Method for identifying privately built charging piles based on property user electricity load data

Abstract

This invention discloses a method for identifying privately built charging piles based on the electricity load data of property users. The method includes: cleaning the daily electricity load data of all charging pile users; labeling all charging pile data using a first labeling method; and extracting the electricity consumption characteristics of charging pile users from all labeled data. It also involves acquiring the daily electricity load data of all property users within the community, labeling the daily electricity load data of all property users using the first labeling method, and analyzing the community's electricity consumption characteristics from the labeled data of all property users. If the electricity consumption characteristics of a property user do not meet the community's electricity consumption characteristics but meet the charging pile user's electricity consumption characteristics, then it is determined that a property user in the community is using a privately built charging pile. Identifying and monitoring users who may have privately built charging piles within a community at the community level helps to rationally allocate electricity resources and ensure the safe electricity use of other residents in the community.

Description

Technical Field

[0001] This invention relates to the field of electric vehicle charging pile technology, specifically a method for judging privately built charging piles based on property user electricity load data. Background Technology

[0002] Electric vehicles typically rely on charging stations for energy storage. However, the installation of these stations requires approval from the State Grid Corporation of China before they can be put into use. After registration, a separate meter for each charging station is created in the State Grid system. Some property management companies organize residents to use their self-built charging stations, which can handle higher loads. However, because charging stations have high power consumption, if too many charging stations in a particular area (which may supply power to multiple communities) are not reported, even if the property management company can handle a higher load, the use of all charging stations can lead to excessive power load in that area, causing power outages or rationing, and inconveniencing residents. Therefore, it is necessary to determine whether any property management companies in each community have privately built charging stations in order to manage their power load and ensure the safety of residents' electricity use. Summary of the Invention

[0003] The purpose of this invention is to provide a method for identifying privately built charging piles based on the electricity load data of property users. By analyzing the electricity load characteristics of charging pile users and comparing them with the electricity characteristics of all property users in the community, if a property user's electricity characteristics do not meet the community's electricity characteristics but are similar to those of the charging pile user, it indicates that a property user in that community has privately built a charging pile. This facilitates State Grid staff in supervising users with privately built charging piles and standardizing the installation of charging piles, which is beneficial to the safe electricity use of other property users in the community and the safe operation of State Grid.

[0004] This application provides a method for identifying privately built charging piles based on property user electricity load data, including the following steps:

[0005] S1. Obtain the daily electricity load data of all charging pile users. After cleaning the daily electricity load data of all charging pile users, obtain all charging pile data. Label all charging pile data using the first label method to obtain all charging pile label data. Extract the electricity consumption characteristics of charging pile users from all charging pile label data.

[0006] S2. Obtain the daily electricity load data of all property users in the community, label the daily electricity load data of all property users according to the first labeling method, obtain the label data of all property users, and analyze the electricity consumption characteristics of the community from the label data of all property users.

[0007] S3. When the electricity consumption characteristics of a property user do not meet the electricity consumption characteristics of the community, determine whether there is a similar relationship between the electricity consumption characteristics of the property user and the charging pile user. If there is, determine that there is a property user in the community using a privately built charging pile.

[0008] Furthermore, the specific process of the first labeling method is as follows:

[0009] Sa: Collect daily electricity load data at fixed time intervals to obtain n electricity load points for each day. Label these n electricity load points chronologically and mark them with the date, storing them in the first electricity load database for each day, denoted as Pax(P1, P2, ..., P...). n );

[0010] Sb, determine the charging status of each electrical load point in Pax and mark the charging status; the charging status includes positive charging and no charging; obtain the charging status mark of each electrical load point; the determination method is: determine the charging status of each electrical load point according to the load size corresponding to each electrical load point;

[0011] Sc. Combine the charging status labels of n power load points to obtain the daily charging tag, denoted as Pax. 状态 (Charging state 1, charging state 2, ..., charging state n);

[0012] Sd, Repeat steps Sa-Sc for all electricity load data to obtain the charging tags for all days, denoted as ax(Pa1). 状态 P a2 状态 Pax 状态 ).

