall condition of the electric energy quality cannot be comprehensively evaluated. The method comprises the steps of 1, collecting electric field intensity signals at nodes of a power distribution network; step 2, performing denoising processing on the electric field intensity signal to obtain a denoised signal; step 3, extracting data features of the denoised signal; step 4, performing voltage grade identification on the data characteristics of the denoised signal to obtain an identified voltage grade; and 5, weighting the voltage grades corresponding to all the nodes on the power distribution network to obtain the power quality of the power distribution network. The device is used for detecting electric energy quality.

Description

Technical Field

[0001] The invention belongs to the field of electric energy detection and relates to an electric energy detection method. Background Art

[0002] With the rapid growth of power load, the structure of power grid load has undergone great changes, which has caused power quality problems such as voltage and current waveform distortion, voltage deviation, flicker and harmonics, affecting the safe and stable operation of the power system.

[0003] The power quality assessment of power grids has always been taken seriously. With the green construction concept of power grids, the quality of power grids has been challenged.

[0004] The existing power quality detection method is mainly a neural network detection method. This method has the problem of difficulty in extracting samples, resulting in low detection efficiency, and a single indicator, which fails to comprehensively evaluate the overall power quality situation. Summary of the invention

[0005] The purpose of the present invention is to solve the problem that the existing power quality detection method is mainly a neural network detection method, which has difficulty in extracting samples, resulting in low detection efficiency, and a single indicator, and fails to comprehensively evaluate the overall power quality situation. A power grid power quality detection method is proposed.

[0006] A method for detecting power quality of a power grid, the method comprising the following contents:

[0007] Step 1: Collect the electric field strength signal at the distribution network node;

[0008] Step 2: De-noise the electric field strength signal to obtain the de-noised signal:

[0009] Step 3, extracting data features of the denoised signal;

[0010] Step 4: Perform voltage level recognition on the data features of the denoised signal to obtain the recognized voltage level;

[0011] Step 5: Perform weighted processing on the voltage levels corresponding to all nodes on the distribution network to obtain the power quality of the distribution network.

[0012] Preferably, the electric field intensity signal is denoised using a wavelet denoising method.

[0013] Preferably, the PAA method is used to extract data features of the denoised signal.

[0014] Preferably, the power quality of the distribution network is:

[0015]

[0016] Where n is the total number of weights, m is the total number of voltage levels, ω j is the weight, V i is the voltage level, and D is the power quality of the distribution network.

[0017] Preferably, step 5 further comprises:

[0018] Determine the voltage risk level based on the power quality of the power grid.

[0019] Preferably, the risk level of the voltage is determined according to the power quality of the power grid, and the specific process is as follows:

[0020] If the power quality of the grid is higher than the first threshold, the voltage is judged to be a high-risk voltage. If the power quality of the grid is higher than the second threshold, the voltage is judged to be a medium-risk voltage. If the power quality of the grid is higher than the third threshold, the voltage is judged to be a high-risk voltage. Otherwise, the voltage is a normal voltage.

[0021] The beneficial effects of the present invention are:

[0022] The present invention utilizes the electric field strength signals collected at the distribution network nodes to ultimately obtain the power quality of the power grid. The detection method is simple, fast and has high detection efficiency.

[0023] The present invention utilizes the voltage level of each node to comprehensively evaluate the power quality of the distribution network, which is more practical and the evaluation is more accurate.

[0024] The present invention processes signals and extracts features to improve the detection accuracy of power quality.

[0025] The present invention can not only obtain the overall power quality situation, but also obtain the situation of each node according to the voltage level of each node, such as harmonic fault conditions, so as to effectively manage and ensure the global power quality of the entire power grid from top to bottom. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 The figure is a flow chart of a method for detecting power quality of a power grid. DETAILED DESCRIPTION

[0027] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0028] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other.

[0029] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments, but they are not intended to limit the present invention.

