A method, system, device and storage medium for controlling power load of a charging and swapping station

Abstract

The present application relates to a method, system, device and storage medium for controlling the power load of a charging and swapping station, and relates to the field of power supply technology. The method includes obtaining the temperature change curve, power change curve, total power of the power consumption side and multiple historical temperature change curves of the current charging of the charging equipment on each branch on the power consumption side. If the total power on the power consumption side reaches a preset power threshold, the characteristic value representing the current charging state of each branch is determined based on the temperature change curve and the power change curve, the probability of an abnormality in each branch is determined based on the characteristic value and multiple historical temperature change curves, the number of branches that need to be disconnected based on the probability of an abnormality in each branch is determined, the target branch of the number of branches is determined based on the probability and the power change curve, and the connection of the target branch is controlled to be disconnected. The present application can determine the appropriate number of branches to be disconnected and accurately determine the branches that need to be disconnected first.

Description

Technical Field

[0001] The present application relates to the field of power supply technology, and in particular to a method, system, equipment and storage medium for controlling power load in a charging and swapping station. Background Art

[0002] Charging and battery swapping stations are places where new energy vehicles can be charged and their batteries swapped. They are equipped with a large number of charging devices, such as charging piles for new energy vehicles and chargers for batteries. However, since charging and battery swapping stations have a fixed maximum power capacity, when a large number of vehicles or batteries are being charged, the total power consumption on the power supply side can easily exceed the maximum power capacity of the charging and battery swapping station, causing power line tripping, equipment damage, and even fire. To maintain a safe power level on the power supply side, some branches need to be disconnected when the power consumption side is too high. However, determining the appropriate number of branches to disconnect and which branches to disconnect first becomes a problem. Summary of the Invention

[0003] In order to determine the appropriate number of branches to be disconnected and accurately determine the branches that need to be disconnected first, the present application provides a method, system, device and storage medium for controlling the power load of a charging and swapping station.

[0004] In a first aspect, the present application provides a method for controlling the power load of a charging and swapping station, which adopts the following technical solution:

[0005] A method for regulating power load in a charging and swapping station, comprising:

[0006] Obtain the temperature change curve, power change curve, total power of the power consumption side, and multiple historical temperature change curves of the charging equipment on each branch on the power consumption side for the current charging time;

[0007] If the total power on the power consumption side reaches a preset power threshold, a characteristic value representing the current charging state of each branch is determined based on the temperature change curve and the power change curve;

[0008] Determining the probability of an abnormality occurring in each branch based on the characteristic value and a plurality of historical temperature change curves;

[0009] Determine the number of branches that need to be disconnected based on the probability of an abnormality occurring in each branch;

[0010] A target branch of the number of branches is determined based on the probability and the power variation curve, and the target branch is disconnected through control.

[0011] By adopting the above technical solution, the temperature change curve, power change curve, total power of the power consumption side and historical temperature change curve of the power consumption side branch are obtained, which facilitates the subsequent accurate analysis of the branch that needs to be disconnected. When the total power of the power consumption side reaches the preset power threshold, it means that the total power of the power consumption side is too high, and it is necessary to disconnect the power supply of some branches to ensure that the power of the power consumption side remains at a safe level. The temperature change curve represents the temperature change of the charging equipment on the branch during operation. According to the temperature change curve, the probability of abnormal heating and potential fire of the charging equipment can be analyzed. The power change curve represents the power change during operation of the charging equipment. According to the power change and the power value at each moment, the current and voltage on the branch and the stability of the charging process can be determined. There is a correlation between the temperature change curve and the power change curve, that is, temperature change affects power change, and power change can also affect temperature change. Therefore, according to the temperature change curve and the power change curve The line can determine the characteristic value of the charging status of each branch. The size of the characteristic value is related to the probability of abnormality in the branch. The historical temperature change curve records the temperature change of the branch during operation in the past period of time. Analysis of the historical temperature change curve can, to a certain extent, analyze the probability of abnormality in each branch. Therefore, it is more accurate to determine the probability of abnormality in each branch based on the characteristic value and the historical temperature change curve. The probability of abnormality in all branches can reflect the overall probability level of the power consumption side, and then the appropriate number of branches that need to be disconnected from the power supply can be determined based on these probabilities. According to the determined probability and the power change curve, a comprehensive analysis can be made of the target branches that are more suitable for disconnecting the power supply, that is, the target branches with a higher probability of potential abnormality and a higher power value level, that is, the branches that need to be disconnected first, and finally the power supply connections of these target branches are disconnected so that the power consumption side is kept at a safe level.

[0012] In another possible implementation, determining a characteristic value representing a current charging state of each branch based on the temperature variation curve and the power variation curve includes:

[0013] Determine from the temperature change curve the maximum temperature value, the temperature value at the current moment, and a first curve segment whose slope is less than a preset slope threshold, and determine the average temperature value of the first curve segment;

[0014] Calculating the difference between the maximum temperature value and the average temperature value, and determining the power value at the current moment from the power change curve;

[0015] Determine a first product of the temperature value at the current moment and the power value at the current moment, and calculate a ratio of the first product to the difference to obtain a first sub-eigenvalue;

[0016] Extracting a second curve segment from the power variation curve according to the starting time and the ending time of the first curve segment, and determining the power variance of the second curve segment;

[0017] Determine a second product of the duration of the first curve segment, the temperature average, and the power variance to obtain a second sub-eigenvalue;

[0018] The eigenvalue is determined based on the first sub-eigenvalue, the second sub-eigenvalue, and their corresponding weights.

[0019] In another possible implementation, determining the eigenvalue based on the first sub-eigenvalue, the second sub-eigenvalue, and their corresponding weights includes:

[0020] determining a ratio of the second curve segment to the power change curve, and determining the ratio as a weight corresponding to the second sub-eigenvalue;

[0021] Subtract the proportion from 1 to obtain the weight corresponding to the first sub-eigenvalue;

[0022] The eigenvalue is obtained by performing weighted calculation on the first sub-eigenvalue, the second sub-eigenvalue, and their corresponding weights.

[0023] In another possible implementation, the multiple historical temperature change curves include multiple first historical temperature change curves when the charging device operates normally and multiple second historical temperature change curves when the charging device operates abnormally. Determining the probability of an abnormality occurring in each branch based on the characteristic value and the multiple historical temperature change curves includes:

[0024] Fitting the plurality of second historical temperature change curves to obtain a reference change curve;

[0025] Calculating a first similarity between the reference change curve and a plurality of preset temperature anomaly curves;

[0026] calculating a second similarity between the temperature change curve and each first historical temperature change curve;

[0027] averaging all first similarities to obtain a first similarity average, and averaging all second similarities to obtain a second similarity average;

[0028] Determine a ratio of the first similarity average value to the second similarity average value to obtain a temperature characteristic value related to a temperature anomaly probability;

[0029] The product of the characteristic value and the temperature characteristic value is calculated to obtain an abnormality score, and the probability of abnormality occurring in each branch is determined based on the abnormality score.

