A method and system for electricity safety processing based on a single-phase smart energy meter

Abstract

This application provides a method and system for handling electricity safety based on a single-phase smart energy meter. In this application, when a short circuit occurs, the current increases sharply. Therefore, it is necessary to first determine the change in electricity current. Furthermore, since the current waveform of a short circuit is highly similar to the waveform of a purely resistive load, to avoid misjudgment, after determining whether the rate of change of electricity current is higher than a preset rate of change, it is also necessary to construct the current waveform of a purely resistive load based on the electricity data collected by the single-phase smart energy meter. Then, the current waveform of the resistive load is compared with the current waveform corresponding to the electricity data collected by the single-phase smart energy meter. When the similarity is high, it indicates that the probability of a short circuit is high. At this time, it is necessary to process it according to the preset processing method. Through the above method, short circuit events can be quickly judged, reducing the probability of fire.

Description

Technical Field

[0001] This application relates to the field of intelligent control technology, and more specifically, to a method and system for handling electricity safety based on a single-phase smart energy meter. Background Technology

[0002] As people's lives become richer, the types of electrical appliances used in their homes are also increasing, and electrical safety is receiving more and more attention.

[0003] If a short circuit occurs in a household appliance or wiring, it can potentially cause a fire if not dealt with promptly. Short circuits are often difficult to detect and are only discovered after obvious events occur, such as smoke or fire. By then, it may be too late to control the situation. Therefore, there is an urgent need for a method to quickly identify short circuit events so that short circuits can be dealt with quickly and the probability of fire can be reduced. Summary of the Invention

[0004] In view of this, embodiments of this application provide a method and system for handling electricity safety based on a single-phase smart energy meter, so as to quickly determine short circuit events and reduce the probability of fire.

[0005] In a first aspect, embodiments of this application provide a method for handling electricity safety based on single-phase smart meters. This method operates within a smart grid system, which includes a cloud server and several single-phase smart meters. A communication connection is established between the single-phase smart meters and the cloud server. The electricity safety handling method includes:

[0006] For each single-phase smart energy meter, after collecting the current power consumption and the current grid voltage at a preset collection frequency, the single-phase smart energy meter calculates the current change rate corresponding to the single-phase smart energy meter based on the current power consumption.

[0007] The single-phase smart energy meter sends the current electricity consumption, the current grid voltage, and the rate of change of the electricity consumption to the cloud server in the form of data sets.

[0008] For each data group, the cloud server determines whether the rate of change of electricity current contained in the data group is higher than a preset rate of change.

[0009] If the rate of change of the current consumption is higher than the preset rate of change, the cloud server obtains a preset number of target data groups, and uses the target data groups and the data group as reference data groups, wherein the target data groups are a preset number of data groups sent by the single-phase smart energy meter after the data group.

[0010] For each reference data group, the cloud server calculates the current based on the current grid voltage and preset reference resistance in the reference data group, and uses the current corresponding to all the reference data groups as the standard current.

[0011] The cloud server compares the similarity between the waveform corresponding to the standard current and the waveform corresponding to the current power consumption contained in each reference data group.

[0012] When the similarity exceeds a preset threshold, the cloud server processes it according to a preset processing method.

[0013] Secondly, embodiments of this application provide an electricity safety processing system based on single-phase smart meters. The electricity safety processing system includes a cloud server and several single-phase smart meters, and a communication connection is established between the single-phase smart meters and the cloud server.

[0014] For each single-phase smart energy meter, the single-phase smart energy meter is used to collect the current current and the current grid voltage according to a preset collection frequency, calculate the current change rate corresponding to the single-phase smart energy meter based on the current current; and is used to send the current current, the current grid voltage and the current change rate to the cloud server in the form of a data set.

[0015] The cloud server is configured to: determine whether the rate of change of current in each data group is higher than a preset rate of change for each data group; and if the rate of change of current is higher than the preset rate of change, acquire a preset number of target data groups, using the target data groups and the data group as reference data groups, wherein the target data groups are a preset number of data groups sent by the single-phase smart energy meter following the data group; calculate the current for each reference data group based on the current grid voltage and a preset reference resistance, using the currents corresponding to all obtained reference data groups as standard currents; compare the similarity between the waveforms corresponding to the standard currents and the waveforms corresponding to the current currents in each reference data group; and process the data according to a preset processing method when the similarity is higher than a preset threshold.