[0030] Example:

[0031] Combination Figure 1 This embodiment describes a method for detecting power quality of a power grid, the method comprising the following contents:

[0032] Step 1: Collect the electric field strength signal at the distribution network node;

[0033] Step 2: De-noise the electric field strength signal to obtain the de-noised signal:

[0034] Step 3, extracting data features of the denoised signal;

[0035] Step 4: Perform voltage level recognition on the data features of the denoised signal to obtain the recognized voltage level;

[0036] Step 5: Perform weighted processing on the voltage levels corresponding to all nodes on the distribution network to obtain the power quality of the distribution network.

[0037] The following further defines the denoising method:

[0038] The wavelet denoising method is used to denoise the electric field strength signal.

[0039] The following is a further introduction to the method of extracting data features:

[0040] The PAA method is used to extract the data features of the denoised signal.

[0041] Specifically, the PAA method is a piecewise aggregation approximate representation method, which mainly extracts the time series characteristics of the denoised signal and uses the support vector machine algorithm to identify the voltage level.

[0042] The following is a further introduction to how to obtain power quality:

[0043] The power quality of the distribution network is:

[0044]

[0045] Where n is the total number of weights, m is the total number of voltage levels, ω j is the weight, V i is the voltage level, and D is the power quality of the distribution network.

[0046] Step 5 is further defined below: Step 5 also includes:

[0047] Determine the voltage risk level based on the power quality of the power grid.

[0048] Specifically, determining the voltage risk level can help staff to be aware of the severity of the voltage hazard and give priority to high-risk voltages.

[0049] The following further defines the specific process of determining the risk level of voltage based on the power quality of the power grid:

[0050] If the power quality of the grid is higher than the first threshold, the voltage is judged to be a high-risk voltage. If the power quality of the grid is higher than the second threshold, the voltage is judged to be a medium-risk voltage. If the power quality of the grid is higher than the third threshold, the voltage is judged to be a high-risk voltage. Otherwise, the voltage is a normal voltage.

[0051] Although the present invention is described herein with reference to specific embodiments, it should be understood that these embodiments are merely examples of the principles and applications of the present invention. It should therefore be understood that many modifications may be made to the exemplary embodiments and that other arrangements may be devised without departing from the spirit and scope of the present invention as defined by the appended claims. It should be understood that the various dependent claims and features described herein may be combined in a manner different from that described in the original claims. It should also be understood that features described in conjunction with individual embodiments may be used in other described embodiments.

Claims

1. A method for detecting power quality of a power grid, characterized in that: The method comprises the following: Step 1: Collect the electric field strength signal at the distribution network node; Step 2: De-noise the electric field strength signal to obtain the de-noised signal: Step 3, extracting data features of the denoised signal; Step 4: Perform voltage level recognition on the data features of the denoised signal to obtain the recognized voltage level; Step 5: Perform weighted processing on the voltage levels corresponding to all nodes on the distribution network to obtain the power quality of the distribution network.

2. The method for detecting power quality of a power grid according to claim 1, characterized in that: The wavelet denoising method is used to denoise the electric field strength signal.

3. The method for detecting power quality of a power grid according to claim 1, characterized in that: The PAA method is used to extract the data features of the denoised signal.

4. The method for detecting power quality of a power grid according to claim 1, characterized in that: The power quality of the distribution network is: Where n is the total number of weights, m is the total number of voltage levels, ω j is the weight, V i is the voltage level, and D is the power quality of the distribution network.

5. The method for detecting power quality of a power grid according to claim 1, characterized in that: Step 5 also includes: Determine the voltage risk level based on the power quality of the power grid.

6. The method for detecting power quality of a power grid according to claim 5, characterized in that: According to the power quality of the power grid, the risk level of the voltage is determined. The specific process is as follows: If the power quality of the grid is higher than the first threshold, the voltage is judged to be a high-risk voltage. If the power quality of the grid is higher than the second threshold, the voltage is judged to be a medium-risk voltage. If the power quality of the grid is higher than the third threshold, the voltage is judged to be a high-risk voltage. Otherwise, the voltage is a normal voltage.

Images