[0030] In another possible implementation, determining the number of branches that need to be disconnected based on the probability of an abnormality occurring in each branch includes:

[0031] Draw a histogram based on the probability of each branch and the preset probability interval;

[0032] Determine a target interval with the most branches from the histogram, and calculate the average probability value within the target interval;

[0033] The number of branches is determined based on the probability average and the number of branches in a target interval.

[0034] In another possible implementation, determining the number of branches based on the probability average and the number of branches in the target interval includes:

[0035] A score is obtained by performing weighted calculation based on the probability average, the number of branches in the target interval, and the corresponding coefficients;

[0036] A target preset score interval where the score is located is determined from multiple preset score intervals, each preset score interval corresponds to a preset number of branches, and the preset number of branches in the target preset score interval is determined as the number of branches.

[0037] In another possible implementation, determining the target number of branches based on the probability and the power variation curve includes:

[0038] Sort all branches from largest to smallest according to the probability to obtain a first sorting result;

[0039] Determine the power value of each branch at a current moment from the power change curve of each branch, and sort all branches from large to small according to the power value at the current moment to obtain a second sorting result;

[0040] Determine the ranking of each branch in the first sorting result and the second sorting result, and sum the rankings in the first sorting result and the second sorting result to obtain a comprehensive ranking score for each branch;

[0041] Sort all branches from largest to smallest according to the comprehensive ranking scores to obtain a third ranking result;

[0042] The target branches of the number of branches are determined in ascending order from the third sorting results.

[0043] In a second aspect, the present application provides a power load control system for a charging and swapping station, which adopts the following technical solutions:

[0044] A power load control system for a charging and swapping station, comprising:

[0045] A curve acquisition module is used to obtain the temperature change curve, power change curve, total power of the power consumption side, and multiple historical temperature change curves of the charging equipment on each branch on the power consumption side;

[0046] a characteristic value determination module, configured to determine a characteristic value representing the current charging state of each branch based on the temperature change curve and the power change curve when the total power on the power consumption side reaches a preset power threshold;

[0047] A probability determination module, configured to determine the probability of an abnormality occurring in each branch based on the characteristic value and a plurality of historical temperature change curves;

[0048] A quantity determination module is used to determine the number of branches that need to be disconnected based on the probability of an abnormality occurring in each branch;

[0049] A control module is used to determine a target branch of the number of branches based on the probability and the power change curve, and control the disconnection of the target branch.

[0050] By adopting the above technical solution, the curve acquisition module obtains the temperature change curve, power change curve, total power of the power consumption side and historical temperature change curve of the power consumption side branch, which is convenient for subsequent accurate analysis of the branch that needs to be disconnected. The total power of the power consumption side reaches the preset power threshold, which means that the total power of the power consumption side is too high, and it is necessary to disconnect the power supply of some branches to ensure that the power of the power consumption side remains at a safe level. The temperature change curve represents the temperature change of the charging equipment on the branch during operation. According to the temperature change curve, the probability of abnormal heating and potential fire of the charging equipment can be analyzed. The power change curve represents the power change during operation of the charging equipment. According to the power change and the power value at each moment, the current and voltage on the branch and the stability of the charging process can be determined. There is a correlation between the temperature change curve and the power change curve, that is, temperature change affects power change, and power change can also affect temperature change. Therefore, the characteristic value determination module determines the characteristic value based on the temperature change curve and the power change curve. It is possible to determine the characteristic value of the charging status of each branch. The size of the characteristic value is related to the probability of abnormality in the branch. The historical temperature change curve records the temperature change of the branch during operation in the past period of time. Analyzing the historical temperature change curve can, to a certain extent, analyze the probability of each branch being abnormal. Therefore, the probability determination module determines the probability of abnormality in each branch more accurately based on the characteristic value and the historical temperature change curve. The probability of abnormality in all branches can reflect the overall probability level of the power consumption side. Then, the quantity determination module can determine the appropriate number of branches that need to be disconnected based on these probabilities. The control module can comprehensively analyze the target branches that are more suitable for disconnecting the power supply based on the determined probabilities and power change curves, that is, the target branches with a higher potential probability of abnormality and a higher power value level, that is, the branches that need to be disconnected first, and finally disconnect the power supply connections of these target branches so that the power consumption side is kept at a safe level.

[0051] In another possible implementation, when the characteristic value determination module determines the characteristic value representing the current charging state of each branch based on the temperature change curve and the power change curve, it is specifically configured to:

[0052] Determine from the temperature change curve the maximum temperature value, the temperature value at the current moment, and a first curve segment whose slope is less than a preset slope threshold, and determine the average temperature value of the first curve segment;

[0053] Calculating the difference between the maximum temperature value and the average temperature value, and determining the power value at the current moment from the power change curve;

[0054] Determine a first product of the temperature value at the current moment and the power value at the current moment, and calculate a ratio of the first product to the difference to obtain a first sub-eigenvalue;

[0055] Extracting a second curve segment from the power variation curve according to the starting time and the ending time of the first curve segment, and determining the power variance of the second curve segment;

[0056] Determine a second product of the duration of the first curve segment, the temperature average, and the power variance to obtain a second sub-eigenvalue;

[0057] The eigenvalue is determined based on the first sub-eigenvalue, the second sub-eigenvalue, and their corresponding weights.

[0058] In another possible implementation, when determining the eigenvalue based on the first sub-eigenvalue, the second sub-eigenvalue, and their corresponding weights, the eigenvalue determination module is specifically configured to:

[0059] determining a ratio of the second curve segment to the power change curve, and determining the ratio as a weight corresponding to the second sub-eigenvalue;

[0060] Subtract the proportion from 1 to obtain the weight corresponding to the first sub-eigenvalue;

[0061] The eigenvalue is obtained by performing weighted calculation on the first sub-eigenvalue, the second sub-eigenvalue, and their corresponding weights.

