A method and system for predicting overload of intelligent AC charging pile

Abstract

The present invention discloses an overload prediction method and system for an intelligent AC charging pile, which specifically relates to the field of intelligent electricity consumption, including S1: dividing time zones, S2: collecting charging pile power data, S3: preprocessing charging pile power data, S4: analyzing charging pile power data, S5: comprehensive charging pile power data evaluation, S6: judging the stability of the charging pile, S7: overload prediction, and S8: human-computer interaction. The present invention selects a first power text feature and preprocesses the first power text to obtain a second power text, and constructs an intelligent AC charging pile overload prediction model through an overload prediction step, providing an overload prediction value for the AC charging pile, and further, based on the overload prediction, obtains an overload risk threshold, performs an overload risk judgment on the AC charging pile, and promptly performs power-off processing and alarm on the charging pile with overload risk, thereby providing an important guarantee for taking measures in time to avoid the occurrence of dangerous accidents.

Description

Technical Field

[0001] The present invention relates to the field of intelligent power consumption technology, and more specifically, to an overload prediction method and system for an intelligent AC charging pile. Background Art

[0002] With the enhancement of environmental awareness and the transformation of energy structure, electric vehicles, as representatives of new energy vehicles, are gradually gaining favor among consumers. Therefore, AC charging piles have begun to be widely built and popularized, providing electric vehicle users with a more convenient and reliable charging method. As an important part of electric vehicle charging infrastructure, the construction and popularization of AC charging piles will help promote the optimization of energy structure.

[0003] Traditional AC charging pile overload prediction methods and systems mainly rely on real-time monitoring and analysis of charging pile operation data, including data collection, data analysis and system early warning. Data collection monitors key parameters such as current, voltage, and power in real time through sensors installed on the charging pile; data analysis processes and analyzes real-time data to identify abnormal values ​​or trends; system early warning judges the data by receiving the data analyzed in data analysis. When the real-time monitored data exceeds the early warning threshold, the system automatically triggers the early warning mechanism. After receiving the early warning signal, emergency response measures are taken immediately.

[0004] However, there are still some shortcomings in its actual use. For example, due to the real-time and rapid charging of charging piles, the traditional AC charging pile overload prediction method can no longer meet the real-time nature of data collection. Therefore, it is necessary to introduce advanced technical means to improve the intelligence and safety of power grid management, such as through the Internet of Things technology, sensors, smart devices, etc., to collect various data in the operation of charging piles in real time, including key information such as power, voltage, current, etc., so as to analyze the current, power surges and other signs that may indicate overload, and then build a more comprehensive and accurate safe charging environment. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides an overload prediction method and system for an intelligent AC charging pile, and solves the problems raised in the above-mentioned background technology through the following scheme.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] S1: Divide time zone: The user confirms the start time of charging on the user information terminal as the start time of using the smart AC charging pile, divides the charging time into various time feature texts by equal time division, and marks each time feature text as 1, 2, ..., i, ..., n in sequence;

[0008] S2: Collect charging pile power data: select a first power text feature based on the time feature text;

[0009] S3: preprocessing charging pile power data: preprocessing the first power text to obtain a second power text;

[0010] S4: Analyze the charging pile power data: obtain any text output value based on the second power text analysis;

[0011] S5: Comprehensive charging pile power data evaluation: obtain a comprehensive power text evaluation value based on multiple text output values ​​in S4;

[0012] S6: Determine the stability of the charging pile: Determine the charging pile based on the comprehensive power text evaluation value and issue an early warning for the judgment result;

[0013] S7: Overload prediction: Based on the judgment result of S6, overload prediction is performed on the AC charging pile without power and unstable state;

[0014] S8: Human-computer interaction: Information output based on overload prediction and user information terminal.

[0015] Preferably, the user information terminal is bound to a mobile phone or any output-capable electronic device based on user information, and the user information includes the type of charging vehicle, the amount of electricity charged by the user each time, and the time when the user starts charging and ends charging.

[0016] Preferably, the step of collecting charging pile power data includes a current data collection unit, a voltage data collection unit, a first power text integration unit and a first power text output unit. The current data collection unit is used to collect the output current, current harmonic content and phase current of the charging pile, which are respectively denoted as Io, Ic and Ie; the voltage data collection unit is used to collect the output voltage, voltage harmonic content and phase voltage of the charging pile, which are respectively denoted as Uo, Uc and Ue; the first power text integration unit obtains the first power text feature by integrating the data collected by different units; the first power text output unit transmits the first power text feature integrated by the first power text integration unit to the system operation database.

