Data matching method, device and electronic equipment in charging facility verification

Abstract

The present application relates to a data matching method, device, and electronic device in the verification of charging facilities. Among them, the data matching method includes: obtaining a number of charging orders of the charging facilities to be verified through the operation system of the charging facilities; respectively matching the corresponding charging event buckets according to the start time of each charging order, and a plurality of charging event buckets are obtained by dividing a number of charging events based on their own start times; for each charging order, matching the corresponding charging event according to the target similarity in its corresponding charging event bucket, and the target similarity is obtained by weighted summation of the start time proximity, duration proximity, time interval overlap degree, and power proximity. Compared with the matching method of traversing all charging events, it has the technical effect of higher efficiency. It solves the problem of low data matching efficiency of the data matching method in the current verification of charging facilities.

Description

Technical Field

[0001] The present application relates to the field of charging verification, and particularly to a data matching method, apparatus, and electronic device in charging facility verification. Background Art

[0002] In on-line metrological verification of charging facilities, a separate remote metrological verification module can be installed to separately measure the charging process data. After the charging pile remote verification platform (hereinafter referred to as the verification platform) obtains the complete charging event data through the remote metrological verification module, the charging event data is then matched and compared with the charging order data of the charging pile operator management system (hereinafter referred to as the operator system) to determine whether the error is qualified. Among them, due to the low penetration rate between the verification platform and the operator system, the data between the two cannot be compared in real time, and a large amount of data to be compared will accumulate. Before the comparison, a large amount of data to be compared needs to be matched, and the traditional data matching method in charging facility verification mainly relies on the start and end times of the data and traverses all charging data for data matching. First, since it needs to traverse all charging data, the data matching efficiency is low; second, when the start time or end time of the data is missing, data matching cannot be performed or the matching accuracy drops significantly.

[0003] Aiming at the problem of low data matching efficiency of the current data matching method in charging facility verification, no effective solution has been proposed yet. Summary of the Invention

[0004] In the present invention, a data matching method, apparatus, and electronic device in charging facility verification are provided to solve the problem of low data matching efficiency of the current data matching method in charging facility verification.

[0005] In a first aspect, the present invention provides a data matching method in charging facility verification, which includes:

[0006] Obtaining a number of charging orders of a charging facility to be verified through the operation system of the charging facility;

[0007] Respectively matching corresponding charging event buckets according to the start time of each charging order, and a plurality of charging event buckets are obtained by dividing a number of charging events based on their own start times;

[0008] For each charging order, matching the charging event corresponding to it according to a target similarity S i in the corresponding charging event bucket, and the target similarity S i is the start time proximity S t and the duration proximity S d, Time interval overlap S o and power proximity S e are obtained by weighted summation.

[0009] Second, in the present invention, a data matching device in charging facility verification is provided, which includes:

[0010] An order acquisition module for acquiring a number of charging orders of the charging facility to be verified through the operation system of the charging facility;

[0011] A first matching module for respectively matching corresponding charging event buckets according to the start time of each charging order, and a plurality of charging event buckets are obtained by dividing a number of charging events based on their own start times;

[0012] A second matching module for, for each charging order, matching the corresponding charging event in the corresponding charging event bucket according to the target similarity S i The target similarity S i is the start time proximity S t , duration proximity S d , time interval overlap S o and power proximity S e are obtained by weighted summation.

[0013] Third, in the present invention, an electronic device is provided, including a memory and a processor. A computer program is stored in the memory, and the processor is configured to run the computer program to execute the data matching method in charging facility verification described in the first aspect.

[0014] Compared with the related art, the data matching method in charging facility verification provided by the present invention first divides a number of charging events into multiple charging event buckets. When performing data matching, it preferentially matches the charging event bucket corresponding to the charging order, and then continues to match the corresponding charging event within the charging event bucket. Compared with the matching method of traversing all charging events, it has the technical effect of higher efficiency. It solves the problem of low data matching efficiency of the current data matching method in charging facility verification.

[0015] At the same time, when matching the charging event and the charging order, the start time proximity, duration proximity, time interval overlap and power proximity between the two are calculated, and the target similarity between the two is measured from multiple dimensions, which can achieve more accurate matching.

[0016] Details of one or more embodiments of the present application are set forth in the following drawings and description to make other features, objects, and advantages of the present application more concise and understandable. Description of the Drawings

[0017] Figure 1 is a flowchart of the data matching method in the charging facility verification provided in this embodiment;

[0018] Figure 2 is a block diagram of the data matching device in the charging facility verification provided in this embodiment. Detailed Embodiments

[0019] To understand the purpose, technical solution, and advantages of the present application more clearly, the present application will be described and illustrated below with reference to the drawings and embodiments.