[0062] In another possible implementation, the multiple historical temperature change curves include multiple first historical temperature change curves when the charging device operates normally and multiple second historical temperature change curves when the charging device operates abnormally. When determining the probability of an abnormality occurring in each branch based on the characteristic value and the multiple historical temperature change curves, the probability determination module is specifically configured to:

[0063] Fitting the plurality of second historical temperature change curves to obtain a reference change curve;

[0064] Calculating a first similarity between the reference change curve and a plurality of preset temperature anomaly curves;

[0065] calculating a second similarity between the temperature change curve and each first historical temperature change curve;

[0066] averaging all first similarities to obtain a first similarity average, and averaging all second similarities to obtain a second similarity average;

[0067] Determine a ratio of the first similarity average value to the second similarity average value to obtain a temperature characteristic value related to a temperature anomaly probability;

[0068] The product of the characteristic value and the temperature characteristic value is calculated to obtain an abnormality score, and the probability of abnormality occurring in each branch is determined based on the abnormality score.

[0069] In another possible implementation, when determining the number of branches that need to be disconnected based on the probability of an abnormality occurring in each branch, the number determination module is specifically configured to:

[0070] Draw a histogram based on the probability of each branch and the preset probability interval;

[0071] Determine a target interval with the most branches from the histogram, and calculate the average probability value within the target interval;

[0072] The number of branches is determined based on the probability average and the number of branches in a target interval.

[0073] In another possible implementation, when the number determination module determines the number of branches based on the probability average and the number of branches in the target interval, it is specifically configured to:

[0074] A score is obtained by performing weighted calculation based on the probability average, the number of branches in the target interval, and the corresponding coefficients;

[0075] A target preset score interval where the score is located is determined from multiple preset score intervals, each preset score interval corresponds to a preset number of branches, and the preset number of branches in the target preset score interval is determined as the number of branches.

[0076] In another possible implementation, when the control module determines the target number of branches based on the probability and the power variation curve, it is specifically configured to:

[0077] Sort all branches from largest to smallest according to the probability to obtain a first sorting result;

[0078] Determine the power value of each branch at a current moment from the power change curve of each branch, and sort all branches from large to small according to the power value at the current moment to obtain a second sorting result;

[0079] Determine the ranking of each branch in the first sorting result and the second sorting result, and sum the rankings in the first sorting result and the second sorting result to obtain a comprehensive ranking score for each branch;

[0080] Sort all branches from largest to smallest according to the comprehensive ranking scores to obtain a third ranking result;

[0081] The target branches of the number of branches are determined in ascending order from the third sorting results.

[0082] In a third aspect, the present application provides an electronic device, which adopts the following technical solution:

[0083] An electronic device, comprising:

[0084] at least one processor;

[0085] Memory;

[0086] At least one application, wherein at least one application is stored in a memory and configured to be executed by at least one processor, and at least one is configured to: execute a method for regulating power load at a charging and swapping station according to any possible implementation of the first aspect.

[0087] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution:

[0088] A computer-readable storage medium, when the computer program is executed in a computer, causes the computer to execute the method for regulating the power load of a charging and swapping station as described in any one of the first aspects.

[0089] In summary, this application includes at least one of the following beneficial technical effects:

[0090] Obtaining the temperature change curve, power change curve, total power of the power consumption side and historical temperature change curve of the power consumption side branch facilitates subsequent accurate analysis of the branch that needs to be disconnected. When the total power of the power consumption side reaches the preset power threshold, it means that the total power of the power consumption side is too high, and it is necessary to disconnect the power supply of some branches to ensure that the power of the power consumption side remains at a safe level. The temperature change curve represents the temperature change of the charging equipment on the branch during operation. According to the temperature change curve, the probability of abnormal heating and potential fire in the charging equipment can be analyzed. The power change curve represents the power change during the operation of the charging equipment. According to the power change and the power value at each moment, the current and voltage on the branch and the stability of the charging process can be determined. There is a correlation between the temperature change curve and the power change curve, that is, temperature change affects power change, and power change can also affect temperature change. Therefore, it can be determined based on the temperature change curve and the power change curve. The characteristic value of the charging status of each branch is obtained. The size of the characteristic value is related to the probability of abnormality in the branch. The historical temperature change curve records the temperature change of the branch during operation in the past period of time. Analysis of the historical temperature change curve can analyze the probability of abnormality in each branch to a certain extent. Therefore, it is more accurate to determine the probability of abnormality in each branch based on the characteristic value and the historical temperature change curve. The probability of abnormality in all branches can reflect the overall probability level of the power consumption side, and then the appropriate number of branches that need to be disconnected from the power supply can be determined based on these probabilities. According to the determined probability and power change curve, a comprehensive analysis can be made of the target branches that are more suitable for disconnecting the power supply, that is, the target branches with a higher probability of potential abnormality and a higher power value level, that is, the branches that need to be disconnected first, and finally the power supply connections of these target branches are disconnected so that the power consumption side is kept at a safe level. BRIEF DESCRIPTION OF THE DRAWINGS

[0091] Figure 1 It is a flow chart of a method for controlling power load in a charging and swapping station according to an embodiment of the present application.

[0092] Figure 2 This is a structural diagram of a power load control system for a charging and swapping station according to an embodiment of the present application.

[0093] Figure 3 It is a structural diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0094] The present application is further described in detail below with reference to the accompanying drawings.

[0095] After reading this specification, those skilled in the art may make non-creative modifications to this embodiment as needed, but such modifications are protected by patent law as long as they fall within the scope of the claims of this application.

[0096] To make the purpose, technical solutions, and advantages of the embodiments of this application more clear, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0097] In this document, the term "and / or" simply describes a relationship between related objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, or B exists alone. Furthermore, the character " / " in this document, unless otherwise specified, generally indicates an "or" relationship between the related objects.

[0098] The embodiments of the present application are described in further detail below with reference to the accompanying drawings.

[0099] The embodiment of the present application provides a method for regulating the power load of a charging and swapping station, which is executed by an electronic device, which can be a server or a terminal device, wherein the server can be an independent physical server, a server cluster or a distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc., but is not limited to this. The terminal device and the server can be directly or indirectly connected through wired or wireless communication. The embodiment of the present application does not limit this. Figure 1 As shown, the method includes steps S101, S102, S103, S104 and S105, wherein:

[0100] S101, obtaining a temperature change curve, a power change curve, a total power of the power consumption side, and a plurality of historical temperature change curves of a charging device on each branch line of the power consumption side for the current charging.

[0101] In the embodiment of the present application, the electronic device is connected to the charging device on each branch via a wire, such as a charging pile, a charger, etc. A temperature sensor is installed at a key heating position in the charging device. The temperature sensor sends the collected temperature data to the charging device. The charging device generates a temperature change curve and sends it to the electronic device, so that the electronic device can obtain the temperature change curve. Similarly, a power sensor is provided in the charging device to send the collected real-time power value to the charging device. The charging device generates a power change curve and sends it to the electronic device, so that the electronic device can obtain the power change curve.