[0017] Preferably, the second power text is preprocessed based on the first power text, and includes a first power text receiving unit, a current data preprocessing unit, a voltage data preprocessing unit, a second power text integration unit and a second power text output unit, wherein the first power text receiving unit is used to receive the collected first power text; the current data preprocessing unit classifies and summarizes the collected current data to calculate the average output current, the average current harmonic content and the current imbalance; the voltage data preprocessing unit classifies and summarizes the collected voltage data to calculate the average output voltage, the average voltage harmonic content and the voltage imbalance; the second power text integration unit is used to obtain the second power text by integrating the data preprocessed by the current data preprocessing unit and the voltage data preprocessing unit through normalization and standardization; the second power text output unit transmits the second power text integrated by the second power text integration unit to the system operation database.

[0018] Preferably, the arbitrary text output is subjected to secondary processing through the preprocessed power data to obtain the current stability index and the voltage stability index respectively and transmit them to the system operation database, specifically including a preprocessed data receiving unit, a current stability index calculation unit, a voltage stability index calculation unit and a current data output unit. The specific data analysis process is as follows:

[0019] Pre-processing data receiving unit: used to receive power data stored in the system operation database;

[0020] Current stability index calculation unit: calculates the current stability index Y based on the average output current, average current harmonic content and current imbalance. The specific analysis formula is:

[0021] ,

[0022] Among them I 1 Represents the average output current, I 1 ´ represents the preset output current of the AC charging pile, I 2 Indicates the average current harmonic content, I 3 Indicates the current imbalance;

[0023] Voltage stability index calculation unit: The voltage stability index is calculated based on the average output voltage, average voltage harmonic content and voltage imbalance. The specific analysis formula is:

[0024] ,

[0025] Among them U 1 Indicates the average output voltage, U 1 ´ represents the preset output voltage of the AC charging pile, U 2 Indicates the average voltage harmonic content, U3 Indicates voltage imbalance;

[0026] Data output unit: sends the analyzed data to the system operation database, where the current stability index and voltage stability index are any text output values.

[0027] Preferably, the comprehensive charging pile power data evaluation calculates the comprehensive power text evaluation value based on the current stability index and the voltage stability index, and the specific analysis formula of the comprehensive power text evaluation value is: η=λ 1 ×Y+λ 2 ×N, where Y represents the current stability index, N represents the voltage stability index, and λ 1 and λ 2 Represent the factors affecting current stability and voltage stability respectively.

[0028] Preferably, the determination of the stability of the charging pile is based on the comprehensive power text evaluation value to set the preset value of the comprehensive power text evaluation value, and the preset value of the comprehensive power text output value is marked as n D , when η D <η, it means that the comprehensive power text output value is greater than the preset value of the comprehensive power text output value, indicating that the AC charging pile is not in an unstable power state at this time, and the judgment result is transmitted to the preset analysis database; when η D >η, it means that the comprehensive power text output value is less than the preset value of the comprehensive power text output value, indicating that the power of the AC charging pile is unstable at this time. The AC charging pile will automatically cut off the power and issue an alarm to ensure that the AC charging pile operates within a safe range.

[0029] Preferably, the overload prediction obtains an intelligent AC charging pile overload prediction model under a stable power state of the AC charging pile, and constructs an intelligent AC charging pile overload prediction model, which specifically includes:

[0030] Obtain analytical datasets for overload prediction;

[0031] Based on the analysis data set, obtain the knowledge graph of overload prediction under the power stable state;

[0032] Based on the overload prediction knowledge graph, an intelligent AC charging pile overload prediction model is constructed.

[0033] Furthermore, the analysis data set for overload prediction includes but is not limited to a historical charging analysis data set and a charging pile environment analysis data set, which collects historical charging data and charging pile environment information. The historical charging data includes charging time, charging power and charging power, and the charging pile environment data includes charging pile surface temperature, insulation temperature and introduction terminal temperature. According to different analysis data sets, different overload prediction knowledge graphs are constructed, and then according to different overload prediction knowledge graphs, an intelligent AC charging pile overload prediction model corresponding to each analysis data set is constructed to obtain an overload prediction value, thereby providing a more accurate judgment for the overload prediction of the AC charging pile.