[0016] The technical solution provided in this application includes, but is not limited to, the following beneficial effects:

[0017] In this application, when a short circuit occurs, the current increases sharply. Therefore, it is necessary to first determine the change in current consumption. Furthermore, since the current waveform of a short circuit is highly similar to that of a purely resistive load, to avoid misjudgment, after determining whether the rate of change of current consumption is higher than a preset rate of change, it is also necessary to construct the current waveform of a purely resistive load based on the electricity consumption data collected by the single-phase smart energy meter. Then, the current waveform of the resistive load is compared with the current waveform corresponding to the electricity consumption data collected by the single-phase smart energy meter. When the similarity between the two is high, it indicates that the probability of a short circuit is high. At this time, it is necessary to process it according to the preset processing method. Through the above method, a short circuit event can be quickly judged, reducing the probability of fire.

[0018] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 A schematic diagram of a smart grid system provided in an embodiment of this application;

[0021] Figure 2 A flowchart illustrating an electricity safety processing method based on a single-phase smart energy meter, provided as an embodiment of this application;

[0022] Figure 3 This is a schematic diagram of a power safety processing system based on a single-phase smart energy meter, provided as an embodiment of this application. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0024] Figure 1 A schematic diagram of a smart grid system provided in this application embodiment is shown below. Figure 1 As shown, the smart grid system includes a cloud server and several single-phase smart meters. A communication connection is established between the single-phase smart meters and the cloud server so that the single-phase smart meters can upload the collected data to the cloud server for processing. For example, the single-phase smart meters can transmit the collected data in real time to the home energy gateway (Edge Gateway) or directly upload it to the cloud platform in the form of a stream through communication methods such as Bluetooth, Wi-Fi, Zigbee or NB-IoT.

[0025] Figure 2 This is a flowchart illustrating a method for handling electricity safety based on a single-phase smart meter, as provided in an embodiment of this application. The method operates within a smart grid system. Figure 2 As shown, this electrical safety handling method includes the following steps:

[0026] Step 201: For each single-phase smart energy meter, after collecting the current power consumption and the current grid voltage at a preset collection frequency, the single-phase smart energy meter calculates the current change rate corresponding to the current consumption based on the current power consumption.

[0027] Step 202: The single-phase smart energy meter sends the current power consumption, the current grid voltage, and the rate of change of the power consumption to the cloud server in the form of data packets.

[0028] Step 203: For each data group, the cloud server determines whether the rate of change of electricity current contained in the data group is higher than the preset rate of change.

[0029] Step 204: If the rate of change of the electricity consumption current is higher than the preset rate of change, the cloud server obtains a preset number of target data groups, and uses the target data groups and the data group as reference data groups, wherein the target data groups are a preset number of data groups sent by the single-phase smart energy meter after the data group.

[0030] Step 205: For each reference data group, the cloud server calculates the current based on the current grid voltage and preset reference resistance in the reference data group, and uses the current corresponding to all the reference data groups as the standard current.

[0031] Step 206: The cloud server performs a similarity comparison between the waveform corresponding to the standard current and the waveform corresponding to the current power consumption contained in each reference data group.

[0032] Step 207: When the similarity is higher than the preset threshold, the cloud server processes it according to the preset processing method.

[0033] Specifically, single-phase smart meters are used to introduce mains power into household electricity consumption and measure electricity usage. During use, single-phase smart meters can collect electricity parameters such as current, voltage, and grid voltage at a preset sampling frequency. After collecting these parameters, the single-phase smart meter can calculate and display the household electricity consumption, and also upload these parameters to a cloud server for further processing. The upload frequency of the single-phase smart meter is the same as the sampling frequency.

[0034] To enable rapid short-circuit detection and reduce the computational burden on cloud servers, single-phase smart meters, after collecting the current electricity consumption, calculate the corresponding rate of change of current based on the parameters they acquire. Since the computational load is relatively small, single-phase smart meters can process this data quickly, thus alleviating the computational burden on cloud servers.