[0013] Furthermore, the first preprocessing method also includes:

[0014] Se, improve the daily charging tags, and add ax days' worth of charging tags Pax. 状态 The first half of the charging status label is added to Pax-1 for ax-1 days. 状态 In the middle; get the complete daily charging tag;

[0015] Sf, refine the daily charging tags in ax according to step Se to obtain the complete charging tags for all days, denoted as ax'(Pa1'). 状态 , P a2' 状态 ,…,Pax' 状态 ).

[0016] Furthermore, the specific process of extracting the electricity consumption characteristics of charging station users from all charging tag data is as follows:

[0017] Analyze the complete charging tags for each charging pile user every day to obtain the charging load characteristics for all days, including the start and end times of charging, the daily charging duration, and the electricity consumption per charge per day; calculate the charging pile load characteristics for a single charging pile user based on the charging load characteristics for all days.

[0018] The charging load characteristics of all charging pile users are statistically analyzed, and the electricity consumption characteristics of charging pile users are extracted. The electricity consumption characteristics of charging pile users include charging time period, charging power, charging duration, and electricity consumption per charge.

[0019] Furthermore, the specific process for analyzing the complete daily charging tags for each charging station user is as follows:

[0020] Extract the start and end times of charging each day: Iterate through the complete charging tags for each day, find the tag segments corresponding to the sudden changes in charging status, and use regular expressions to index and extract the power load points corresponding to the tag segments in the complete charging tags for each day as the start and end times of charging respectively; thus obtaining several start and end times of charging.

[0021] Calculate the daily charging time: Extract several charging time periods based on several charging start and end times, calculate the length of each charging time period, and select the longest charging time period to calculate the daily charging time.

[0022] Calculate the daily electricity consumption for charging once: Calculate the daily electricity consumption for charging once based on the load size of the electrical load point corresponding to the longest charging time period.

[0023] Furthermore, the process of calculating the charging pile load characteristics of a single charging pile user in a given location includes:

[0024] Calculate the peak charging time for a single user: Based on the start and end times of charging for all days, count the frequency at which each user starts charging at each time of day, and select the time with the highest frequency as the peak charging time for that user.

[0025] Calculate the average charging time for a single user: Calculate the average charging time for a single charging station user based on the charging time for all days.

[0026] Calculate the average electricity consumption per user per charge: Based on the electricity consumption per charge for all days, calculate the average electricity consumption per user per charge at a single charging station.

[0027] Calculate the average starting load value for charging for a single user: Based on the load size corresponding to the charging start time point for all days, calculate the average starting load value for charging for a single charging pile user.

[0028] Furthermore, the charging pile load characteristics also include the number of charging interval days for a single charging pile user. The process for obtaining the number of charging interval days is as follows:

[0029] Get the charging duration and start and end times of each charging station user for all days. Based on the daily charging duration, determine whether there is charging activity on that day. If so, tag the electricity load data for that day with a "charging activity" label.

[0030] Based on the charging dates corresponding to all electricity load data with charging tags for that day, calculate the number of days between two adjacent charging dates for each user, and then filter out the maximum, minimum, and average charging interval days for each user.

[0031] Furthermore, the process of obtaining the electricity consumption characteristics of charging station users includes:

[0032] Charging time period: Count the peak charging times of all charging pile users and group them according to time to get several time periods. Calculate the total frequency of charging at each time in each time period. Select the time period with the highest total frequency as the charging time period for all charging pile users and record the start and end times of charging corresponding to the charging time period.

[0033] Charging power of charging piles: The charging power of a single charging pile user is determined based on the average starting load value of the charging pile. All charging pile users are grouped according to their corresponding charging power.

[0034] Charging time of charging piles: This includes calculating the average single charging time of charging piles with different power levels based on the average charging time of all users in different charging power groups.

[0035] Electricity consumption per charge at a charging station: The average electricity consumption per charge at different power charging stations is calculated based on the average electricity consumption per charge for all users in different charging power groups.

[0036] Furthermore, the process of extracting the electricity consumption characteristics of the community is as follows:

[0037] Based on the complete charging tags of all property users for all days, the off-peak electricity consumption periods of the community are obtained, along with the average electricity consumption and average load per household during the off-peak electricity consumption periods, and the average electricity consumption and average load per household during the charging period at the charging station.