[0102] Alternatively, the charging device sends temperature and power data to a cloud server, which generates a temperature profile based on the temperature data and a power profile based on the power data. The electronic device is in communication with the cloud server and obtains the temperature and power profiles for each charging device on each branch from the cloud server. The cloud server stores the temperature profile of each charging device, allowing the electronic device to obtain multiple historical temperature profiles for the charging device.

[0103] S102 : If the total power on the power consumption side reaches a preset power threshold, a characteristic value representing the current charging state of each branch is determined based on the temperature change curve and the power change curve.

[0104] For the embodiment of the present application, the preset power threshold is used as the dividing point for whether the power on the power consumption side is too high. For example, the preset power threshold is 3000KW. The electronic device compares the total power on the power consumption side with 3000KW. If it reaches 3000KW, it means that the power on the power consumption side is too high and is about to exceed the maximum power that the charging and swapping station can withstand. The temperature change curve records the temperature changes of the charging device during the current charging process. Excessive temperature or continuous high temperature can easily cause abnormalities in the charging device or even potential fire hazards. The power change curve records the power changes of the charging device during the current charging process. Unstable power or continuous high power can also easily cause abnormalities in the charging device. Therefore, the electronic device combines the temperature change curve and the power change curve to comprehensively determine the characteristic value that characterizes the current charging state of each branch. According to the characteristic value, it is convenient to accurately determine the probability of the branch being abnormal, and it is also convenient to accurately determine the branch that needs to be powered off first.

[0105] S103: Determine the probability of abnormality occurring in each branch based on the characteristic value and multiple historical temperature change curves.

[0106] For the embodiment of the present application, the historical temperature change curve records the temperature changes of the charging device during its historical operation. The historical temperature change curve can also analyze the probability of an abnormality in a branch to a certain extent. The electronic device can more accurately determine the probability of an abnormality in each branch by combining the characteristic value and the historical temperature change curve.

[0107] S104: Determine the number of branches that need to be disconnected from power supply based on the probability of an abnormality occurring in each branch.

[0108] In the embodiment of the present application, the electronic device can reflect the overall abnormality probability level of the power consumption side based on the probability of abnormalities occurring in all branches. For example, the higher the overall abnormality probability level, the more branches that need to be disconnected to ensure more stable operation and less prone to abnormalities on the power consumption side. Therefore, the electronic device can determine an appropriate number of branches to disconnect based on the probability of each branch.

[0109] S105 , determining a target branch number based on the probability and the power variation curve, and controlling to disconnect the target branch.

[0110] Specifically, by comprehensively considering the probability of each branch and the power change curve, a more appropriate target branch for disconnecting power can be determined. After determining the target branch, the electronic equipment can send a control signal to the switch, solenoid valve, air switch, and PLC controller that control the on / off of the target branch to disconnect the target branch, thereby ensuring smoother and safer operation on the power consumption side. The characteristic value of the branch is determined based on the temperature change curve and the power change curve. The probability of an abnormality in each branch is determined based on the characteristic value and the historical temperature change curve. The appropriate number of branches can be determined based on the probability of all branches, and the more appropriate branches for priority disconnection can be determined based on the probability and power change curve.

[0111] In a possible implementation of the embodiment of the present application, in step S102, a characteristic value characterizing the current charging state of each branch is determined based on the temperature change curve and the power change curve, specifically including step S1021 (not shown in the figure), step S1022 (not shown in the figure), step S1023 (not shown in the figure), step S1024 (not shown in the figure), step S1025 (not shown in the figure), and step S1026 (not shown in the figure), wherein,

[0112] S1021 , determining the maximum temperature value, the temperature value at the current moment, and a first curve segment whose slope is less than a preset slope threshold from the temperature change curve, and determining an average temperature value of the first curve segment.

[0113] For the embodiment of the present application, the preset slope threshold serves as the dividing point for whether the temperature change tends to be stable. The electronic device determines the slope of each point in the temperature change curve and then determines the first curve segment whose slope is less than the preset slope threshold. The electronic device then averages the temperature data in the first curve segment to obtain the temperature average value, that is, the temperature average value is used to represent the temperature level after the temperature change tends to be stable.

[0114] S1022: Calculate the difference between the maximum temperature value and the average temperature value, and determine the power value at the current moment from the power change curve.

[0115] In the embodiment of the present application, the electronic device subtracts the average temperature from the maximum temperature value to obtain the difference. A larger difference indicates a lower temperature level after stabilization and a lower probability of an abnormality. The electronic device extracts the current power value from the power change curve at the current moment. A larger power value at the current moment indicates more heat generated by the charging device, higher current and voltage levels on the branch circuit, and a higher probability of an abnormality.

[0116] S1023: Determine a first product of the temperature value at the current moment and the power value at the current moment, and calculate a ratio of the first product to the difference to obtain a first sub-eigenvalue.

[0117] In the embodiment of the present application, the electronic device multiplies the current temperature value by the current power value to obtain a first product. A larger first product indicates a greater probability of an abnormality in the branch. The first product is then divided by the difference to obtain a ratio, which is the first sub-eigenvalue. A larger difference indicates a smaller probability of an abnormality in the branch. A larger first sub-eigenvalue indicates a greater probability of an abnormality in the branch. The first sub-eigenvalue is determined based on the current temperature, power, and the difference between the temperature after the temperature stabilizes and the maximum temperature value.

[0118] S1024: Extract a second curve segment from the power variation curve according to the starting time and the ending time of the first curve segment, and determine the power variance of the second curve segment.

[0119] In this embodiment, the second curve segment represents the power change after the charging device's temperature stabilizes. The electronic device then uses a variance calculation formula to calculate the variance of the power data in the second curve segment to obtain the power variance. A larger power variance indicates a more unstable power change after the temperature stabilizes, and a greater probability of an anomaly.

[0120] S1025 , determining a second product of the duration of the first curve segment, the temperature average value, and the power variance to obtain a second sub-eigenvalue.

[0121] For the embodiment of the present application, the longer the duration of the first curve segment, the longer the time after stabilization. The charging device enters the stage of continuous stable heating. The electronic device calculates the product of the duration of the first curve segment and the average temperature. The larger the average temperature, the more heat is emitted, and the greater the probability of abnormality in the branch. That is, the larger the product, the greater the probability of abnormality in the branch. The electronic device then multiplies the product by the power variance to obtain the second sub-eigenvalue. The larger the second sub-eigenvalue, the greater the probability of abnormality in the branch. The second sub-eigenvalue is obtained by considering both the heating situation and the degree of power stability.

[0122] S1026: Determine a eigenvalue based on the first sub-eigenvalue, the second sub-eigenvalue, and their corresponding weights.

