Load access identification method and system based on intelligent circuit breaker

Abstract

The invention discloses a load access identification method and system based on an intelligent circuit breaker, and the method is characterized in that the method comprises the following steps: collecting a real-time current on a corresponding load circuit through the intelligent circuit breaker, and calculating a frequency domain current amplitude array at each prediction moment on the load circuit; and calculating the similarity between two continuous frequency domain current amplitude arrays, and judging a load access event and a load access type on the load loop according to the similarity. By analyzing the variable quantity of the load current frequency domain amplitude array on different frequency bands, the access event of dangerous loads such as an electric vehicle and the like is identified, and an alarm is given, so that the use behavior of the dangerous loads is standardized.

Description

Technical Field

[0001] The present invention relates to the field of power systems, and more specifically, to a method and system for identifying load access based on an intelligent circuit breaker. Background Art

[0002] A load refers to an electronic component connected across the power supply that consumes electrical energy in a circuit. It is a device that operates using electrical energy. The function of a load is to convert electrical energy into other forms of energy. For example, an electric furnace converts electrical energy into heat energy; an electric motor converts electrical energy into mechanical energy, etc. Commonly used lighting fixtures, household appliances, electric vehicles, etc. can all be referred to as electrical appliances.

[0003] During daily travel, many people choose electric vehicles as a means of transportation. However, while electric vehicles bring convenience to transportation, their fire hazards cannot be ignored. Chargers with low prices and poor quality only have a cooling fan and a heat sink inside, without a protection board, and thus cannot play the role of self - protection and self - power - off. Some vehicle owners unauthorizedly modify the power supply of electric vehicles, damaging the safety performance of the vehicle's electrical circuit. During charging, it is easy to cause faults such as electrical circuit overload and short - circuit of the vehicle, increasing the probability of causing a fire accident. The fire hazards of electric bicycles include a very fast burning speed, a high temperature generated during combustion, and it is easy to generate a large amount of toxic gases during the combustion process. The battery of an electric bicycle will explode during combustion or when heated.

[0008] In view of the above problems, if an alarm method for dangerous load access events in a load circuit can be provided, the phenomenon of unreasonable use of dangerous loads can be significantly reduced. Summary of the Invention

[0009] To solve the deficiencies in the prior art, the present invention provides a method and system for identifying load access based on an intelligent circuit breaker, which issues an alarm by identifying access events of dangerous loads such as electric vehicles, thereby standardizing the usage behavior of dangerous loads.

[0010] The present invention adopts the following technical solutions.

[0011] In a first aspect of the present invention, there is provided a method for identifying load access based on an intelligent circuit breaker. The method includes the following steps: collecting real - time current on the load circuit corresponding to the intelligent circuit breaker, and calculating the frequency - domain current amplitude array at each prediction moment on the load circuit; calculating the similarity between two consecutive frequency - domain current amplitude arrays, and judging the load access event and load access type on the load circuit according to the similarity.

[0012] Preferably, the intelligent circuit breaker is used to collect the real-time current on the corresponding load loop, and calculate the frequency-domain current amplitude array at each prediction moment on the load loop, including: collecting the real-time current sampling values within a preset time period, and obtaining the frequency-domain curve through Fourier transform; taking the power-frequency fundamental wave as the center point, selecting the frequency-domain points of each harmonic on both sides of the power frequency, and collecting the amplitudes of the frequency-domain curves at each harmonic frequency-domain point; using the frequency-domain points of each harmonic and the amplitudes of the frequency-domain curves at the center point to construct the frequency-domain current amplitude array.

[0013] Preferably, calculating the frequency-domain current amplitude array at each prediction moment on the load loop includes: the distance between any two adjacent prediction moments is at least multiple power-frequency cycles, and the number of power-frequency cycles is determined by the accuracy of the Fourier transform.

[0014] Preferably, using the frequency-domain points of each harmonic and the amplitudes of the frequency-domain curves at the center point to construct the frequency-domain current amplitude array includes: the amplitudes of the frequency-domain curves at the frequency-domain points of each harmonic and the center point are saved in the form of floating-point numbers, and the frequency-domain current amplitude array is saved in the form of a floating-point number array.