[0035] After obtaining the current change rate, the single-phase smart energy meter sends the current current, current grid voltage, and current change rate as a data set to the cloud server. Since household current rises rapidly during a short circuit, the current change rate can provide a preliminary indication of a short circuit. However, this rise could also be due to leakage or the addition of high-power electrical equipment. Therefore, when the cloud server determines that the current change rate is higher than a preset rate, further analysis is needed to accurately determine if a short circuit has actually occurred. This requires continuously acquiring other consecutive data sets following this one (i.e., the target data set). After obtaining a preset number of other data sets, the current is calculated based on the current grid voltage and a preset reference resistance in each reference data set. The current corresponding to the reference data set is used as the standard current, which is the current corresponding to the grid voltage under a purely resistive load. Then, the waveform corresponding to the standard current is compared with the waveform corresponding to the current electricity consumption in each reference data set. If the similarity is higher than a preset threshold, it means that the current household electricity consumption is very similar to that of a purely resistive load. In addition, the rate of change of the current consumption is high, so it can be determined that the probability of a short circuit is high. Therefore, when it is determined that the similarity is higher than the preset threshold, the cloud server can handle it according to the preset processing method, such as power outage. Since each single-phase smart meter has a corresponding user and can query the user's contact information, location, and other information, it can also send a prompt message to the user, send a prompt message to the organization managing the household, or send a prompt message with the household's address to the fire department for rapid human intervention.

[0036] In this application, when a short circuit occurs, the current increases sharply. Therefore, it is necessary to first determine the change in current consumption. Furthermore, since the current waveform of a short circuit is highly similar to that of a purely resistive load, to avoid misjudgment, after determining whether the rate of change of current consumption is higher than a preset rate of change, it is also necessary to construct the current waveform of a purely resistive load based on the electricity consumption data collected by the single-phase smart energy meter. Then, the current waveform of the resistive load is compared with the current waveform corresponding to the electricity consumption data collected by the single-phase smart energy meter. When the similarity between the two is high, it indicates that the probability of a short circuit is high. At this time, it is necessary to process it according to the preset processing method. Through the above method, a short circuit event can be quickly judged, reducing the probability of fire.

[0037] In one feasible implementation, the acquisition frequency is greater than 1 kHz.

[0038] Specifically, since the frequency of mains power is generally 50Hz, using a sampling frequency of 1kHz can ensure that a sufficient amount of data is collected within one cycle for accurate judgment.

[0039] It should be noted that the sampling frequency can also be less than 1kHz for quick and rough judgment. The specific sampling frequency can be set according to actual needs, and no specific limit is set here.

[0040] In a feasible implementation, when performing step 201, which involves calculating the rate of change of current corresponding to the single-phase smart energy meter based on the current current consumption, formula one can be used for calculation:

[0041] ΔI = I[t] - I[t-1];

[0042] dI / dt = ΔI / Δt; Formula 1

[0043] Where I[t] is the current collected at the t-th sampling point, I[t-1] is the current collected at the (t-1)-th sampling point, t is a positive integer greater than 1, ΔI is the change in current, Δt is the sampling interval, and dI / dt is the rate of change of current.

[0044] In one feasible implementation, the preset quantity is the product of the single-phase AC cycle corresponding to the current grid voltage and the sampling frequency.

[0045] Specifically, when the preset quantity is the product of the single-phase AC cycle corresponding to the current grid voltage and the sampling frequency, the preset quantity can just cover one single-phase AC cycle, so that the current waveform corresponding to one single-phase AC cycle can be compared, thereby improving the accuracy of the judgment.

[0046] In a feasible implementation, when performing step 206, similarity comparison can be performed using Formula 2:

[0047] r = Σ((I[n]-μ_i)×(R_ref[n]-μ_R)) / (σ_i×σ_R); Formula 2

[0048] Wherein, I[n] is the current current corresponding to the nth reference data group, μ_i is the average value of the current current included in each reference data group within the single-phase AC cycle, R_ref[n] is the standard current corresponding to the nth reference data group, μ_R is the average value of the standard current within the single-phase AC cycle, σ_i is the standard deviation of the current current included in each reference data group within the single-phase AC cycle, and σ_R is the standard deviation of the standard current within the single-phase AC cycle.