[0034] Preferably, the human-computer interaction establishes an overload risk assessment model based on overload prediction, evaluates the overload risk of the AC charging pile under different time feature texts, and obtains the overload risk threshold based on the overload risk assessment model. If the overload prediction value is less than the overload risk threshold, it means that the AC charging pile has no overload risk at this time, and the power data processing and analysis of the charging process continues. If the overload prediction value is greater than or equal to the risk threshold, it means that the AC charging pile has an overload risk at this time, and the power supply is immediately cut off, and an audible and visual alarm signal is issued.

[0035] The present invention also provides an overload prediction system for an intelligent AC charging pile, which is applied to the above-mentioned overload prediction method for an intelligent AC charging pile, comprising:

[0036] Time division module: the charging time is divided into various time feature texts by equal time division, based on the start time when the user confirms the start of charging on the user information terminal as the start time of using the smart AC charging pile, and each time feature text is marked as 1, 2, ..., i, ..., n in sequence;

[0037] Power data acquisition module: selecting the first power text feature based on the time feature text;

[0038] Power data preprocessing module: preprocessing the first power text to obtain the second power text;

[0039] Power data analysis module: obtains any text output value based on the second power text analysis;

[0040] Power data comprehensive evaluation module: obtains comprehensive power text evaluation value based on multiple text output values ​​in S4;

[0041] Charging pile stability judgment module: judges the charging pile based on the comprehensive power text evaluation value and issues an early warning for the judgment result;

[0042] Overload prediction module: based on the judgment result of S6, overload prediction is performed for the unstable state of AC charging pile without power;

[0043] Human-computer interaction module: outputs information based on overload prediction and user information terminal.

[0044] Technical effects and advantages of the present invention:

[0045] The present invention divides the use time of the AC charging pile by dividing the time area step, which provides more refined monitoring for subsequent power data evaluation and overload prediction; selects the first power text feature, and pre-processes the first power text to obtain the second power text, simplifies the complex and changeable power data, reduces the operating load, and improves the system operation efficiency; through the charging pile power data analysis step, the pre-processed second power text is analyzed to obtain any text output value, which is of great significance for the comprehensive evaluation of the stability of the AC charging pile; through the comprehensive charging pile power data evaluation step, the comprehensive power text evaluation value is obtained, which can reflect the overall operating state of the AC charging pile; the charging pile is judged for stability, whether the power of the AC charging pile is stable, and the time feature text in a stable state is further analyzed; through the overload prediction step, an intelligent AC charging pile overload prediction model is constructed to provide an overload prediction value for the AC charging pile, and further obtain an overload risk threshold based on the overload prediction, the overload risk of the AC charging pile is judged, and the charging pile with overload risk is timely powered off and alarmed, which provides an important guarantee for taking measures in time to avoid the occurrence of dangerous accidents. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 It is a schematic diagram of the overall structure of the present invention.

[0047] Figure 2 It is a flow chart of the system operation of the present invention.

[0048] Figure 3 The figure is a schematic diagram of the structure of an electronic device of the present invention. DETAILED DESCRIPTION

[0049] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0050] As attached Figure 1 An overload prediction method for an intelligent AC charging pile is shown, including S1 to S8.

[0051] S1: Divide time zone: The user confirms the start time of charging on the user information terminal as the start time of using the smart AC charging pile, divides the charging time into various time feature texts by equal time division, and marks each time feature text as 1, 2, ..., i, ..., n in sequence.

[0052] In this embodiment, it should be specifically explained that the user information terminal is bound to a mobile phone or any output-capable electronic device based on user information, and the user information includes the charging vehicle model, the amount of power charged by the user each time, and the time when the user starts and ends charging.

[0053] S2: Collect charging pile power data: select the first power text feature based on the time feature text.