[0015] Preferably, calculating the similarity between two consecutive frequency-domain current amplitude arrays includes: the similarity Delta(A,B) of the frequency-domain current amplitudes between any two adjacent prediction moments A and B is:

[0016]

[0017] n is the number of the floating-point number in the floating-point number array, and N is the total number of the floating-point numbers in the floating-point number array;

[0018] An is the value of the nth floating-point number in the floating-point number array at the prediction moment A;

[0019] Bn is the value of the nth floating-point number in the floating-point number array at the prediction moment B.

[0020] Preferably, judging the load access event and load access type on the load loop according to the similarity includes: if the similarity of the frequency-domain current amplitudes between any two adjacent prediction moments A and B is greater than the first preset threshold, it is judged that a load access event has occurred between two adjacent prediction moments; the load access event includes a new load accessing the load loop, an old load exiting the load loop, and a change in the power of the old load. [[ID=X]] [[ID=Y]]

[0021] Preferably, determining the load access event and load access type on the load loop according to the similarity includes: if the similarity of the frequency-domain current amplitudes between any two adjacent prediction times A and B is less than a second preset threshold, it is determined that no load access event occurs between the two adjacent prediction times; the second preset threshold is less than the first preset threshold.

[0022] Preferably, determining the load access event and load access type on the load loop according to the similarity includes: normalizing the floating-point numbers in the floating-point number array in advance, and determining the first preset threshold and the second preset threshold according to the value range of the floating-point numbers.

[0023] In a second aspect of the present invention, there is provided a load access recognition system based on an intelligent circuit breaker, the system including a collection unit, a calculation unit and an alarm unit; wherein, the collection unit is deployed on the intelligent circuit breaker and is used for collecting real-time current on the load loop corresponding to the intelligent circuit breaker; the calculation unit is used for calculating the frequency-domain current amplitude array at each prediction time on the load loop, calculating the similarity between two consecutive frequency-domain current amplitude arrays, and determining the load access event and load access type on the load loop according to the similarity; the alarm unit is used for sending an alarm according to the load access event and load access type.

[0024] In a third aspect of the present invention, there is provided a terminal, including a processor and a storage medium; the storage medium is used for storing instructions; the processor is used for operating according to the instructions to execute the steps of the method according to any one of claims 1-8.

[0025] The beneficial effects of the present invention are as follows. Compared with the prior art, in a load access recognition method and system based on an intelligent circuit breaker in the present invention, by analyzing the change amount of the load current frequency-domain amplitude array in different frequency bands, the access event of dangerous loads such as electric vehicles is identified and an alarm is issued, thereby standardizing the use behavior of dangerous loads.

[0026] The beneficial effects of the present invention also include:

[0027] 1. Based on the frequency-domain characteristics of the charging current shown by different rechargeable batteries during the charging process, the present invention identifies and judges the charging action of electric vehicle batteries. The function of automatically identifying the charging of electric vehicle batteries by the indoor intelligent circuit breaker has great significance.

[0028] 2. Through the present invention, on the low-computation-level hardware platform of the intelligent circuit breaker, through a relatively simple software algorithm, without increasing additional product costs, the indoor charging recognition of electric bicycles can be realized, greatly improving the product value of the intelligent circuit breaker and also greatly improving the residential electricity use safety. Description of the Drawings

[0029] Figure 1 This is a schematic flowchart of a load access recognition method based on an intelligent circuit breaker according to the present invention. Detailed implementation manners

[0030] To make the objectives, technical solutions and advantages of the present invention clearer and more accurate, the technical solutions of the present invention will be described in detail below through multiple specific implementation manners. The embodiments adopted in the present invention are only used to explain the present invention and do not limit the content of the present invention.

[0031] In the intelligent circuit breaker of the present invention, based on the frequency-domain characteristics of the charging current during the charging process of an electric vehicle battery, real-time data is collected and fast Fourier transform is performed to obtain the frequency-domain characteristics of the charging current. Based on the previously obtained frequency-domain characteristics of the charging current, it is determined in real time whether there is a matching current frequency-domain characteristic in the actual operation scenario to identify the charging action of the electric vehicle battery and trigger an alarm to solve the problem that it is difficult to restrict indoor charging of electric vehicle batteries.

[0032] Figure 1 This is a schematic flowchart of a load access recognition method based on an intelligent circuit breaker according to the present invention. As Figure 1 shown, in the first aspect of the present invention, a load access recognition method based on an intelligent circuit breaker is involved, and the method includes Step 1 to Step 2.