[0049] Specifically, I[n]-μ_i is used to eliminate the influence of the DC component, resulting in an AC signal with a mean of 0, causing its variation to fluctuate around zero. This is used to represent the decentralized value of the current current. R_ref[n] is the current corresponding to the purely resistive load, which can form an ideal sine wave. Since it is obtained from each reference data set, R_ref[n] and I[n] have the same period, and the sampling points of R_ref[n] and I[n] are in one-to-one correspondence. Similarly, R_ref[n]-μ_R is used to obtain a pure reference AC signal with a mean of 0, that is, the decentralized value of the reference AC signal is completed.

[0050] (I[n]-μ_i)×(R_ref[n]-μ_R) represents the covariance of two decentralized signals, used to measure the consistency of the two signals in the direction of change. If at the same moment, both signals are above their respective means (multiplication of two positive numbers) or below their respective means (multiplication of two negative numbers), the product is positive. If one is above the mean and the other is below the mean (multiplication of positive and negative numbers), the product is negative. The numerator is the sum of these products at all times. If the two signals have the same trend of change, the positive product will be much more than the negative product, and the numerator will be a very large positive number, causing r to tend to 1. σ_i×σ_R is the product of the standard deviations of the two signals. It is a standardization factor used to scale the correlation coefficient r to the range [-1, 1]. Without a denominator, the value of the numerator will be greatly affected by the fluctuation amplitude of the signals themselves (σ_i and σ_R). Dividing by (σ_i × σ_R) After that, the influence of signal amplitude is eliminated, and r only reflects the similarity of two signals in "shape" and "trend" without caring about their absolute size.

[0051] The subsequent I[n] is called the actual current, and R_ref[n] is called the reference current.

[0052] When a short circuit occurs:

[0053] The actual current becomes a perfect sine wave with a huge amplitude and in phase with the voltage, while the reference current is an artificially generated perfect sine wave in phase with the voltage. At this point, the waveforms of the actual current and the reference current are exactly the same, only the amplitudes are different.

[0054] Numerator: Since the trend of change is always consistent, the summation results in a very large positive number. Denominator: The standard deviations of the two signals, σ_i and σ_R, are also positive numbers. The final calculated value of r will be infinitely close to 1. For example, when the preset threshold is 0.995, the cloud server can accurately determine that a short circuit has occurred when it detects that r>0.995 and the current increases sharply.

[0055] Formula 2 measures the degree of linear correlation between two signals in terms of their changing trends, with the range of r being [-1, 1].

[0056] r=1: Perfect positive correlation, if one signal increases, the other signal also increases by a fixed proportion;

[0057] r=-1: Perfect negative correlation, when one signal increases, the other signal decreases by a fixed proportion;

[0058] r=0: Uncorrelated, the changes of the two signals have no linear relationship.

[0059] In one feasible implementation, the preset threshold is 0.995.

[0060] It should be noted that the preset threshold can be adjusted according to actual needs, and the specific value is not specified here.

[0061] In one feasible implementation, when the cloud server issues an early warning for the single-phase smart meter, it can send a reminder message to the phone number corresponding to the single-phase smart meter; and / or control the single-phase smart meter to cut off power.

[0062] Figure 3 This is a schematic diagram of a power safety processing system based on a single-phase smart energy meter, provided in an embodiment of this application. The power safety processing system includes a cloud server 301 and several single-phase smart energy meters 302, and a communication connection is established between the single-phase smart energy meters and the cloud server.

[0063] For each single-phase smart energy meter 302, the single-phase smart energy meter 302 is used to collect the current current and the current grid voltage according to a preset collection frequency, calculate the current change rate corresponding to the single-phase smart energy meter based on the current current; and is used to send the current current, the current grid voltage and the current change rate to the cloud server in the form of a data set.

[0064] The cloud server 301 is configured to: determine whether the rate of change of current in each data group is higher than a preset rate of change; and if the rate of change of current is higher than the preset rate of change, acquire a preset number of target data groups, using the target data groups and the data group as reference data groups, wherein the target data groups are a preset number of data groups sent by the single-phase smart energy meter following the data group; calculate the current for each reference data group based on the current grid voltage and a preset reference resistance, using the current corresponding to all the obtained reference data groups as standard currents; compare the similarity between the waveform corresponding to the standard current and the waveform corresponding to the current current in each reference data group; and process the data according to a preset processing method when the similarity is higher than a preset threshold.