[0054] In this embodiment, it should be specifically explained that the step of collecting charging pile power data includes a current data collection unit, a voltage data collection unit, a first power text integration unit and a first power text output unit. The current data collection unit is used to collect the output current, current harmonic content and phase current of the charging pile, which are respectively denoted as Io, Ic and Ie; the voltage data collection unit is used to collect the output voltage, voltage harmonic content and phase voltage of the charging pile, which are respectively denoted as Uo, Uc and Ue; the first power text integration unit integrates the data collected by different units to obtain the first power text feature; the first power text output unit transmits the first power text feature integrated by the first power text integration unit to the system operation database.

[0055] Furthermore, by embedding high-precision sensors in the AC charging pile, the output current and output voltage of the charging pile are monitored in real time. The voltage harmonic content and current harmonic content are obtained by sampling and digitizing the current signal through fast Fourier transform to obtain the frequency and amplitude of each harmonic, and the percentage of the fundamental amplitude is calculated to obtain the harmonic content; the phase voltage and phase current are the current and voltage flowing through each phase load, and are collected by sensors installed in each phase of the motor winding.

[0056] S3: Preprocessing charging pile power data: preprocessing the first power text to obtain a second power text.

[0057] In this embodiment, it should be specifically explained that the second power text is preprocessed based on the first power text, including a first power text receiving unit, a current data preprocessing unit, a voltage data preprocessing unit, a second power text integration unit and a second power text output unit. The first power text receiving unit is used to receive the collected first power text; the current data preprocessing unit classifies and summarizes the collected current data to calculate the average output current, the average current harmonic content and the current imbalance. The specific calculation formula of the average output current is: , where Io iThe specific calculation formula for the output current and average current harmonic content of the i-th time characteristic text is: , where Ic i The specific calculation formula for the current harmonic content of the i-th time characteristic text and the current unbalance degree is: , where Ie max Indicates the maximum value of the three-phase current, Ie min Indicates the minimum value of the three-phase current, Ie i Indicates the phase current of the i-th time feature text; the voltage data preprocessing unit classifies and summarizes the collected voltage data to calculate the average output voltage, average voltage harmonic content and voltage imbalance. The specific calculation formula for the average output voltage is: , where Uo i The specific calculation formula for the output voltage and average current harmonic content of the i-th time characteristic text is: , where Uc i The specific calculation formula for the current harmonic content of the i-th time characteristic text and the current unbalance degree is: , where Ue max Indicates the maximum value of the three-phase current, Ue min Indicates the minimum value of the three-phase current, Ue i The phase current representing the i-th time characteristic text; the second power text integration unit is used to obtain the second power text by integrating the data preprocessed by the current data preprocessing unit and the voltage data preprocessing unit; the second power text output unit transmits the second power text integrated by the second power text integration unit to the system operation database.

[0058] S4: Analyze charging pile power data: obtain any text output value based on the second power text analysis.

[0059] In this embodiment, it should be specifically explained that any one text output is secondary processed through the pre-processed power data to obtain the current stability index and the voltage stability index respectively and transmit them to the system operation database, which specifically includes a pre-processed data receiving unit, a current stability index calculation unit, a voltage stability index calculation unit and a current data output unit. The specific data analysis process is as follows:

[0060] Pre-processing data receiving unit: used to receive power data stored in the system operation database;

[0061] Current stability index calculation unit: calculates the current stability index Y based on the average output current, average current harmonic content and current imbalance. The specific analysis formula is:

[0062] ,

[0063] Among them I 1 Represents the average output current, I 1 ´ represents the preset output current of the AC charging pile, I 2 Indicates the average current harmonic content, I 3 Indicates the current imbalance;

[0064] Voltage stability index calculation unit: The voltage stability index is calculated based on the average output voltage, average voltage harmonic content and voltage imbalance. The specific analysis formula is:

[0065] ,

[0066] Among them U 1 Indicates the average output voltage, U 1 ´ represents the preset output voltage of the AC charging pile, U 2 Indicates the average voltage harmonic content, U 3 Indicates voltage imbalance;

[0067] Data output unit: sends the analyzed data to the system analysis database, where the current stability index and voltage stability index are any text output values.

[0068] S5: Comprehensive charging pile power data evaluation: Obtain a comprehensive power text evaluation value based on multiple text output values ​​in S4.

[0069] In this embodiment, it should be specifically explained that the comprehensive charging pile power data evaluation is based on the current stability index and the voltage stability index to calculate the comprehensive power text evaluation value. The specific analysis formula of the comprehensive power text evaluation value is: η=λ 1 ×Y+λ 2 ×N, where Y represents the current stability index, N represents the voltage stability index, and λ 1 and λ 2 They respectively represent the factors that affect current stability and voltage stability, such as changes in current and voltage caused by increases in external temperature.