[0033] Step 1: Collect the real-time current on the load loop corresponding to the intelligent circuit breaker, and calculate the frequency-domain current amplitude array at each prediction moment on the load loop.

[0034] Collecting the real-time current on the load loop corresponding to the intelligent circuit breaker and calculating the frequency-domain current amplitude array at each prediction moment on the load loop includes: collecting the real-time current sampling values within a preset time period, obtaining the frequency-domain curve through Fourier transform; taking the power frequency fundamental wave as the center point, selecting the frequency-domain points of each harmonic on both sides of the power frequency, and collecting the amplitudes of the frequency-domain curves at each harmonic frequency-domain point; using the frequency-domain points of each harmonic and the amplitudes of the frequency-domain curves at the center point to construct the frequency-domain current amplitude array.

[0035] Collect the real-time current of each phase of the intelligent circuit breaker to calculate the effective value of the real-time current. The intelligent circuit breaker converts the analog current signal into multiple sampling points through the A / D conversion unit. Perform Fourier transform to obtain the frequency-domain current waveform at each prediction moment on the load loop.

[0036] Under normal circumstances, the frequency-domain current waveform has the largest value at the power frequency fundamental wave position, and the values at each harmonic frequency point on both sides gradually decrease. Taking the power frequency fundamental wave as the center point, the peaks of multiple harmonics are sequentially selected on both sides. In one embodiment, the first harmonic to the seventh harmonic are selected, and 15 harmonic frequency points are obtained as the points to be sampled. At each sampling point, the amplitude of the frequency-domain current waveform is collected.

[0037] Preferably, calculate the frequency-domain current amplitude array at each prediction moment on the load loop, including: the distance between any two adjacent prediction moments is at least multiple power frequency cycles, and the number of power frequency cycles is determined by the accuracy of the Fourier transform.

[0038] In one embodiment, the acquisition frequency of the current sensor is 2KHz, and 1024 sampling points are collected for one Fourier transform. Thus, taking 0.5s as a power frequency cycle.

[0039] Using the amplitudes of the frequency-domain curves at each harmonic frequency point and the center point, construct the frequency-domain current amplitude array, including: the amplitudes of the frequency-domain curves at each harmonic frequency point and the center point are saved in floating-point form, and the frequency-domain current amplitude array is saved in the form of a floating-point array.

[0040] The amplitude of the collected frequency-domain current waveform is stored in floating-point form. 15 harmonic frequency points form a floating-point array.

[0041] Step 2, calculate the similarity between two consecutive frequency-domain current amplitude arrays, and judge the load access event and load access type on the load loop according to the similarity.

[0042] Calculating the similarity between two consecutive frequency-domain current amplitude arrays includes: the similarity Delta(A,B) of the frequency-domain current amplitudes between any two adjacent prediction moments A and B is:

[0043]

[0044] n is the number of the floating-point number in the floating-point array, N is the total number of floating-point numbers in the floating-point array, and N = 15;

[0045] An is the value of the nth floating-point number in the floating-point array at prediction moment A;

[0046] Bn is the value of the nth floating-point number in the floating-point array at prediction moment B.

[0047] In addition to calculating the similarity, it is also possible to analyze the amplitude difference at each frequency point between the previous time period and the next time period, construct a frequency-domain current amplitude difference array, and analyze the type of connected load according to the characteristics between different frequencies in the array. Determine the connected load according to the magnitude of the amplitude difference at different frequencies.

[0048] Judging the load access event and load access type on the load loop according to the similarity, including: if the similarity of the frequency-domain current amplitudes between any two adjacent prediction times A and B is greater than a first preset threshold, it is determined that a load access event has occurred between the two adjacent prediction times; the load access event includes a new load accessing the load loop, an old load exiting the load loop, and a change in the power of an old load.

[0049] If the similarity is greater than the first preset threshold, it is considered that a mutation has occurred in two sets of frequency-domain sampling values, and a new electrical device has accessed the load loop of the intelligent circuit breaker, or an old electrical device has exited the load loop, or an old electrical device has a power state transfer, such as air conditioner frequency adjustment, etc. In one embodiment, the first preset threshold is 0.2.