[0123] In the embodiment of the present application, after the electronic device determines the first sub-eigenvalue and the second sub-eigenvalue, because the two sub-eigenvalues ​​have different importance, the electronic device determines the eigenvalue of each branch by combining the importance of the first sub-eigenvalue and the second sub-eigenvalue. The electronic device more accurately determines the eigenvalue of the branch by combining the first sub-eigenvalue and the second sub-eigenvalue.

[0124] In a possible implementation of the embodiment of the present application, determining the eigenvalue based on the first sub-eigenvalue, the second sub-eigenvalue, and their corresponding weights in step S1026 specifically includes step 1, step 2, and step 3, wherein:

[0125] Step 1: Determine the ratio of the second curve segment to the power change curve, and determine the ratio as the weight corresponding to the second sub-eigenvalue.

[0126] For the embodiment of the present application, the electronic device determines the operating time of the charging device from the current charge to the current moment, and then determines the time from the starting point of the second curve segment to the current moment, and divides the time of the second curve segment by the operating time of the current charge to obtain a proportion. The larger the proportion, the longer the operating time after the temperature stabilizes, and the more and more severe the corresponding heat generation, which further indicates that the second sub-eigenvalue characterizing the heat generation situation and the power stability is more important, so the proportion is determined as the weight of the second sub-eigenvalue.

[0127] Step 2: Subtract the proportion from 1 to get the weight corresponding to the first sub-eigenvalue.

[0128] In the embodiment of the present application, the electronic device can obtain the weight of the first sub-eigenvalue by subtracting the proportion in step 1 from 1. For example, if the proportion is 0.7, the weight of the first sub-eigenvalue is 0.3.

[0129] Step three: perform weighted calculation on the first sub-eigenvalue, the second sub-eigenvalue, and their corresponding weights to obtain an eigenvalue.

[0130] In the embodiment of the present application, after the electronic device determines the first and second sub-eigenvalues, it uses the corresponding weights to perform a weighted calculation to determine the eigenvalue of the branch. The electronic device determines appropriate weights based on the importance of the first and second sub-eigenvalues, performing the weighted calculation, thereby making the ultimately determined eigenvalue more accurate and consistent with the actual operation of the branch.

[0131] In a possible implementation of the embodiment of the present application, the multiple historical temperature change curves include a first historical temperature change curve when the multiple charging devices are operating normally and a second historical temperature change curve when the multiple charging devices are operating abnormally. In step S103, the probability of an abnormality occurring in each branch is determined based on the characteristic value and the multiple historical temperature change curves, specifically including step S1031 (not shown in the figure), step S1032 (not shown in the figure), step S1033 (not shown in the figure), step S1034 (not shown in the figure), step S1035 (not shown in the figure) and step S1036 (not shown in the figure), wherein,

[0132] S1031 , fitting multiple second historical temperature change curves to obtain a reference change curve.

[0133] In the embodiment of the present application, the first and second historical temperature change curves are screened by personnel and labeled as normal operation or abnormal operation. The electronic device can input multiple second historical temperature change curves into the Origin software plug-in for fitting to obtain a baseline change curve. The baseline change curve represents the overall change trend of each branch when all abnormal operation conditions have occurred in history.

[0134] S1032: Calculate first similarities between the reference change curve and each of the plurality of preset temperature anomaly curves.

[0135] In the embodiments of the present application, each preset temperature anomaly curve represents a temperature change when an abnormal operation occurs and an accident such as equipment damage or fire occurs. The electronic device can calculate a first similarity by calculating the Euclidean distance between the baseline change curve and the preset temperature anomaly curve, or by using methods such as dynamic time warping (DTW). A higher first similarity indicates a greater likelihood that the charging device experienced equipment damage or fire during its historical operation, and thus a greater likelihood that the charging device will experience equipment damage or fire in the future.

[0136] S1033: Calculate a second similarity between the temperature change curve and each first historical temperature change curve.

[0137] Similarly, the electronic device can calculate the second similarity between the temperature change curve and the first historical temperature change curve according to the method disclosed in step S1032. The higher the second similarity, the higher the possibility that the charging device is currently operating normally, and the lower the probability of an abnormality or other accident.

[0138] S1034: Calculate an average value of all first similarities to obtain a first average similarity value, and calculate an average value of all second similarities to obtain a second average similarity value.

[0139] For the embodiment of the present application, the electronic device calculates the average value of all first similarities, i.e., the first similarity average value, through the average value calculation formula. The larger the first similarity average value, the greater the possibility that the charging device will suffer equipment damage or fire or other accidents during historical abnormal operation, and thus the greater the possibility that an accident will occur in future operation. The electronic device calculates the average value of all second similarities, i.e., the second similarity average value, through the average value calculation formula. The larger the second similarity average value, the closer the temperature change of the charging device during the current operation is to the temperature change during normal operation in history, and thus the greater the possibility that it will still operate normally in the future.

[0140] S1035 : Determine a ratio of the first similarity average value to the second similarity average value to obtain a temperature characteristic value related to the temperature anomaly probability.

[0141] In the embodiment of the present application, the electronic device divides the first similarity average by the second similarity average to obtain a ratio, which is the temperature characteristic value representing the probability of branch temperature anomaly. A larger temperature characteristic value indicates a greater probability of an impending anomaly.

[0142] S1036: Calculate the product of the characteristic value and the temperature characteristic value to obtain an abnormality score, and determine the probability of an abnormality occurring in each branch based on the abnormality score.

[0143] In the embodiments of the present application, both the eigenvalue and the temperature eigenvalue are key factors in characterizing the probability of a branch abnormality. Therefore, the electronic device multiplies the eigenvalue by the temperature eigenvalue to obtain an abnormality score. The electronic device then multiplies the abnormality score by a specified parameter or coefficient to obtain the probability of an abnormality in each branch. Using an abnormality score that combines the eigenvalue and temperature eigenvalues ​​to more accurately determine the probability of an abnormality in each branch.

[0144] In a possible implementation of the embodiment of the present application, in step S104, the number of branches that need to be disconnected from the power supply is determined based on the probability of an abnormality occurring in each branch, specifically including step S1041 (not shown in the figure), step S1042 (not shown in the figure), and step S1043 (not shown in the figure), wherein:

[0145] S1041: Draw a histogram based on the probability of each branch and a preset probability interval.

[0146] S1042: Determine a target interval with the most branches from the histogram, and calculate the average probability value within the target interval.

[0147] S1043 : Determine the number of branches based on the probability average and the number of branches in the target interval.