[0070] S6: Determine the stability of the charging pile: Determine the charging pile based on the comprehensive power text evaluation value and issue an early warning for the judgment result.

[0071] In this embodiment, it should be specifically explained that the preset value of the comprehensive power text evaluation value is set based on the comprehensive power text evaluation value, and the preset value of the comprehensive power text output value is marked as n. D , when η D <η, it means that the comprehensive power text output value is greater than the preset value of the comprehensive power text output value, indicating that the AC charging pile is not in an unstable power state at this time, and the judgment result is transmitted to the preset analysis database; when η D>η, it means that the comprehensive power text output value is less than the preset value of the comprehensive power text output value, indicating that the power of the AC charging pile is unstable at this time. The AC charging pile will automatically cut off the power, transmit it to the system operation database and issue an alarm to ensure that the AC charging pile works under stable power conditions.

[0072] S7: Overload prediction: Based on the judgment result of S6, an overload prediction is performed on the power stability state of the AC charging pile.

[0073] In this embodiment, it should be specifically explained that the overload prediction obtains the intelligent AC charging pile overload prediction model under the AC charging pile power stable state, and constructs the intelligent AC charging pile overload prediction model, which specifically includes:

[0074] Obtain analytical datasets for overload prediction;

[0075] Based on the analysis data set, obtain the knowledge graph of overload prediction under the power stable state;

[0076] Based on the overload prediction knowledge graph, an intelligent AC charging pile overload prediction model is constructed.

[0077] Furthermore, the analysis data set for overload prediction includes but is not limited to a historical charging analysis data set and a charging pile environment analysis data set, which collects historical charging data and charging pile environment information. The historical charging data includes charging time, charging power and charging power, and the charging pile environment data includes charging pile surface temperature, insulation temperature and introduction terminal temperature. According to different analysis data sets, different overload prediction knowledge graphs are constructed, and then according to different overload prediction knowledge graphs, an intelligent AC charging pile overload prediction model corresponding to each analysis data set is constructed to obtain an overload prediction value, thereby providing a more accurate judgment for the overload prediction of the AC charging pile.

[0078] S8: Human-computer interaction: Information output based on overload prediction and user information terminal.

[0079] In this embodiment, it is necessary to specifically explain that an overload risk assessment model is established based on overload prediction, the overload risk of the AC charging pile under different time feature texts is evaluated, and the overload risk threshold is obtained based on the overload risk assessment model. If the overload prediction value is less than the overload risk threshold, it means that there is no overload risk for the AC charging pile at this time, and the power data processing and analysis of the charging process continues. If the overload prediction value is greater than or equal to the risk threshold, it means that there is an overload risk for the AC charging pile at this time, the power supply is immediately cut off, and an audible and visual alarm signal is issued to prevent equipment damage and fire and other safety accidents. The fault code or error prompt information is displayed on the display screen of the charging pile to help users quickly locate the cause of the problem.

[0080] The system operation database includes all data texts of an overload prediction method and system of an intelligent AC charging pile, and collects information texts outputted from each step in real time.

[0081] The present invention divides the use time of the AC charging pile by dividing the time area step, which provides more refined monitoring for subsequent power data evaluation and overload prediction; selects the first power text feature, and pre-processes the first power text to obtain the second power text, simplifies the complex and changeable power data, reduces the operating load, and improves the system operation efficiency; through the charging pile power data analysis step, the pre-processed second power text is analyzed to obtain any text output value, which is of great significance for the comprehensive evaluation of the stability of the AC charging pile; through the comprehensive charging pile power data evaluation step, the comprehensive power text evaluation value is obtained, which can reflect the overall operating state of the AC charging pile; the charging pile is judged for stability, whether the power of the AC charging pile is stable, and the time feature text in a stable state is further analyzed; through the overload prediction step, an intelligent AC charging pile overload prediction model is constructed to provide an overload prediction value for the AC charging pile, and further obtain an overload risk threshold based on the overload prediction, the overload risk of the AC charging pile is judged, and the charging pile with overload risk is timely powered off and alarmed, which provides an important guarantee for taking measures in time to avoid the occurrence of dangerous accidents.