[0020] Unless otherwise defined, the technical terms or scientific terms involved in the present application shall have the general meaning understood by those with ordinary skills in the technical field to which the present application belongs. In the present application, words such as "a", "an", "one kind", "the", "these", etc. do not indicate a limitation in quantity, and they can be singular or plural. The terms "including", "comprising", "having" and any variants thereof involved in the present application are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device including a series of steps or modules (units) is not limited to the listed steps or modules (units), but may include unlisted steps or modules (units), or may include other steps or modules (units) inherent in these processes, methods, products, or devices. The terms "connected", "coupled", etc. involved in the present application do not limit to physical or mechanical connections, but may include electrical connections, whether directly or indirectly. The term "plurality" involved in the present application means two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" may represent: A exists alone, A and B exist simultaneously, and B exists alone. Usually, the character " / " indicates that the objects associated before and after are in an "or" relationship. The terms "first", "second", "third", etc. involved in the present application are only used to distinguish similar objects and do not represent a specific order for the objects.

[0021] In this embodiment, a data matching method in the charging facility verification is provided. Figure 1 is a flowchart of the data matching method in the charging facility verification provided in this embodiment, as Figure 1 shown, this process includes: step S110, step S120, and step S130.

[0022] Step S110: Obtain a number of charging orders of the charging facilities to be verified through the operation system of the charging facilities. In this embodiment, the charging facilities are multiple charging piles.

[0023] When it is necessary to verify the charging facilities, all charging orders within a verification period are obtained from the operation system of the charging facilities. Each charging order should include information such as the start time, end time, and electricity quantity of the order. However, in some cases, the start time or end time of the charging order may be missing. For such charging events, how this embodiment deals with them will be introduced in detail later. After obtaining the charging orders, it is necessary to match these charging orders with the charging events, and the data of the charging events is obtained by the remote metering verification module through metering the charging facilities to be verified. Each charging event also includes information such as the start time, end time, and electricity quantity of the event. It should be noted that the data matching method in the charging facility verification of this embodiment is applied to the remote verification platform of the charging facilities, and the remote metering verification module is a local module within this platform. Therefore, the start time or end time of the charging event generally will not be lost. Among them, the charging event i can be represented as a quadruple: . , , and are the start time, end time, duration, and electricity quantity respectively. At the same time, the maximum effective charging time (maximum order duration) of the charging facilities to be verified can also be set according to the actual situation d max and the minimum effective charging time (minimum order duration) d min .

[0024] Step S120: Match the corresponding charging event bucket according to the start time of each charging order respectively. Multiple charging event buckets are obtained by dividing a number of charging events based on their own start times.

[0025] In the traditional data matching method, for each charging order, all charging events will be traversed to match the corresponding charging event, but this method is less efficient. In this embodiment, for a large number of charging events, they are pre-divided according to the start time and stored in different charging event buckets respectively. Then each charging event bucket contains multiple charging events whose start times are in the same time period.

[0026] Specifically, the division steps of multiple charging event buckets include:

[0027] Divide the verification period into multiple time periods at equal intervals, and divide multiple charging events whose start times are in the same time period into the same charging event bucket.

[0028] For the charging event bucket with the number of charging events exceeding the threshold, a target strategy is adopted to further divide the multiple charging events it contains into new multiple charging event buckets. The target strategy is as follows:

[0029]

[0030] Among them, T ( k ) is the time range of the charging event bucket k , C is the capacity threshold of the charging event bucket, K ( k ) represents the storage capacity of the charging event bucket k , weight ( k ) represents the dynamic gain function of the corresponding charging event bucket k , T min and T max are respectively the lower and upper limits of the time range of the charging event bucket k , adg(x,a,b) is an adaptive particle function used to constrain x between a and b . Δ K ( k ) is the change in the number of events of the charging event bucket k compared to the charging event bucket k -1, and are both weight adjustment parameters, is a preset positive number used to determine whether there is a significant change in the number of events. If , then weight ( k ) takes other values (usually 1 or a certain constant), indicating that when the data change is not significant, there is no need to adjust the time range of the bucket additionally. Among them, the change in the number of events can be the absolute value or the ratio of the change in the number of events.

