Intelligent identification method for electrical equipment load characteristics

Abstract

The application provides an intelligent identification method for load characteristics of electrical equipment, comprising the following steps: S1. collecting load signals of the electrical equipment during operation, including voltage and current signals, and recording a collection period of the load signals of the electrical equipment during operation; S2. processing and transforming the load signals by using Fourier series to obtain a direct current component value, a fundamental wave amplitude, a harmonic amplitude and a phase of the load signals; and S3. constructing a characteristic matrix based on the direct current component value, the fundamental wave amplitude, the harmonic amplitude and the phase of the load signals. Through the above method, the load characteristics of each electrical equipment in the distribution network can be accurately identified, accurate data support is provided for power supply of the distribution network, and accurate data support is provided for judgment of electrical equipment abnormalities and early warning analysis of electrical fires.

Description

Technical Field

[0001] This invention relates to the field of electrical engineering, and more particularly to a method for intelligent identification of load characteristics of electrical equipment. Background Technology

[0002] In modern society, both businesses and households have an increasing number of different electrical devices. These devices all affect the power distribution network during operation. Therefore, identifying the load characteristics of these devices has become a challenge. As the service life of electrical devices changes, their load characteristics (including operating voltage and current) also change accordingly. That is, both their operating voltage and current will change. There is currently no effective solution for accurately identifying these changes. Although there are some monitoring devices in the existing technology, such as voltage sensors and current sensors, that monitor their operating voltage and current, these can only perform rough analysis and cannot provide accurate data support for precise analysis of the impact on the power distribution network and equipment anomalies.

[0003] Therefore, in order to solve the above-mentioned technical problems, it is urgent to propose a new technical approach. Summary of the Invention

[0004] In view of this, the purpose of the present invention is to provide an intelligent identification method for the load characteristics of electrical equipment, which can accurately identify the load characteristics of each electrical device in the distribution network, provide accurate data support for the power supply of the distribution network, and provide accurate data support for the early warning analysis of electrical equipment abnormalities and electrical fires.

[0005] The present invention provides an intelligent identification method for load characteristics of electrical equipment, comprising the following steps:

[0006] S1. Collect load signals from electrical equipment during operation, including voltage and current signals, and record the acquisition cycle of the load signals from electrical equipment during operation;

[0007] S2. The load signal is processed and transformed using Fourier series to obtain the DC component value, fundamental amplitude, harmonic amplitude and phase of the load signal;

[0008] S3. Construct a feature matrix based on the DC component value, fundamental amplitude, harmonic amplitude, and phase of the load signal.

[0009] Furthermore, step S2 specifically includes:

[0010] S21. The load signal shall be expressed using the following formula:

[0011] Where A represents the load signal, and n represents the nth harmonic. nLet nω represent the amplitude of the nth harmonic, and nω represent the angular frequency of the nth harmonic. This represents the phase of the nth harmonic;

[0012] S22. Decompose formula (1) to obtain formula (2):

[0013] Where A0 represents the DC component value of the load signal; A(t) represents the load signal at time t;

[0014] S23. Apply Fourier transform to equation (2) to obtain the load signal A(t)' at time t after Fourier transform:

[0015]

[0016] Where a0 represents the DC component value of the load signal, a1 and b1 are the fundamental amplitude values ​​of the load, and a n b n This represents the amplitude of the nth harmonic.

[0017] Furthermore, the DC component amplitude a0 is determined using the following method:

[0018] in Among them, f s The frequency of the load signal acquisition is represented by f, where f represents the power frequency, t0 represents the initial acquisition time, and T represents the frequency of the load signal acquisition. s This indicates the acquisition period of the load signal.

[0019] Furthermore, the fundamental amplitude 'a' of the nth harmonic is determined using the following method: n :

[0020] in, Among them, f s The frequency of the load signal acquisition is represented by f, where f represents the power frequency, t0 represents the initial acquisition time, and T represents the frequency of the load signal acquisition. s This indicates the acquisition period of the load signal.

[0021] Furthermore, the harmonic amplitude b of the nth harmonic is determined by the following method. n :

[0022] in, Among them, f s The frequency of the load signal acquisition is represented by f, where f represents the power frequency, t0 represents the initial acquisition time, and T represents the frequency of the load signal acquisition. s This indicates the acquisition period of the load signal.

[0023] Furthermore, the phase of the nth harmonic is determined using the following method:

[0024]

[0025] The beneficial effects of this invention are as follows: This invention enables accurate identification of the load characteristics of various electrical devices in the distribution network, providing accurate data support for the power supply of the distribution network, and also provides accurate data support for early warning analysis of electrical equipment abnormalities and electrical fires. Attached Figure Description

[0026] The present invention will be further described below with reference to the accompanying drawings and embodiments:

[0027] Figure 1 This is a flowchart of the present invention. Detailed Implementation

[0028] The present invention will be further described in detail below:

[0029] The present invention provides an intelligent identification method for load characteristics of electrical equipment, comprising the following steps:

[0030] S1. Collect load signals from electrical equipment during operation, including voltage and current signals, and record the acquisition cycle of the load signals during operation. The acquisition cycle is set according to the actual working conditions. For the acquisition of load signals, existing voltage and current sensors are used, and then the signals are transmitted through corresponding IoT nodes and then input to the processor for processing. This process belongs to existing technology.