[0082] As attached Figure 2 The overload prediction system of an intelligent AC charging pile shown in the embodiment further includes:

[0083] Time division module: the charging time is divided into various time feature texts by equal time division, based on the start time when the user confirms the start of charging on the user information terminal as the start time of using the smart AC charging pile, and each time feature text is marked as 1, 2, ..., i, ..., n in sequence;

[0084] Power data acquisition module: selecting the first power text feature based on the time feature text;

[0085] Power data preprocessing module: preprocessing the first power text to obtain the second power text;

[0086] Power data analysis module: obtains any text output value based on the second power text analysis;

[0087] Power data comprehensive evaluation module: obtains comprehensive power text evaluation value based on multiple text output values ​​in S4;

[0088] Charging pile stability judgment module: judges the charging pile based on the comprehensive power text evaluation value and issues an early warning for the judgment result;

[0089] Overload prediction module: based on the judgment result of S6, overload prediction is performed for the unstable state of AC charging pile without power;

[0090] Human-computer interaction module: outputs information based on overload prediction and user information terminal.

[0091] Secondly: In the drawings of the embodiments disclosed in the present invention, only the structures related to the embodiments disclosed in the present invention are involved, and other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of the present invention can be combined with each other;

[0092] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for predicting overload of an intelligent AC charging pile, characterized in that: include: S1: Divide time zone: The user confirms the start time of charging on the user information terminal as the start time of using the smart AC charging pile, divides the charging time into various time feature texts by equal time division, and marks each time feature text as 1, 2, ..., i, ..., n in sequence; S2: Collect charging pile power data: select a first power text feature based on the time feature text; S3: preprocessing charging pile power data: preprocessing the first power text to obtain a second power text; S4: Analyze the charging pile power data: obtain any text output value based on the second power text analysis; The arbitrary text output is subjected to secondary processing through the pre-processed power data to obtain the current stability index and the voltage stability index respectively and transmit them to the system operation database, which specifically includes a pre-processed data receiving unit, a current stability index calculation unit, a voltage stability index calculation unit and a current data output unit. The specific data analysis process is as follows: Pre-processed data receiving unit: used to receive power data stored in the system operation database; Current stability index calculation unit: calculates the current stability index Y based on the average output current, average current harmonic content and current imbalance. The specific analysis formula is: Where I1 represents the average output current, I1′ represents the preset output current of the AC charging pile, I2 represents the average current harmonic content, and I3 represents the current imbalance; Voltage stability index calculation unit: The voltage stability index N is calculated based on the average output voltage, the average voltage harmonic content and the voltage imbalance. The specific analysis formula is: Among them, U1 represents the average output voltage, U1′ represents the preset output voltage of the AC charging pile, U2 represents the average voltage harmonic content, and U3 represents the voltage imbalance; Data output unit: sends the analyzed data to the system analysis database, where the current stability index and voltage stability index are any text output values; S5: Comprehensive charging pile power data evaluation: obtain a comprehensive power text evaluation value based on multiple text output values ​​in S4; S6: Determine the stability of the charging pile: Determine the charging pile based on the comprehensive power text evaluation value and issue an early warning for the judgment result; S7: Overload prediction: Based on the judgment result of S6, overload prediction is performed on the AC charging pile without power and unstable state; S8: Human-computer interaction: Information output based on overload prediction and user information terminal.

2. The method for predicting overload of an intelligent AC charging pile according to claim 1, characterized in that: The user information terminal is bound to a mobile phone or any electronic device capable of outputting information based on the user information, wherein the user information includes the type of charging vehicle, the amount of electricity charged by the user each time, and the time when the user starts charging and ends charging.

3. The method for predicting overload of an intelligent AC charging pile according to claim 1, characterized in that: The step of collecting charging pile power data includes a current data collection unit, a voltage data collection unit, a first power text integration unit and a first power text output unit. The current data collection unit is used to collect the output current, current harmonic content and phase current of the charging pile, which are respectively recorded as Io, Ic and Ie; the voltage data collection unit is used to collect the output voltage, voltage harmonic content and phase voltage of the charging pile, which are respectively recorded as Uo, Uc and Ue; the first power text integration unit integrates the data collected by different units to obtain the first power text feature; The first power text output unit transmits the first power text feature integrated by the first power text integration unit to the system operation database.