[0038] Furthermore, the number of all property management users within the community is counted. When the total number of all property management users in the community exceeds a preset threshold, and any of the following similarities is met, it is determined that a property management user in the community is using a privately built charging station:

[0039] Similarity 1: During off-peak hours in the community, the electricity consumption of property users is greater than the average electricity consumption per household, and the electricity consumption during the charging time at the charging station is similar to the electricity consumption for a single charge at the charging station.

[0040] Similarity Relationship 2: During the off-peak hours of electricity consumption in the community, the maximum load value of property users is greater than the average load value per household, and the maximum load value is similar to the charging power of the charging pile, and the time that the maximum load value remains at the charging power of the charging pile is similar to the charging duration of the charging pile.

[0041] Similarity Relationship 3: During the charging period of the charging pile, the electricity consumption of property users is greater than the average electricity consumption per household and is similar to the electricity consumption of charging the charging pile once;

[0042] Similarity Relationship 4: During the charging period of the charging pile, the maximum load value of the property users is greater than the average load value per household, and the maximum load value is similar to the charging power of the charging pile.

[0043] The beneficial effects of this invention are as follows:

[0044] This application extracts features from the electricity load data of charging pile users. Starting from the most granular data dimension of 96 daily load points for each charging pile user, it fully considers the data differences caused by different charging pile models and charging habits, and deeply mines the electricity consumption characteristics of charging pile users. The load and electricity consumption of property users within a residential community are relatively stable daily, and their values ​​are generally related to the size of the community. Therefore, it is necessary to first screen based on the electricity consumption characteristics of all properties within the community. If the electricity consumption characteristics of a property user are significantly different from those of other property users in the community, it indicates that they may have privately installed charging piles. Then, the electricity consumption characteristics of property users that do not conform to the community's electricity consumption characteristics are compared with those of charging pile users. If the characteristics are highly similar, the possibility of privately installed charging piles is highest. Identifying users within a community who may have privately installed charging piles for monitoring, and incorporating the electricity load of these privately installed charging piles into the community's electricity planning, helps to rationally allocate electricity resources and ensure the safe electricity use of other residents within the community. Attached Figure Description

[0045] Figure 1 This is a schematic diagram of the method for judging privately built charging piles based on the electricity load data of property users according to the present invention;

[0046] Figure 2 This is a logic diagram for determining private stakes according to a specific embodiment of the present invention.

[0047] Figure 3 This is a specific embodiment of the present invention showing the power load points of charging pile users and their corresponding charging status markings.

[0048] Figure 4A schematic diagram of a complete daily charging tag provided for a specific embodiment of the present invention;

[0049] Figure 5 This is a specific embodiment of the present invention showing the capture of charging start and end time points;

[0050] Figure 6 This is a specific embodiment of the present invention, showing the extraction of charging features of charging pile users. Detailed Implementation

[0051] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the present invention or its application or use. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0052] Unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps described in these embodiments do not limit the scope of the invention.

[0053] At the same time, it should be understood that, for ease of description, the dimensions of the various parts shown in the accompanying drawings are not drawn according to actual scale.

[0054] Furthermore, for clarity and brevity, descriptions of well-known structures, functions, and configurations may have been omitted. Those skilled in the art will recognize that various changes and modifications can be made to the examples described herein without departing from the spirit and scope of this disclosure.

[0055] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and equipment should be considered part of the specification.

[0056] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values.

[0057] Example 1

[0058] like Figure 1 As shown, this embodiment provides a method for identifying privately built charging piles based on property user electricity load data, including the following steps:

[0059] S1. Obtain the daily electricity load data of all charging pile users. After cleaning the daily electricity load data of all charging pile users, obtain all charging pile data. Label all charging pile data using the first label method to obtain all charging pile label data. Extract the electricity consumption characteristics of charging pile users from all charging pile label data.

[0060] S2. Obtain the daily electricity load data of all property users in the community, label the daily electricity load data of all property users according to the first labeling method, obtain the label data of all property users, and analyze the electricity consumption characteristics of the community from the label data of all property users.

[0061] S3. When the electricity consumption characteristics of a property user do not meet the electricity consumption characteristics of the community, determine whether there is a similar relationship between the electricity consumption characteristics of the property user and the charging pile user. If there is, determine that there is a property user in the community using a privately built charging pile.