[0031] The service life of the charging pile is usually about 10 years. Therefore, the time range for storing charging event data is also set to 10 years. For this purpose, a first-level time index is established first, and the charging start time of the charging events is classified into the corresponding year, month, and day. When the verification period is one day, it can be divided by hour first, and 24 hour buckets are initialized every day to correspond to the 24 hours of a day. In this way, the charging event bucket index of the charging pile can be expressed as:

[0032]

[0033] Among them, Bk Indicates the charging event bucket k , k is the index of the charging event bucket, indicates the start time of charging event i, W is the time length of the charging event bucket, such as one hour.

[0034] Through the above steps, multiple charging event buckets are initially obtained. Considering that there are peak and off-peak periods for charging every day, some charging event buckets contain more charging events, while some charging event buckets contain fewer charging events. Ensure that the amount of charging events stored in each charging event bucket does not exceed a preset threshold, thereby reducing the pressure on subsequent charging order queries. In this embodiment, the target strategy is used to re-partition the charging events in the charging event buckets where the number of charging events exceeds the threshold. The target strategy is essentially an adaptive particle binning strategy, and each charging event to be stored is regarded as a particle.

[0035] As introduced above about the partitioning of the charging event buckets, after the charging event buckets are partitioned, a corresponding charging event bucket can be matched for each charging order. Specifically matching the corresponding charging event bucket according to the start time of each charging order includes: obtaining the start time range of each charging order by adding a time error to the start time; for each charging order, using at least one charging event bucket that covers any point in its start time range as its corresponding charging event bucket.

[0036] Considering the problem of data asynchronization between charging orders and charging events, even for corresponding charging orders and charging events, there may be deviations in their start times or end times. Therefore, a preset time error is added to the start time of the charging order during the matching process. The start time range of charging order j can be expressed as . For example, when the time range of charging event bucket 5 is from 12:00 to 13:00 and the time range of charging event bucket 6 is from 13:00 to 14:00, if the start time range of a certain charging order is between 12:55 and 13:03, then both charging event buckets 5 and 6 cover a part of the start time range of this charging order, so both charging event buckets 5 and 6 are used as the corresponding charging event buckets for this charging order.

[0037] Step S130, for each charging order, match the charging event corresponding to it according to the target similarity S i The target similarity S i is the start time proximity S t 、duration proximity S d 、time interval overlap So and power proximity S e is obtained by performing weighted summation.

[0038] In this embodiment, the situation where the start time or end time of the charging order is missing is also considered. For a charging order with a missing start time, its start time is determined according to the maximum order duration and its end time; for a charging order with a missing end time, its end time is determined according to the maximum order duration and its start time. Among them, the maximum order duration is the maximum effective charging time of the charging facility to be verified d max For a charging order with a missing start time, its start time can be obtained by subtracting the maximum order duration from its end time For a charging order with a missing end time, its end time can be obtained by adding the maximum order duration to its start time .

[0039] During the charging event bucket matching process, the start time of the charging order is a key parameter. When the start time of the charging order is missing, although its start time can be calculated by the above steps, considering that it may cause greater errors, that is, matching to an inappropriate charging event bucket. Therefore, in this embodiment, for each charging order, according to the target similarity in its corresponding charging event bucket S i matching the corresponding charging event specifically includes: for each charging order: screening out the charging events with a power deviation ratio greater than the threshold in its corresponding charging event bucket, and according to the target similarity among the remaining charging events S i matching the corresponding charging event.

[0040] Among them, the calculation formula of the power deviation ratio is , is the power of charging event i, and is the power of charging order j. Through the above formula, the power deviation ratio between any charging event and charging order can be calculated. When the power deviation ratio is greater than the threshold (such as 5%), it is considered that the charging event and the charging order are significantly unmatched, and there is no need to further calculate the target similarity between the two, which simplifies the matching process.

[0041] Correspondingly, in other embodiments, the charging event bucket can also be considered as a basic unit to determine whether to screen it out. When the power deviation ratios of all charging events in a certain charging event bucket to the charging order to be matched are greater than the threshold, then screen out this charging event bucket, otherwise retain this charging event bucket, and then continue to calculate the target similarity between each charging event in this bucket and the charging order to be matched.

[0042] For the charging events that have not been screened out, continue to calculate their target similarity with the charging orders to be matched. The target similarity S i is calculated by the formula:

[0043]

[0044] where 、 、 and are four weights. When the start time or end time of the charging order is missing, 、 、 and are 0.3, 0.1, 0.1, and 0.5 respectively. Otherwise, 、 、 and are 0.3, 0.3, 0.3, and 0.1 respectively.