[0031] S2. The load signal is processed and transformed using Fourier series to obtain the DC component value, fundamental amplitude, harmonic amplitude and phase of the load signal;

[0032] S3. Construct a feature matrix based on the DC component value, fundamental amplitude, harmonic amplitude, and phase of the load signal. The feature matrix is ​​constructed as follows: Assuming there are m electrical devices in the target area, the electrical components are:

[0033] {load1 load2 load3 … loadm}; then, taking the first electrical device as an example, its load characteristic matrix is:

[0034] Where load1 represents electrical equipment 1, I represents current signal, U represents voltage signal, subscript 0 represents DC component value, subscript 1 represents fundamental frequency, and subscript 2 represents harmonic frequency;

[0035] The above methods can accurately identify the load characteristics of each electrical device in the distribution network, providing accurate data support for the power supply of the distribution network, and also providing accurate data support for early warning analysis of electrical equipment abnormalities and electrical fires.

[0036] In this example, step S2 specifically includes: Since the load signal includes both voltage and current signals, which are sinusoidal signals, it can be expressed using formula (1):

[0037] S21. The load signal shall be expressed using the following formula:

[0038] Where A represents the load signal, and n represents the nth harmonic. n Let nω represent the amplitude of the nth harmonic, and nω represent the angular frequency of the nth harmonic. This represents the phase of the nth harmonic;

[0039] S22. Decompose formula (1) to obtain formula (2):

[0040] Where A0 represents the DC component value of the load signal; A(t) represents the load signal at time t;

[0041] S23. Apply Fourier transform to equation (2) to obtain the load signal A(t)' at time t after Fourier transform:

[0042]

[0043] Where a0 represents the DC component value of the load signal, a1 and b1 are the fundamental amplitude values ​​of the load, and a n b n This represents the amplitude of the nth harmonic.

[0044] Specifically, the DC component amplitude a0 is determined by the following method:

[0045] in Among them, f s The frequency of the load signal acquisition is represented by f, where f represents the power frequency, t0 represents the initial acquisition time, and T represents the frequency of the load signal acquisition. s This indicates the acquisition period of the load signal.

[0046] The fundamental amplitude 'a' of the nth harmonic is determined using the following method. n :

[0047] in, Among them, f s The frequency of the load signal acquisition is represented by f, where f represents the power frequency, t0 represents the initial acquisition time, and T represents the frequency of the load signal acquisition. s This indicates the acquisition period of the load signal.

[0048] The harmonic amplitude b of the nth harmonic is determined by the following method. n :

[0049] in, Among them, f s The frequency of the load signal acquisition is represented by f, where f represents the power frequency, t0 represents the initial acquisition time, and T represents the frequency of the load signal acquisition. s This indicates the acquisition period of the load signal.

[0050] The phase of the nth harmonic is determined by the following method:

[0051] because It can be distributed in all four quadrants, therefore The calculation is divided into two parts: (-π, 0) and (0, π), and then calculated using the two formulas mentioned above. In traditional technologies, voltage and current sensors are used to monitor the voltage and current signals of electrical equipment to determine their operating characteristics, impact on the power distribution network, and status. However, each electrical device is composed of resistors (linear elements), capacitors, and reactances (nonlinear elements), which create unique characteristics for each device. Furthermore, different environments, the instant of energization, and operating states all generate unique DC components, fundamental frequencies, and multiple harmonics. The amplitude and initial phase of these DC components, fundamental frequencies, and multiple harmonics are unique to each device. Therefore, traditional methods cannot obtain this characteristic information. The method described in this application acquires all these characteristics, providing accurate data support for subsequent judgments. In the above calculations, the real-time amplitude of the coincidence signal can be acquired by voltage and current sensors before and after the Fourier transform. However, if expressed in the conventional form of load signals, the amplitude characteristics of the corresponding harmonics and fundamental frequencies cannot be determined. Therefore, the method described above can accurately determine these characteristics.

[0052] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for intelligent identification of load characteristics of electrical equipment, characterized in that: Includes the following steps: S1. Collect load signals from electrical equipment during operation, including voltage and current signals, and record the acquisition cycle of the load signals from electrical equipment during operation; S2. The load signal is processed and transformed using Fourier series to obtain the DC component value, fundamental amplitude, harmonic amplitude and phase of the load signal; S3. Construct a feature matrix based on the DC component value, fundamental amplitude, harmonic amplitude, and phase of the load signal; Step S2 specifically includes: S21. The load signal shall be expressed using the following formula: Where A represents the load signal, and n represents the nth harmonic. n Let nω represent the amplitude of the nth harmonic, and nω represent the angular frequency of the nth harmonic. This represents the phase of the nth harmonic; S22. Decompose formula (1) to obtain formula (2): Where A0 represents the DC component value of the load signal; A(t) represents the load signal at time t; S23. Apply Fourier transform to equation (2) to obtain the load signal A(t)' at time t after Fourier transform: Where a0 represents the DC component value of the load signal, a1 and b1 are the fundamental amplitude values ​​of the load, and a n b n This represents the amplitude of the nth harmonic; The fundamental amplitude 'a' of the nth harmonic is determined using the following method. n : in, Among them, f s The frequency of the load signal acquisition is represented by f, where f represents the power frequency, t0 represents the initial acquisition time, and T represents the frequency of the load signal acquisition. s Indicates the acquisition period of the load signal; The harmonic amplitude b of the nth harmonic is determined by the following method. n : in, Among them, f s The frequency of the load signal acquisition is represented by f, where f represents the power frequency, t0 represents the initial acquisition time, and T represents the frequency of the load signal acquisition. s This indicates the acquisition period of the load signal.

2. The intelligent identification method for electrical equipment load characteristics according to claim 1, characterized in that: The DC component amplitude a0 is determined by utilizing the orthogonality of trigonometric functions as follows: in Among them, f s The frequency of the load signal acquisition is represented by f, where f represents the power frequency, t0 represents the initial acquisition time, and T represents the frequency of the load signal acquisition. s This indicates the acquisition period of the load signal.

3. The intelligent identification method for electrical equipment load characteristics according to claim 1, characterized in that: The phase of the nth harmonic is determined by the following method:

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