[0062] Specifically, the process of extracting the electricity consumption characteristics of charging station users is as follows:

[0063] S11. Clean the data. To remove some invalid data from all charging pile users, calculate the historical maximum load of each charging pile user. If the historical maximum load of a charging pile user is 0 or close to 0, it indicates that the charging pile user has not charged (application submitted but not used). All data of the user is invalid, and the data of the charging pile user is deleted from the analysis data.

[0064] S12. Obtain charging pile tag data, and acquire the daily electricity load data of each valid charging pile user after cleaning in step S11, denoted as A. m (a1, a2, ..., ax); The daily electricity load data of each charging pile user is tagged with a charging tag using the first tagging method, and charging features are extracted to obtain the charging pile tag data:

[0065] The specific process of applying the first labeling method to charging station users is as follows:

[0066] 1.1. Collect power load points: For A m For each data point in the database, electricity load data is collected at fixed time intervals each day, resulting in n electricity load points for each day. These n electricity load points are then numbered and dated in chronological order and stored in the first electricity load database for each day, denoted as Pax(P1, P2, ..., P...). nIn one specific implementation, the daily electricity load data is collected at 15-minute intervals, and a total of 96 electricity load values ​​are collected for each charging pile user at each time point every day, corresponding to 96 time points from P1 to P96 (for example, P1 represents 0:15, P2 represents 0:30, P3 represents 0:45, and so on). The interval between two adjacent load points is 15 minutes, or 0.25 hours.

[0067] 1.2 Determine the charging status of each electrical load point in Pax, including positive charging and no charging; and mark the charging status; obtain the charging status mark of each electrical load point; the determination method is: determine the charging status of each electrical load point according to the load size corresponding to each electrical load point;

[0068] Specifically, when a charging station is not charging, its load may be much smaller than when charging, but still greater than 0 (e.g., 0.005kW). At the very end of the charging process, the load may decrease significantly, but still be significantly greater than the load when not charging. Generally, the minimum power of a common electric vehicle charging station is 5kW. To determine the charging status of each user's electrical load point at any given time, points with a load less than 1kW can be marked as "0" (not charging), and others as "1" (charging).

[0069] 1.3 Obtain the daily charging tags for charging station users, and combine the charging status labels of n power load points to obtain the daily charging tag; denoted as Pax. 状态 (Charging state 1, charging state 2, ..., charging state n); for example, Pax 状态 (1100….001), Pax 状态 This includes 96 status information items; repeat the above steps for all electricity load data to obtain the charging tags for all days, denoted as ax(Pa1). 状态 P a2 状态 Pax 状态 ).

[0070] Specifically, a string of length 96, composed of 0s and 1s, is obtained, called the daily charging tag. This clearly records the charging status of the user at 96 electricity load points throughout the day, such as... Figure 3 As shown, the power load points P1 to P8 (partial) of a certain charging pile user on a certain date and the corresponding charging status labels are given.

[0071] 1.4 Correct the daily charging labels. There are cases where a certain power load point is in the state of not charging, but several power load points before and after it are in the state of positive charging, such as 101. Considering that users are unlikely to deliberately stop charging for 15 minutes in the middle, it is considered that load data was missed at this point. Therefore, the charging status of the load point is changed to positive charging, and "101" in the charging label is replaced with "111".

[0072] 1.5. Improve the daily charging tags by adding half of the charging status labels from the charging tags of the next two consecutive days in Am to the charging tags of the previous day, and update the daily charging tags to obtain the complete daily charging tags.

[0073] Analysis of user charging start times revealed that most users prefer to start charging between 11 PM and midnight, with charging sessions typically lasting several hours. Therefore, many charging processes span multiple dates. Studying charging pile load characteristics involves charging duration, start and end times, and load changes throughout the charging process. Therefore, the analysis should be based on a complete charging process, not individual dates. To record the entire charging process, the load data for the first half of the following day can be added to the load data for each user on each date. For example, the load data for user A on July 1st should include the load data for the first 12 hours of July 2nd, resulting in new load data for user A on July 1st. This would give user A 144 load points on July 1st. Figure 4 This provides the electricity load data for a specific charging station user on July 1st, along with the complete composition of the charging tag for that day. Similarly, user A's load data for July 2nd requires the addition of load data from the first half of July 3rd, and so on for other dates.