[0050] Preferably, judging the load access event and load access type on the load loop according to the similarity, including: if the similarity of the frequency-domain current amplitudes between any two adjacent prediction times A and B is less than a second preset threshold, it is determined that no load access event has occurred between the two adjacent prediction times; the second preset threshold is less than the first preset threshold.

[0051] If the similarity is less than the second preset threshold, it is considered that the two sets of eigenvalue meet the similarity requirement, and it is considered that no load access event has occurred between two consecutive times. In one embodiment, the second preset threshold is 0.06.

[0052] Different types of loads have different frequency-domain characteristics. By analyzing and calculating the typical historical periods under different load accesses, the current frequency-domain characteristics when a certain type of load accesses can be obtained. Store this characteristic in the software pre-installed in the intelligent circuit breaker in one or more different ways, such as the value range of different frequency points, the value difference characteristics between different frequency points, and the value range of the eigenvalue at the frequency point when a unit load accesses. To ensure that the pre-installed software can analyze the similarity between the current current frequency-domain eigenvalue and the pre-stored eigenvalue.

[0053] According to the acquisition method of frequency-domain sampling values and frequency-domain eigenvalues and the calculation method of the mutation of frequency-domain sampling values, after connecting the electric vehicle charging battery device to be identified to the load loop of the intelligent circuit breaker, when the software determines a mutation in the frequency-domain sampling values, analyze whether this mutation is caused by the charging current of the electric bicycle battery.

[0054] In one embodiment, the frequency-domain eigenvalue of the charging current of a certain type of electric bicycle is obtained in advance and stored in the storage unit of the intelligent circuit breaker. Taking T as the period, the real-time current frequency-domain sampling value of the breaker load circuit is obtained. If it is the first time to obtain the current frequency-domain sampling value after the intelligent circuit breaker is powered on and runs, no operation is performed, and this set of current frequency-domain sampling values is directly saved to the storage unit of the current frequency-domain sampling values of the previous period. If it is not the first time to obtain the current frequency-domain sampling value after the intelligent circuit breaker is powered on, using the current frequency-domain sampling value and the data stored in the storage unit of the current frequency-domain sampling values of the previous period as inputs, the mutation method of the frequency-domain sampling values is used to determine whether there is a new device connected to the current intelligent circuit breaker loop. When the software determines the mutation of the frequency-domain sampling values, using the current frequency-domain sampling values of the previous period and the current current frequency-domain sampling value as inputs, the frequency-domain eigenvalue of the newly connected device is calculated. Using the comparison method of the similarity of the frequency-domain eigenvalues, calculate the difference between the currently calculated frequency-domain eigenvalue and the frequency-domain eigenvalue of the charging current of the electric bicycle to be identified. If the similarity condition is met, an alarm is triggered; if the similarity condition is not met, the current current frequency-domain sampling value is saved to the storage unit of the current frequency-domain sampling values of the previous period.

[0055] Generally, due to cost requirements, the hardware platform used by intelligent circuit breakers has weak computing power, and the A / D acquisition frequency cannot reach a high level. Through the present invention, on the low-computation-level hardware platform of the intelligent circuit breaker, through a relatively simple software algorithm, without increasing additional product costs, the indoor charging identification of electric bicycles can be realized, greatly improving the product value of the intelligent circuit breaker and also greatly improving the residential electricity safety.

[0056] Judging the load access event and load access type on the load loop according to the similarity includes: normalizing the floating-point numbers in the floating-point number array in advance, and determining the first preset threshold and the second preset threshold according to the value range of the floating-point numbers.

[0057] In the second aspect of the present invention, it relates to a load access identification system based on an intelligent circuit breaker. The system includes a collection unit, a calculation unit, and an alarm unit. Among them, the collection unit is deployed on the intelligent circuit breaker and is used to collect the real-time current on the load loop corresponding to the intelligent circuit breaker. The calculation unit is used to calculate the frequency-domain current amplitude array at each prediction moment on the load loop, calculate the similarity between two consecutive frequency-domain current amplitude arrays, and judge the load access event and load access type on the load loop according to the similarity. The alarm unit is used to issue an alarm according to the load access event and load access type.

[0058] In the third aspect of the present invention, it relates to a terminal, including a processor and a storage medium. The storage medium is used to store instructions. The processor is used to operate according to the instructions to execute the steps of the method described in the first aspect of the present invention.