[0148] For the embodiment of the present application, the preset probability interval can be 5%, 10%, or other percentages. The electronic device counts and sorts the number of branches in each interval of the histogram to obtain the target interval with the most branches. The electronic device then averages all the probabilities within the target interval to obtain a probability average. The largest number of branches within the target interval indicates that the probability of the majority of branches is within the interval. The larger the probability average within the interval, the greater the probability average of the electricity consumption side is near the probability average level. Therefore, the appropriate number of branches that need to be powered off can be determined based on the probability average and the number of branches within the target interval.

[0149] In a possible implementation of the embodiment of the present application, the number of branches is determined based on the probability average and the number of branches in the target interval in step S1043, specifically including step Sa (not shown in the figure) and step Sb (not shown in the figure), wherein:

[0150] Sa, a score is obtained by weighted calculation based on the probability average, the number of branches in the target interval and their corresponding coefficients.

[0151] Sb, determining a target preset score interval where the score is located from multiple preset score intervals, each preset score interval corresponds to a preset number of branches, and determining the preset number of branches in the target preset score interval as the branch number.

[0152] For the embodiment of the present application, the probability average value and the number of branches within the target interval are both key factors affecting the number of branches that need to be powered off, and the probability average value and the number of branches within the target interval have different degrees of influence on the number of branches. Therefore, the electronic device sets corresponding coefficients for the probability average value and the number of branches within the target interval, and the electronic device calls the corresponding coefficients for the probability average value and the number of branches within the target interval to perform weighted calculation to obtain a score. The electronic device then determines the target preset score interval where the score is located from multiple preset score intervals, and determines the preset number of branches in the target preset score interval as the number of branches. The preset number of branches in each preset score interval is set by the staff based on calculations or actual conditions.

[0153] In a possible implementation of the embodiment of the present application, step S105 determines the target branch number based on the probability and the power change curve, specifically including step S1051 (not shown in the figure), step S1052 (not shown in the figure), step S1053 (not shown in the figure), step S1054 (not shown in the figure) and step S1055 (not shown in the figure), wherein,

[0154] S1051: Sort all branch routes in descending order according to probability to obtain a first sorting result.

[0155] For the embodiment of the present application, assuming there are 50 branches, the electronic device can sort these 50 branches from high to low according to probability to obtain a first sorting result. The branch with a higher probability needs to be disconnected from the power supply first.

[0156] S1052: Determine the power value of each branch at the current moment from the power change curve of each branch, and sort all branches from large to small according to the power value at the current moment to obtain a second sorting result.

[0157] For the embodiment of the present application, the electronic device determines the current power value of each branch from the power change diagram at the current moment, and sorts the 50 branches from high to low according to the power value to obtain a second sorting result. The larger the current power value, the more necessary it is to disconnect the power supply first.

[0158] S1053: Determine the ranking of each branch in the first sorting result and the second sorting result, and sum the rankings in the first sorting result and the second sorting result to obtain a comprehensive ranking score for each branch.

[0159] In the embodiment of the present application, the electronic device determines the ranking of each branch from the two ranking results, and then sums the two rankings to obtain a comprehensive ranking score. A higher comprehensive ranking score indicates a higher probability of an abnormality and a higher power value at this time, and thus needs to be prioritized for power outage.

[0160] S1054: Sort all branches in descending order according to the comprehensive ranking scores to obtain a third ranking result.

[0161] In the embodiment of the present application, the branches that are closer to the end in the third sorting result need to be powered off first.

[0162] S1055: Determine the target number of branches in ascending order from the third sorting result.

[0163] For the embodiment of the present application, assuming that the number of determined branches is 10, the electronic device selects 10 branches from the third sorting result in ascending order from the beginning, and the first 10 branches are the target branches. The target branch determined by comprehensively considering the probability and the current power value is more suitable.

[0164] The above embodiment introduces a method for controlling the power load of a charging and swapping station from the perspective of a method flow. The following embodiment introduces a system 20 for controlling the power load of a charging and swapping station from the perspective of a virtual module or a virtual unit. For details, please refer to the following embodiment.

[0165] The embodiment of the present application provides a power load control system 20 for a charging and swapping station, such as Figure 2 As shown, a charging and swapping station power load control system 20 may specifically include:

[0166] The curve acquisition module 201 is used to obtain the temperature change curve, power change curve, total power of the power consumption side, and multiple historical temperature change curves of the charging device on each branch of the power consumption side;

[0167] A characteristic value determination module 202 is configured to determine a characteristic value representing the current charging state of each branch based on the temperature change curve and the power change curve when the total power on the power consumption side reaches a preset power threshold;

[0168] A probability determination module 203 is configured to determine the probability of an abnormality occurring in each branch based on the characteristic value and a plurality of historical temperature change curves;

[0169] The number determination module 204 is used to determine the number of branches that need to be disconnected based on the probability of an abnormality occurring in each branch;

[0170] The control module 205 is configured to determine a target number of branches based on the probability and the power variation curve, and control the disconnection of the target branches.

[0171] The embodiment of the present application discloses a power load control system 20 for a charging and swapping station, wherein a curve acquisition module 201 acquires a temperature change curve, a power change curve, a total power of the power side and a historical temperature change curve of a power-consuming side branch to facilitate subsequent accurate analysis of a branch that needs to be disconnected. If the total power of the power side reaches a preset power threshold, it means that the total power of the power side is too high and it is necessary to disconnect the power supply of some branches to ensure that the power of the power side remains at a safe level. The temperature change curve represents the temperature change of the charging equipment on the branch during operation. According to the temperature change curve, the probability of abnormal heating and potential fire of the charging equipment can be analyzed. The power change curve represents the power change during operation of the charging equipment. According to the power change and the power value at each moment, the current and voltage on the branch and the stability of the charging process can be determined. There is a correlation between the temperature change curve and the power change curve, that is, temperature change affects power change, and power change can also affect temperature change. Therefore, the characteristic value determination module 202 determines the characteristic value according to the temperature change curve. The power change curve can determine the characteristic value of the charging status of each branch. The size of the characteristic value is related to the probability of abnormality in the branch. The historical temperature change curve records the temperature change of the branch during operation in the past period of time. Analyzing the historical temperature change curve can analyze the probability of abnormality in each branch to a certain extent. Therefore, the probability determination module 203 determines the probability of abnormality in each branch more accurately based on the characteristic value and the historical temperature change curve. The probability of abnormality in all branches can reflect the overall probability level of the power consumption side, and then the quantity determination module 204 can determine the appropriate number of branches that need to be disconnected from the power supply based on these probabilities. The control module 205 can comprehensively analyze the target branches that are more suitable for disconnecting the power supply based on the determined probabilities and power change curves, that is, the target branches with a higher potential probability of abnormality and a higher power value level, that is, the branches that need to be disconnected first, and finally disconnect the power supply connections of these target branches so that the power consumption side is kept at a safe level.