[0074] S13. Extract the electricity consumption characteristics of charging pile users. The specific process is as follows:

[0075] S131. Analyze the complete daily charging tags for each charging station user. The specific process is as follows:

[0076] 2.1 Extracting the start and end times of charging each day: Traverse the complete charging tags for each day, find the tag segments corresponding to the sudden changes in charging status, and use regular expressions to index and extract the corresponding power load points from the corresponding tag segments as the start and end times of charging; thus obtaining several start and end times of charging.

[0077] For example, in a charging tag with a character length of 144, one or more segments contain interfering (or erroneous) data, such as "1001001". Therefore, the tag segments "0011" and "1100" representing a sudden change in charging status are used as the start and end markers for charging, respectively, instead of "01" and "10". Figure 5 Regular expressions are used to extract the start and end indices of the charging segment within the complete charging tag set (the indices corresponding to the start and end times of each charging action), such as... Figure 5 The charging start index is 58 and the charging end index is 65, which correspond to two times of the day when the electricity load points P58 and P65 are respectively used as the start and end times of charging.

[0078] 2.2 Calculate the daily charging time: Extract several charging time periods based on several charging start and end times, calculate the length of each charging time period, and select the longest charging time period to calculate the daily charging time.

[0079] The extracted charging time periods may be one or more segments. These charging time periods need to be categorized by date. Since later tags in the complete charging tag list belong to the next day, if the earliest charging start marker is "0011," i.e., 0:45 AM (P3), then charging activities with a starting index less than 99 (i.e., before 0:45 AM the next day) are counted as the current day; otherwise, they are counted as the next day. This solves the problem of load data being distributed across two days and thus unanalyzable when charging across multiple dates.

[0080] 2.3 Calculate the daily charging power consumption: Calculate the daily charging power consumption based on the load size of the electrical load point corresponding to the longest charging time period.

[0081] Given that it's relatively rare for a single user to charge multiple times a day, to analyze the load characteristics of a single charging session, the longest charging segment of the day is taken as the start and end time of that day's charging activity. For example... Figure 3 The longest charging period for user 123 on June 15th was from P95 to P109, while user 234 charged once, from P58 to P68. Since the two adjacent load points are 0.25 hours apart, taking user 234 as an example, the charging duration for that user on that day is calculated as 0.25 * (end time index - start time index + 1). Therefore, the electricity consumption for one charge for that user is 0.25 * (the sum of load values ​​between the start and end times of charging). Figure 6 .

[0082] S132. Calculate the charging pile load characteristics for a single charging pile user. The specific process is as follows:

[0083] 3.1 Calculating Peak Charging Times for Individual Users: Based on the start and end times of charging for all days, count the frequency of each user starting charging at each time of day, and select the time with the highest frequency as the peak charging time for that user. Count the frequency of each user starting charging at each time (e.g., user A starts charging at 10 PM 19 times, starts charging at 8 PM 8 times, ...), and select the time with the highest frequency for each user. The data obtained is the time when multiple users start charging most frequently. For example, user A started charging at 10 PM 19 days, ranking first in frequency, so this user prefers to start charging at 10 PM.

[0084] 3.2 Calculate the average charging time for a single user: Based on the charging time for all days, calculate the average charging time for a single charging station user; statistical analysis of the data shows that the average charging time for charging station users is generally concentrated between 3.5 and 8 hours.

[0085] 3.3 Calculate the average electricity consumption per charge for a single user: Calculate the average electricity consumption per charge for a single user at a charging station based on the electricity consumption per charge for all days.

[0086] 3.4 Calculate the average starting load value for charging for a single user: Calculate the average starting load value for charging for a single charging pile user based on the load size corresponding to the charging start time point for all days.

[0087] 3.5 Calculate the charging interval days. The calculation process is as follows:

[0088] 3.5.1 Obtain the charging duration and start and end times for each charging station user for all days. Based on the daily charging duration, determine whether there is charging activity on that day. If so, tag the electricity load data for that day with a "charging activity" label.

[0089] 3.5.2 Based on the charging dates corresponding to all the electricity load data with charging tags for the current day, calculate the number of days between two adjacent charging dates for each user, and filter out the maximum, minimum and average charging interval days for each user.