[0059] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that there are still contents in the technical solutions of the present invention that can modify the specific implementation manners of the present invention or make equivalent replacements. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention shall be covered by the protection scope of the claims of the present invention.

Claims

1. A load access recognition method based on an intelligent circuit breaker, characterized in that The method includes the following steps: Collect the real-time current on the load loop corresponding to the intelligent circuit breaker, and calculate the frequency-domain current amplitude array at each prediction moment on the load loop; Calculate the similarity between two consecutive frequency-domain current amplitude arrays, and judge the load access event and load access type on the load loop according to the similarity.

2. The method for identifying load access based on an intelligent circuit breaker according to claim 1, wherein: The step of collecting the real-time current on the load loop corresponding to the intelligent circuit breaker and calculating the frequency-domain current amplitude array at each prediction moment on the load loop includes: Collect real-time current sampling values within a preset time period, and obtain a frequency-domain curve through Fourier transform; Taking the power-frequency fundamental wave as the center point, select harmonic frequency-domain points on both sides of the power frequency, and collect the amplitudes of the frequency-domain curves at each harmonic frequency-domain point; Use the amplitudes of the frequency-domain curves at each harmonic frequency-domain point and the center point to construct the frequency-domain current amplitude array.

3. The method for identifying load access based on an intelligent circuit breaker according to claim 2, wherein: The step of calculating the frequency-domain current amplitude array at each prediction moment on the load loop includes: The distance between any two adjacent prediction moments is at least multiple power-frequency cycles, and the number of power-frequency cycles is determined by the accuracy of the Fourier transform.

4. The method for identifying load access based on an intelligent circuit breaker according to claim 3, wherein: The step of using the amplitudes of the frequency-domain curves at each harmonic frequency-domain point and the center point to construct the frequency-domain current amplitude array includes: The amplitudes of the frequency-domain curves at each harmonic frequency-domain point and the center point are saved in the form of floating-point numbers, and the frequency-domain current amplitude array is saved in the form of a floating-point number array.

5. The method for identifying load access based on an intelligent circuit breaker according to claim 4, wherein: The step of calculating the similarity between two consecutive frequency-domain current amplitude arrays includes: The similarity Delta(A,B) of the frequency-domain current amplitudes between any two adjacent prediction moments A and B is: n is the number of the floating-point number in the floating-point number array, and N is the total number of floating-point numbers in the floating-point number array; An is the value of the nth floating-point number in the floating-point number array at prediction moment A; Bn is the value of the nth floating-point number in the floating-point number array at prediction moment B.

6. The method for identifying load access based on an intelligent circuit breaker according to claim 5, wherein: The step of judging the load access event and load access type on the load loop according to the similarity includes: If the similarity of the frequency-domain current amplitudes between any two adjacent prediction moments A and B is greater than a first preset threshold, it is judged that a load access event has occurred between the two adjacent prediction moments; The load access event includes a new load accessing the load loop, an old load exiting the load loop, and a change in the power of the old load.

7. The method for identifying load access based on an intelligent circuit breaker according to claim 6, wherein: The step of judging the load access event and load access type on the load loop according to the similarity includes: If the similarity of the frequency-domain current amplitudes between any two adjacent prediction times A and B is less than a second preset threshold, it is determined that no load access event has occurred between the two adjacent prediction times; The second preset threshold is less than the first preset threshold.

8. The load access recognition method based on an intelligent circuit breaker according to claim 7, wherein: The judging of the load access event and the load access type on the load loop according to the similarity includes: Normalize the floating-point numbers in the floating-point number array in advance, and determine the first preset threshold and the second preset threshold according to the value range of the floating-point numbers.

9. A load access recognition system based on an intelligent circuit breaker, wherein: The system includes a collection unit, a calculation unit, and an alarm unit; wherein, The collection unit is deployed on the intelligent circuit breaker and is used to collect the real-time current on the load loop corresponding to the intelligent circuit breaker; The calculation unit is used to calculate the frequency-domain current amplitude array at each prediction time on the load loop, calculate the similarity between two consecutive frequency-domain current amplitude arrays, and judge the load access event and the load access type on the load loop according to the similarity; The alarm unit is used to issue an alarm according to the load access event and the load access type.

10. A terminal, comprising a processor and a storage medium; wherein: The storage medium is used to store instructions; The processor is used to operate according to the instructions to execute the steps of the method according to any one of claims 1-8.

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