[0065] In one feasible implementation, the acquisition frequency is greater than 1 kHz.

[0066] In one feasible implementation, when the single-phase smart energy meter is used to calculate the rate of change of the current corresponding to the single-phase smart energy meter based on the current current consumption, it includes:

[0067] The rate of change of the electrical current is calculated using the following formula:

[0068] ΔI = I[t] - I[t-1];

[0069] dI / dt=ΔI / Δt; Formula 3

[0070] Where I[t] is the current collected at the t-th sampling point, I[t-1] is the current collected at the (t-1)-th sampling point, t is a positive integer greater than 1, ΔI is the change in current, Δt is the sampling interval, and dI / dt is the rate of change of current.

[0071] In one feasible implementation, the preset quantity is the product of the single-phase AC cycle corresponding to the current grid voltage and the sampling frequency.

[0072] In one feasible implementation, the cloud server performs a similarity comparison between the waveform corresponding to the standard current and the waveform corresponding to the current power consumption contained in each reference data group, including:

[0073] Similarity comparison is performed according to the following formula (4):

[0074] r = Σ((I[n]-μ_i)×(R_ref[n]-μ_R)) / (σ_i×σ_R); Formula 4

[0075] Wherein, I[n] is the current current corresponding to the nth reference data group, μ_i is the average value of the current current included in each reference data group within the single-phase AC cycle, R_ref[n] is the standard current corresponding to the nth reference data group, μ_R is the average value of the standard current within the single-phase AC cycle, σ_i is the standard deviation of the current current included in each reference data group within the single-phase AC cycle, and σ_R is the standard deviation of the standard current within the single-phase AC cycle.

[0076] In one feasible implementation, the preset threshold is 0.995.

[0077] In one feasible implementation, the cloud server provides early warnings for the single-phase smart meter, including:

[0078] Send a reminder message to the phone number corresponding to the single-phase smart energy meter; and / or,

[0079] Control the single-phase smart energy meter to cut off power.

[0080] about Figure 3 The principles behind the content shown can be found in the following references. Figure 1 and Figure 2 The relevant explanations are not specifically limited here.

[0081] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some communication interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0082] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0083] In addition, the functional units in the embodiments provided in this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0084] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0085] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. In addition, the terms "first", "second", "third", etc. are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0086] Finally, it should be noted that the above-described embodiments are merely specific implementations of this application, used to illustrate the technical solutions of this application, and not to limit them. The protection scope of this application is not limited thereto. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments, or make equivalent substitutions for some of the technical features, within the scope of the technology disclosed in this application; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application. All should be covered within the protection scope of this application. Therefore, the protection scope of this application should be determined by the protection scope of the claims.

Claims

1. A method for handling electricity safety based on a single-phase smart energy meter, characterized in that, The electricity safety processing method operates in a smart grid system, which includes a cloud server and several single-phase smart meters. A communication connection is established between the single-phase smart meters and the cloud server. The electricity safety processing method includes: For each single-phase smart energy meter, after collecting the current power consumption and the current grid voltage at a preset collection frequency, the single-phase smart energy meter calculates the current change rate corresponding to the single-phase smart energy meter based on the current power consumption. The single-phase smart energy meter sends the current electricity consumption, the current grid voltage, and the rate of change of the electricity consumption to the cloud server in the form of data sets. For each data group, the cloud server determines whether the rate of change of electricity current contained in the data group is higher than a preset rate of change. If the rate of change of the current consumption is higher than the preset rate of change, the cloud server obtains a preset number of target data groups, and uses the target data groups and the data group as reference data groups, wherein the target data groups are a preset number of data groups sent by the single-phase smart energy meter after the data group. For each reference data group, the cloud server calculates the current based on the current grid voltage and preset reference resistance in the reference data group, and uses the current corresponding to all the reference data groups as the standard current, wherein the standard current is the current corresponding to the grid voltage under a purely resistive load. The cloud server compares the similarity between the waveform corresponding to the standard current and the waveform corresponding to the current power consumption contained in each reference data group. When the similarity is higher than a preset threshold, the cloud server processes the data according to a preset processing method. When the similarity is higher than the preset threshold, it indicates that a short circuit has occurred.