[0090] S133. Extracting the electricity consumption characteristics of charging pile users, the specific process includes:

[0091] 4.1 Charging Station Charging Time Periods: Peak charging times for all charging station users were statistically analyzed and grouped into time periods. The total frequency of charging starts at each time point within each time period was calculated. The time period with the highest total frequency was selected as the charging time period for all charging station users, and the start and end times of each charging time period were recorded. Research revealed that most people start charging between 10 PM and midnight, especially between 11 PM and midnight. Therefore, if a user has installed a private charging station, its load is likely to suddenly increase between 11 PM and midnight.

[0092] 4.2 Charging Power of Charging Piles: Based on the average starting load value of a single charging pile user, the charging power corresponding to a single charging pile user is determined, and all charging pile users are grouped according to the corresponding charging power. The load value at the start of charging for charging piles with different power is statistically analyzed. It is found that the starting load of a 7kW charging pile is generally between 6 and 7.5kW, and such a load will generally last for at least 4 hours. The average starting load of a 5kW charging pile is 4.22kW.

[0093] 4.3 Charging Time: This includes calculating the average single charging time for charging piles of different power levels based on the average charging time of all users in different charging pile groups. Based on the average single charging time for charging piles of different power levels, the overall average single charging time for all charging piles is approximately 4.57 hours. Users with charging piles of 7kW and 8kW power are the most numerous and representative, with an average charging time of 4.66 hours for this group.

[0094] 4.4 Electricity Consumption per Charge: Based on the average electricity consumption per charge for all users of different charging piles in different charging power groups, the average electricity consumption per charge for different power charging piles is calculated. The average electricity consumption per charge for most charging pile users is concentrated between 15 and 50 kWh, while the average electricity consumption per charge for users with charging pile power of 7 kW and 8 kW is 32.51 kWh.

[0095] In step S2, the process of extracting the electricity consumption characteristics of the community is as follows:

[0096] S21. Label the electricity load data of all property users in the community according to the first labeling method in step S12 above, to obtain the label data of all property users, specifically including:

[0097] Electricity load data for each property user was collected daily at 15-minute intervals, resulting in 96 time points per day for each user, corresponding to times P1 to P96 (e.g., P1 represents 0:15, P2 represents 0:30, P3 represents 0:45, and so on). Adjacent load points were spaced 15 minutes apart, or 0.25 hours. To maintain consistency with charging station users' electricity usage, load points with a load less than 1kW were marked as "0" (no electricity used), and others as "1" (electricity used). The daily charging tags for property users did not require correction, as their electricity usage is inherently uncertain. However, to ensure comparability with charging station users across timeframes, the daily charging tags for property users were refined. This refinement involved adding half of the charging tags from the following day to the previous day's, and arranging the two days' tags in chronological and date order. This yielded the complete daily tags for each property user.

[0098] S22. Based on the complete charging tags of all property users for all days, analyze the data of all property users in the community, remove some data that are significantly different from other property users, and analyze and summarize the off-peak electricity consumption periods of the community from all the data after removal, as well as the average electricity consumption and average load per household during the off-peak electricity consumption periods.

[0099] S23. Based on step S22, analyze the average electricity consumption and average load per household in the community during the charging period of the charging pile.

[0100] In step S3, the privately installed charging piles of property management users within the community are judged.

[0101] Since property management users exist within residential communities, and the number of households varies across communities (100 households, 500 households, etc.), it's possible to analyze the load characteristics of property management users in communities with different numbers of households (average load per household, average electricity consumption per household, off-peak hours, periods of relatively stable load, etc.). Some communities with a small number of households may not have the conditions to build charging stations and can be directly excluded. The daily electricity load and consumption of property management users are likely to be relatively stable. If there is a sudden increase in load at a certain moment (the increase is approximately the power of a charging station, such as 7kW) and it lasts for several hours, it may indicate the use of privately installed charging stations. Furthermore, the load performance of property management users during off-peak hours can be observed to identify private charging stations, as peak household electricity consumption is generally concentrated between 7 PM and 11 PM, while charging activity typically occurs between 11 PM and the early morning. Additionally, the electricity load characteristics of property management users may differ between weekdays, weekends, and holidays. Analysis of the electricity consumption characteristics of property management users on weekends and holidays can also be used to identify private charging stations.