4. The method for predicting overload of an intelligent AC charging pile according to claim 1, characterized in that: The second power text is preprocessed based on the first power text, including a first power text receiving unit, a current data preprocessing unit, a voltage data preprocessing unit, a second power text integration unit and a second power text output unit, and the first power text receiving unit is used to receive the collected first power text; The current data preprocessing unit classifies and summarizes the collected current data to calculate the average output current I1, the average current harmonic content I2 and the current imbalance I3; the voltage data preprocessing unit classifies and summarizes the collected voltage data to calculate the average output voltage U1, the average voltage harmonic content U2 and the voltage imbalance U3; The second power text integration unit is used to obtain a second power text by integrating the data preprocessed by the current data preprocessing unit and the voltage data preprocessing unit, and performing normalization and standardization processing; The second power text output unit transmits the second power text integrated by the second power text integration unit to the system operation database.

5. The method for predicting overload of an intelligent AC charging pile according to claim 1, characterized in that: The comprehensive charging pile power data evaluation calculates the comprehensive power text evaluation value based on the current stability index and the voltage stability index. The specific analysis formula of the comprehensive power text evaluation value is: η=λ1×Y+λ2×N, where Y represents the current stability index, N represents the voltage stability index, and λ1 and λ2 represent factors affecting current stability and voltage stability, respectively.

6. The method for predicting overload of an intelligent AC charging pile according to claim 5, characterized in that: The method of judging the stability of the charging pile sets a preset value of the comprehensive power text evaluation value based on the comprehensive power text evaluation value, and marks the preset value of the comprehensive power text output value as n. D , when η D <η, it means that the comprehensive power text output value is greater than the preset value of the comprehensive power text output value, indicating that the AC charging pile is not in an unstable power state at this time, and the judgment result is transmitted to the preset analysis database; when η D >η, it means that the comprehensive power text output value is less than the preset value of the comprehensive power text output value, indicating that the power of the AC charging pile is unstable at this time. The AC charging pile will automatically cut off the power and issue an alarm to ensure that the AC charging pile operates within a safe range.

7. The method for predicting overload of an intelligent AC charging pile according to claim 1, characterized in that: The overload prediction obtains the intelligent AC charging pile overload prediction model under the AC charging pile power stable state, and constructs the intelligent AC charging pile overload prediction model, specifically including: Obtain analytical datasets for overload prediction; Based on the analysis data set, obtain the knowledge graph of overload prediction under the power stable state; Based on the overload prediction knowledge graph, an intelligent AC charging pile overload prediction model is constructed.

8. An overload prediction system for an intelligent AC charging pile, characterized in that: The method for predicting overload of a smart AC charging pile as claimed in any one of claims 1 to 7 comprises: Time division module: the charging time is divided into various time feature texts by equal time division, based on the start time when the user confirms the start of charging on the user information terminal as the start time of using the smart AC charging pile, and each time feature text is marked as 1, 2, ..., i, ..., n in sequence; Power data acquisition module: selecting the first power text feature based on the time feature text; Power data preprocessing module: preprocessing the first power text to obtain the second power text; Power data analysis module: obtains any text output value based on the second power text analysis; Power data comprehensive evaluation module: obtains comprehensive power text evaluation value based on multiple text output values ​​in S4; Charging pile stability judgment module: judges the charging pile based on the comprehensive power text evaluation value and issues an early warning for the judgment result; Overload prediction module: Based on the judgment result of S6, overload prediction is performed for the unstable state of AC charging pile without power; Human-computer interaction module: outputs information based on overload prediction and user information terminal.

9. The overload prediction system of an intelligent AC charging pile according to claim 8, characterized in that: The human-computer interaction module establishes an overload risk assessment model based on overload prediction, evaluates the overload risk of the AC charging pile under different time feature texts, and obtains the overload risk threshold based on the overload risk assessment model. If the overload prediction value is less than the overload risk threshold, it means that the AC charging pile has no overload risk at this time, and the power data processing and analysis of the charging process continues. If the overload prediction value is greater than or equal to the risk threshold, it means that the AC charging pile has an overload risk at this time, and the power supply is immediately cut off, and an audible and visual alarm signal is issued.

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