[0172] In one possible implementation of the embodiment of the present application, the characteristic value determination module 202 is specifically configured to:

[0173] Determine the maximum temperature value, the current temperature value, and the first curve segment whose slope is less than a preset slope threshold from the temperature change curve, and determine the average temperature value of the first curve segment;

[0174] Calculate the difference between the maximum temperature and the average temperature, and determine the current power value from the power change curve;

[0175] Determine a first product of the temperature value at the current moment and the power value at the current moment, and calculate a ratio of the first product to the difference to obtain a first sub-eigenvalue;

[0176] Extracting a second curve segment from the power variation curve according to the starting time and the ending time of the first curve segment, and determining the power variance of the second curve segment;

[0177] Determine a second product of the duration of the first curve segment, the temperature average, and the power variance to obtain a second sub-eigenvalue;

[0178] An eigenvalue is determined based on the first sub-eigenvalue, the second sub-eigenvalue, and their corresponding weights.

[0179] In one possible implementation of the embodiment of the present application, the eigenvalue determining module 202 is specifically configured to:

[0180] Determine a ratio of the second curve segment to the power change curve, and determine the ratio as a weight corresponding to the second sub-eigenvalue;

[0181] Subtract the proportion from 1 to get the weight corresponding to the first sub-eigenvalue;

[0182] The first sub-eigenvalue, the second sub-eigenvalue, and their corresponding weights are weightedly calculated to obtain an eigenvalue.

[0183] In one possible implementation of the embodiment of the present application, the multiple historical temperature change curves include a first historical temperature change curve when the multiple charging devices operate normally and a second historical temperature change curve when the multiple charging devices operate abnormally. The probability determination module 203 is specifically configured to:

[0184] Fitting a plurality of second historical temperature change curves to obtain a reference change curve;

[0185] Calculating a first similarity between the reference change curve and each of the plurality of preset temperature anomaly curves;

[0186] calculating a second similarity between the temperature change curve and each first historical temperature change curve;

[0187] averaging all first similarities to obtain a first similarity average, and averaging all second similarities to obtain a second similarity average;

[0188] Determine a ratio of the first similarity average value to the second similarity average value to obtain a temperature characteristic value related to the temperature anomaly probability;

[0189] The product of the characteristic value and the temperature characteristic value is calculated to obtain an abnormality score, and the probability of an abnormality occurring in each branch is determined based on the abnormality score.

[0190] In one possible implementation of the embodiment of the present application, when the quantity determination module 204 determines the number of branches that need to be disconnected based on the probability of an abnormality occurring in each branch, it is specifically configured to:

[0191] Draw a histogram based on the probability of each branch and the preset probability interval;

[0192] Determine the target interval with the most branches from the histogram and calculate the average probability within the target interval;

[0193] The number of branches is determined based on the probability average and the number of branches within the target interval.

[0194] In one possible implementation of the embodiment of the present application, when the number determination module 204 determines the number of branches based on the probability average and the number of branches within the target interval, it is specifically configured to:

[0195] A score is obtained by weighted calculation based on the probability average, the number of branches in the target interval, and the corresponding coefficients;

[0196] A target preset score interval where the score is located is determined from multiple preset score intervals, each preset score interval corresponds to a preset number of branches, and the preset number of branches in the target preset score interval is determined as the number of branches.

[0197] In one possible implementation of the embodiment of the present application, when the control module 205 determines the target number of branches based on the probability and the power change curve, it is specifically configured to:

[0198] Sort all branches from largest to smallest according to probability to obtain a first sorting result;

[0199] Determine the power value of each branch at a current moment from the power change curve of each branch, and sort all branches from large to small according to the power value at the current moment to obtain a second sorting result;

[0200] Determine the ranking of each branch in the first sorting result and the second sorting result, and sum the rankings in the first sorting result and the second sorting result to obtain a comprehensive ranking score for each branch;

[0201] Sort all branches from largest to smallest according to the comprehensive ranking scores to obtain a third ranking result;

[0202] The target branches with the same number of branches are determined in ascending order from the third sorting results.

[0203] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the power load control system 20 of the charging and swapping station described above can refer to the corresponding process in the aforementioned method embodiment and will not be repeated here.

[0204] An electronic device is provided in an embodiment of the present application, such as Figure 3 As shown, Figure 3 The electronic device 30 shown includes a processor 301 and a memory 303. The processor 301 and the memory 303 are connected, for example, via a bus 302. Optionally, the electronic device 30 may further include a transceiver 304. It should be noted that in actual applications, the number of transceivers 304 is not limited to one, and the structure of the electronic device 30 does not constitute a limitation on the embodiments of the present application.

[0205] The processor 301 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It may implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. The processor 301 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, and the like.

[0206] The bus 302 may include a path for transmitting information between the above components. The bus 302 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 302 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 Only one thick line is used in the diagram, but it does not mean that there is only one bus or one type of bus.

[0207] The memory 303 may be a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, a RAM (Random Access Memory) or other type of dynamic storage device that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0208] The memory 303 is used to store application code for executing the solution of the present application, and the execution is controlled by the processor 301. The processor 301 is used to execute the application code stored in the memory 303 to implement the content shown in the above method embodiment.

[0209] The electronic devices include, but are not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), and in-vehicle terminals (e.g., in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. Servers and the like are also possible. Figure 3 The electronic device shown is merely an example and should not limit the functions and scope of use of the embodiments of the present application.

[0210] The embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer-readable storage medium is run on a computer, the computer can execute the corresponding content in the aforementioned method embodiment. Compared with the related art, in the embodiment of the present application, the temperature change curve, power change curve, total power of the power consumption side and historical temperature change curve of the power consumption side branch are obtained to facilitate the subsequent accurate analysis of the branch that needs to be disconnected. When the total power of the power consumption side reaches the preset power threshold, it means that the total power of the power consumption side is too high, and it is necessary to disconnect the power supply of some branches to ensure that the power consumption side remains at a safe level. The temperature change curve represents the temperature change of the charging device on the branch during operation. According to the temperature change curve, the probability of abnormal heating and potential fire of the charging device can be analyzed. The power change curve represents the power change during operation of the charging device. According to the power change and the power value at each moment, the current and voltage on the branch and the stability of the charging process can be determined. There is a correlation between the temperature change curve and the power change curve, that is, temperature change affects power change, and power change can also affect temperature change. Therefore, according to the temperature change curve and the power change curve, the power value at each moment can be determined. The temperature change curve can determine the characteristic value of the charging status of each branch. The size of the characteristic value is related to the probability of abnormality in the branch. The historical temperature change curve records the temperature change of the branch during operation in the past period of time. Analysis of the historical temperature change curve can analyze the probability of abnormality in each branch to a certain extent. Therefore, it is more accurate to determine the probability of abnormality in each branch based on the characteristic value and the historical temperature change curve. The probability of abnormality in all branches can reflect the overall probability level of the power consumption side, and then the appropriate number of branches that need to be disconnected from the power supply can be determined based on these probabilities. According to the determined probability and the power change curve, a comprehensive analysis can be made of the target branches that are more suitable for disconnecting the power supply, that is, the target branches with a higher probability of potential abnormality and a higher power value level, that is, the branches that need to be disconnected first, and finally the power supply connections of these target branches are disconnected so that the power consumption side is kept at a safe level.