[0102] Specifically, such as Figure 2 As shown, based on the above analysis of the differences between the electricity consumption characteristics of property users and the electricity consumption characteristics of charging piles, the following logic for judging private charging piles is formulated:

[0103] The system counts the total number of property management users within a residential community. If the total number of property management users exceeds a preset threshold (e.g., more than 100 households), and any of the following similarities are met, it is determined that a property management user within the community is using a privately installed charging station:

[0104] Similarity 1: During off-peak hours in the community, the electricity consumption of property users is greater than the average electricity consumption per household, and the electricity consumption during the charging time at the charging station is similar to the electricity consumption for a single charge at the charging station.

[0105] Similarity Relationship 2: During the off-peak hours of electricity consumption in the community, the maximum load value of property users is greater than the average load value per household, and the maximum load value is similar to the charging power of the charging pile, and the time that the maximum load value remains at the charging power of the charging pile is similar to the charging duration of the charging pile.

[0106] Similarity Relationship 3: During the charging period of the charging pile, the electricity consumption of property users is greater than the average electricity consumption per household and is similar to the electricity consumption of charging the charging pile once;

[0107] Similarity Relationship 4: During the charging period of the charging pile, the maximum load value of the property users is greater than the average load value per household, and the maximum load value is similar to the charging power of the charging pile.

[0108] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Based on the technical essence of the present invention, any simple modifications, equivalent substitutions, and improvements made to the above embodiments within the spirit and principles of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A method for identifying privately built charging piles based on property user electricity load data, characterized in that, Includes the following steps: S1. Obtain the daily electricity load data of all charging pile users. After cleaning the daily electricity load data of all charging pile users, obtain all charging pile data. Label all charging pile data using the first label method to obtain all charging pile label data. Extract the electricity consumption characteristics of charging pile users from all charging pile label data. The specific process of the first labeling method is as follows: Sa: Collect daily electricity load data at fixed time intervals to obtain n electricity load points for each day. Label these n electricity load points chronologically and mark them with the date, storing them in the first electricity load database for each day, denoted as Pax (P1, P2, ..., P...). n ); Sb, determine the charging status of each electrical load point in Pax and mark the charging status; the charging status includes positive charging and no charging; obtain the charging status mark of each electrical load point; the determination method is: determine the charging status of each electrical load point according to the load size corresponding to each electrical load point; Sc. Combine the charging status labels of n power load points to obtain the daily charging tag, denoted as Pax. 状态 (Charging state 1, charging state 2, ..., charging state n); Sd, Repeat steps Sa-Sc for all electricity load data to obtain charging tags for all days, denoted as ax (Pa1). 状态 P a2 状态 Pax 状态 ); Se, improve the daily charging tags, and add ax days' worth of charging tags Pax. 状态 The first half of the charging status label is added to Pax-1 for ax-1 days. 状态 In the middle; get the complete daily charging tag; Sf, refine the daily charging tags in ax according to step Se to obtain the complete charging tags for all days, denoted as ax'(Pa1'). 状态 , P a2' 状态 ,…,Pax' 状态 ); S2. Obtain the daily electricity load data of all property users in the community, label the daily electricity load data of all property users according to the first labeling method, obtain the label data of all property users, and analyze the electricity consumption characteristics of the community from the label data of all property users. S3. When the electricity consumption characteristics of a property user do not meet the electricity consumption characteristics of the community, determine whether there is a similar relationship between the electricity consumption characteristics of the property user and the charging pile user. If there is, determine that there is a property user in the community using a privately built charging pile.

2. The method for judging privately built charging piles based on property user electricity load data according to claim 1, characterized in that, The specific process for extracting the electricity consumption characteristics of charging station users from all charging tag data is as follows: Analyze the complete charging tags for each charging pile user every day to obtain the charging load characteristics for all days, including the start and end times of charging, the daily charging duration, and the electricity consumption per charge per day; calculate the charging pile load characteristics for a single charging pile user based on the charging load characteristics for all days. The charging load characteristics of all charging pile users are statistically analyzed, and the electricity consumption characteristics of charging pile users are extracted. The electricity consumption characteristics of charging pile users include charging time period, charging power, charging duration, and electricity consumption per charge.