2. The electrical safety handling method as described in claim 1, characterized in that, The sampling frequency is greater than 1 kHz.

3. The electrical safety handling method as described in claim 1, characterized in that, The step of calculating the rate of change of current corresponding to the single-phase smart energy meter based on the current current consumption includes: The rate of change of the electrical current is calculated using the following formula: ΔI = I[t] - I[t-1]; dI / dt = ΔI / Δt; Where I[t] is the current collected at the t-th sampling point, I[t-1] is the current collected at the (t-1)-th sampling point, t is a positive integer greater than 1, ΔI is the change in current, Δt is the sampling interval, and dI / dt is the rate of change of current.

4. The electrical safety handling method as described in claim 1, characterized in that, The preset quantity is the product of the single-phase AC cycle corresponding to the current grid voltage and the acquisition frequency.

5. The electrical safety handling method as described in claim 4, characterized in that, The cloud server performs a similarity comparison between the waveform corresponding to the standard current and the waveform corresponding to the current power consumption contained in each reference data group, including: Similarity comparison is performed using the following formula: r = Σ((I[n]-μ_i)×(R_ref[n]-μ_R)) / (σ_i×σ_R); Wherein, I[n] is the current current corresponding to the nth reference data group, μ_i is the average value of the current current included in each reference data group within the single-phase AC cycle, R_ref[n] is the standard current corresponding to the nth reference data group, μ_R is the average value of the standard current within the single-phase AC cycle, σ_i is the standard deviation of the current current included in each reference data group within the single-phase AC cycle, and σ_R is the standard deviation of the standard current within the single-phase AC cycle.

6. The electrical safety handling method as described in claim 1, characterized in that, The preset threshold is 0.

995.

7. The electrical safety handling method as described in claim 1, characterized in that, The cloud server provides early warnings for the single-phase smart meter, including: Send a reminder message to the phone number corresponding to the single-phase smart energy meter; and / or, Control the single-phase smart energy meter to cut off power.

8. A power safety processing system based on a single-phase smart energy meter, characterized in that, The electricity safety processing system includes a cloud server and several single-phase smart meters, and a communication connection is established between the single-phase smart meters and the cloud server; For each single-phase smart energy meter, after collecting the current current and the current grid voltage at a preset collection frequency, the single-phase smart energy meter calculates the rate of change of the current corresponding to the single-phase smart energy meter based on the current current. And for sending the current power consumption, the current grid voltage, and the rate of change of the power consumption in the form of a data set to the cloud server; The cloud server is used to determine, for each data group, whether the rate of change of electricity current contained in the data group is higher than a preset rate of change. The system is configured to: acquire a preset number of target data groups if the rate of change of the current consumption is higher than the preset rate of change, and use the target data groups and the data groups as reference data groups, wherein the target data groups are a preset number of data groups sent by the single-phase smart energy meter after the data groups; calculate the current for each reference data group based on the current grid voltage and a preset reference resistance in the reference data group, and use the currents corresponding to all the obtained reference data groups as standard currents, wherein the standard current is the current corresponding to the grid voltage under a purely resistive load; compare the similarity between the waveform corresponding to the standard current and the waveform corresponding to the current consumption included in each reference data group; and process the data according to a preset processing method when the similarity is higher than a preset threshold, wherein when the similarity is higher than the preset threshold, it indicates that a short circuit has occurred.

9. The electrical safety processing system as described in claim 8, characterized in that, The sampling frequency is greater than 1 kHz.

10. The electrical safety processing system as described in claim 8, characterized in that, When the single-phase smart energy meter is used to calculate the rate of change of the current corresponding to the current consumption based on the current consumption, it includes: The rate of change of the electrical current is calculated using the following formula: ΔI = I[t] - I[t-1]; dI / dt = ΔI / Δt; Where I[t] is the current collected at the t-th sampling point, I[t-1] is the current collected at the (t-1)-th sampling point, t is a positive integer greater than 1, ΔI is the change in current, Δt is the sampling interval, and dI / dt is the rate of change of current.

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