[0211] It should be understood that although the steps in the flowcharts of the accompanying drawings are shown in sequence as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some of the steps in the flowcharts of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0212] The above description is only part of the implementation methods of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for controlling the power load of a charging and swapping station, characterized in that: include: Obtain the current charging temperature change curve, power change curve, total power of the power consumption side, and multiple historical temperature change curves of the charging equipment on each branch on the power consumption side; If the total power on the power consumption side reaches a preset power threshold, a characteristic value representing the current charging state of each branch is determined based on the temperature change curve and the power change curve; Determining the probability of an abnormality occurring in each branch based on the characteristic value and a plurality of historical temperature change curves; Determine the number of branches that need to be disconnected based on the probability of an abnormality occurring in each branch; A target branch of the number of branches is determined based on the probability and the power variation curve, and the target branch is disconnected through control.

2. A method for controlling power load of a charging and swapping station according to claim 1, characterized in that: The determining of a characteristic value representing a current charging state of each branch based on the temperature change curve and the power change curve includes: Determine from the temperature change curve the maximum temperature value, the temperature value at the current moment, and a first curve segment whose slope is less than a preset slope threshold, and determine the average temperature value of the first curve segment; Calculating the difference between the maximum temperature value and the average temperature value, and determining the power value at the current moment from the power change curve; Determine a first product of the temperature value at the current moment and the power value at the current moment, and calculate a ratio of the first product to the difference to obtain a first sub-eigenvalue; Extracting a second curve segment from the power variation curve according to the starting time and the ending time of the first curve segment, and determining the power variance of the second curve segment; Determine a second product of the duration of the first curve segment, the temperature average, and the power variance to obtain a second sub-eigenvalue; The eigenvalue is determined based on the first sub-eigenvalue, the second sub-eigenvalue, and their corresponding weights.

3. A method for controlling power load of a charging and swapping station according to claim 2, characterized in that: The determining the eigenvalue based on the first sub-eigenvalue, the second sub-eigenvalue, and their corresponding weights includes: determining a ratio of the second curve segment to the power change curve, and determining the ratio as a weight corresponding to the second sub-eigenvalue; Subtract the proportion from 1 to obtain the weight corresponding to the first sub-eigenvalue; The eigenvalue is obtained by performing weighted calculation on the first sub-eigenvalue, the second sub-eigenvalue, and their corresponding weights.

4. The method for controlling power load of a charging and swapping station according to claim 1, characterized in that: The multiple historical temperature change curves include multiple first historical temperature change curves when the charging device operates normally and multiple second historical temperature change curves when the charging device operates abnormally. Determining the probability of an abnormality occurring in each branch based on the characteristic value and the multiple historical temperature change curves includes: Fitting the plurality of second historical temperature change curves to obtain a reference change curve; Calculating a first similarity between the reference change curve and each of a plurality of preset temperature anomaly curves; calculating a second similarity between the temperature change curve and each first historical temperature change curve; averaging all first similarities to obtain a first similarity average, and averaging all second similarities to obtain a second similarity average; Determine a ratio of the first similarity average value to the second similarity average value to obtain a temperature characteristic value related to a temperature anomaly probability; The product of the characteristic value and the temperature characteristic value is calculated to obtain an abnormality score, and the probability of abnormality occurring in each branch is determined based on the abnormality score.

5. The method for controlling power load of a charging and swapping station according to claim 1, characterized in that: The determining the number of branches that need to be disconnected based on the probability of an abnormality occurring in each branch includes: Draw a histogram based on the probability of each branch and the preset probability interval; Determine a target interval with the most branches from the histogram, and calculate the average probability value within the target interval; The number of branches is determined based on the probability average and the number of branches in a target interval.

6. A method for controlling power load of a charging and swapping station according to claim 5, characterized in that: The determining the number of branches based on the probability average and the number of branches in the target interval includes: A score is obtained by performing weighted calculation based on the probability average, the number of branches in the target interval, and the corresponding coefficients; A target preset score interval where the score is located is determined from multiple preset score intervals, each preset score interval corresponds to a preset number of branches, and the preset number of branches in the target preset score interval is determined as the number of branches.

7. The method for controlling power load of a charging and swapping station according to claim 1, characterized in that: The determining the target branch of the number of branches based on the probability and the power change curve includes: Sort all branches from largest to smallest according to the probability to obtain a first sorting result; Determine the power value of each branch at a current moment from the power change curve of each branch, and sort all branches from large to small according to the power value at the current moment to obtain a second sorting result; Determine the ranking of each branch in the first sorting result and the second sorting result, and sum the rankings in the first sorting result and the second sorting result to obtain a comprehensive ranking score for each branch; Sort all branches from largest to smallest according to the comprehensive ranking scores to obtain a third ranking result; The target branches of the number of branches are determined in ascending order from the third sorting results.

8. A power load control system for a charging and swapping station, characterized in that: include: A curve acquisition module is used to obtain the temperature change curve, power change curve, total power of the power consumption side, and multiple historical temperature change curves of the charging equipment on each branch on the power consumption side; a characteristic value determination module, configured to determine a characteristic value representing the current charging state of each branch based on the temperature change curve and the power change curve when the total power on the power consumption side reaches a preset power threshold; A probability determination module, configured to determine the probability of an abnormality occurring in each branch based on the characteristic value and a plurality of historical temperature change curves; A quantity determination module is used to determine the number of branches that need to be disconnected based on the probability of an abnormality occurring in each branch; A control module is used to determine a target branch of the number of branches based on the probability and the power change curve, and control the disconnection of the target branch.

9. An electronic device, characterized in that: It includes: at least one processor; Memory; At least one application, wherein the at least one application is stored in the memory and configured to be executed by the at least one processor, and the at least one application is used to execute a method for controlling power load in a charging and swapping station according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed in a computer, the computer is caused to execute the method for controlling the power load of a charging and swapping station according to any one of claims 1 to 7.

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