3. The method for judging privately built charging piles based on property user electricity load data according to claim 2, characterized in that, The specific process for analyzing the complete daily charging tags for each charging station user is as follows: Extract the start and end times of charging each day: Iterate through the complete charging tags for each day, find the tag segments corresponding to the sudden changes in charging status, and use regular expressions to index and extract the power load points corresponding to the tag segments in the complete charging tags for each day as the start and end times of charging respectively; thus obtaining several start and end times of charging. Calculate the daily charging time: Extract several charging time periods based on several charging start and end times, calculate the length of each charging time period, and select the longest charging time period to calculate the daily charging time. Calculate the daily electricity consumption for charging once: Calculate the daily electricity consumption for charging once based on the load size of the electrical load point corresponding to the longest charging time period.

4. The method for judging privately built charging piles based on property user electricity load data according to claim 2, characterized in that, The process of calculating the charging pile load characteristics of a single charging pile user includes: Calculate the peak charging time for a single user: Based on the start and end times of charging for all days, count the frequency at which each user starts charging at each time of day, and select the time with the highest frequency as the peak charging time for that user. Calculate the average charging time for a single user: Calculate the average charging time for a single charging station user based on the charging time for all days. Calculate the average electricity consumption per user per charge: Based on the electricity consumption per charge for all days, calculate the average electricity consumption per user per charge at a single charging station. Calculate the average starting load value for charging for a single user: Based on the load size corresponding to the charging start time point for all days, calculate the average starting load value for charging for a single charging pile user.

5. The method for judging privately built charging piles based on property user electricity load data according to claim 2, characterized in that, The charging pile load characteristics also include the number of charging interval days for a single charging pile user. The process for obtaining the number of charging interval days is as follows: Get the charging duration and start and end times of each charging station user for all days. Based on the daily charging duration, determine whether there is charging activity on that day. If so, tag the electricity load data for that day with a "charging activity" label. Based on the charging dates corresponding to all electricity load data with charging tags for that day, calculate the number of days between two adjacent charging dates for each user, and then filter out the maximum, minimum, and average charging interval days for each user.

6. The method for judging privately built charging piles based on property user electricity load data according to claim 4, characterized in that, The process of obtaining the electricity consumption characteristics of charging station users includes: Charging time period: Count the peak charging times of all charging pile users and group them according to time to get several time periods. Calculate the total frequency of charging at each time in each time period. Select the time period with the highest total frequency as the charging time period for all charging pile users and record the start and end times of charging corresponding to the charging time period. Charging power of charging piles: The charging power of a single charging pile user is determined based on the average starting load value of the charging pile. All charging pile users are grouped according to their corresponding charging power. Charging time of charging piles: This includes calculating the average single charging time of charging piles with different power levels based on the average charging time of all users in different charging power groups. Electricity consumption per charge at a charging station: The average electricity consumption per charge at different power charging stations is calculated based on the average electricity consumption per charge for all users in different charging power groups.

7. The method for judging privately built charging piles based on property user electricity load data according to claim 2, characterized in that, The process of analyzing the electricity consumption characteristics of the community is as follows: Based on the complete charging tags of all property users for all days, the off-peak electricity consumption periods of the community are obtained, along with the average electricity consumption and average load per household during the off-peak electricity consumption periods, and the average electricity consumption and average load per household during the charging period at the charging station.

8. The method for judging privately built charging piles based on property user electricity load data according to claim 7, characterized in that, The system counts the total number of property management users within a residential community. If the total number of property management users exceeds a preset threshold, and any of the following similarities are met, it is determined that a property management user within the community is using a privately installed charging station: Similarity 1: During off-peak hours in the community, the electricity consumption of property users is greater than the average electricity consumption per household, and the electricity consumption during the charging time at the charging station is similar to the electricity consumption for a single charge at the charging station. Similarity Relationship 2: During the off-peak hours of electricity consumption in the community, the maximum load value of property users is greater than the average load value per household, and the maximum load value is similar to the charging power of the charging pile, and the time that the maximum load value remains at the charging power of the charging pile is similar to the charging duration of the charging pile. Similarity Relationship 3: During the charging period of the charging pile, the electricity consumption of property users is greater than the average electricity consumption per household and is similar to the electricity consumption of charging the charging pile once; Similarity Relationship 4: During the charging period of the charging pile, the maximum load value of the property users is greater than the average load value per household, and the maximum load value is similar to the charging power of the charging pile.

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