[0045] In different cases, the weight settings are different. When the start and end times of the charging order are complete, more attention is paid to the overlap of time. When one-sided start or end time of the charging order is missing, more attention is paid to the overlap of power consumption, because the start and end times of the charging order have a greater error at this time.

[0046] Furthermore, the calculation formula for the start time proximity S t is:

[0047]

[0048] The calculation formula for the duration proximity S d is:

[0049]

[0050] The calculation formula for the time interval overlap S o is:

[0051]

[0052] The calculation formula for the power proximity S e is:

[0053]

[0054] where and are the start time and end time of the charging event i respectively, Wis the time length of the charging event bucket where charging event i is located. and are the start time and end time of charging order j respectively. d i is the duration of charging event i; is and the minimum value in; is and the maximum value in; is the power of charging event i, is the power of charging order j.

[0055] For each charging order to be matched, select the charging event with the highest target similarity to it as the corresponding charging event.

[0056] As above, a complete embodiment illustrates the data matching method in the charging facility verification provided by the present invention.

[0057] It can be seen from the above description that this data matching method first divides several charging events into multiple charging event buckets. When performing data matching, it preferentially matches the charging event bucket corresponding to the charging order, and then continues to match the corresponding charging event within the charging event bucket. Compared with the matching method of traversing all charging events, it has the technical effect of higher efficiency. It solves the problem of low data matching efficiency of the data matching method in the current charging facility verification.

[0058] At the same time, when matching the charging event and the charging order, calculate the start time proximity S t 、duration proximity S d 、time interval overlap S o and power proximity S e, Measuring the target similarity between the two from multiple dimensions can achieve more accurate matching. The reason is that there may be a deviation of up to a few minutes between a charging order and a charging event, and there may be multiple charging orders (multiple charging piles) with approximate start and end times in the same time period. Relying solely on the start and end times cannot accurately match the charging event and the charging order. Exemplarily, the charging events stored in the case are: Event 1: 10:02 - 10:35, charging 28 kWh (user A actually charging); Event 2: 10:00 - 10:38, charging 35 kWh (user B actually charging). Now there is 1 charging order to be matched: reserved from 10:00 to 10:40, expected to charge 25 kWh (user A, household car, low power demand). If only considering the factor of start and end times, it is obvious that Event 2 better meets the conditions. After applying the data matching method in this embodiment, the target similarity of Event 1 is 0.8925, and the target similarity of Event 2 is 0.888. Event 1 is finally successfully matched with user A.

[0059] Moreover, charging events are preferentially divided into different charging event buckets according to time periods. To avoid a serious imbalance in the number of events in different charging event buckets, the target strategy is continued to further divide the charging event buckets with the number of events exceeding the threshold. Finally, the number of events in each charging event bucket is relatively balanced and does not exceed the threshold.

[0060] Finally, in the case where the start time or end time of a charging order is missing, the maximum order duration is used to determine the missing end time from the known start time or the missing start time from the known end time. Considering that this method may introduce errors and thus match to an inappropriate charging event bucket, when calculating the target similarity between a charging order and a charging event, the power deviation ratio between the two is preferentially calculated, and the target similarity is only calculated between a charging order and a charging event where the power deviation ratio is less than the threshold, thereby avoiding some meaningless target similarity calculations and improving the overall calculation efficiency.

[0061] In this embodiment, a data matching device in charging facility verification is also provided. This device is used to implement the data matching method in charging facility verification in this embodiment, and those that have been described will not be repeated here. The following terms such as "module", "unit", "sub-unit", etc. can be a combination of software and / or hardware that can achieve a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware is also possible and contemplated.

[0062] Figure 2 is the architecture diagram of the data matching device in charging facility verification provided in this embodiment. Refer to Figure 2, the data matching device in the charging facility verification provided in this embodiment includes: an order acquisition module, a first matching module, and a second matching module.

[0063] The order acquisition module: is used to obtain several charging orders of the charging facility to be verified through the operation system of the charging facility;

[0064] The first matching module: is used to respectively match the corresponding charging event buckets according to the start time of each charging order, and multiple charging event buckets are obtained by dividing several charging events based on their own start times;

[0065] The second matching module: is used for each charging order to match the corresponding charging event in its corresponding charging event bucket according to the target similarity S i The target similarity S i is the weighted sum of the start time proximity S t , the duration proximity S d , the time interval overlap S o and the power proximity S e obtained.

[0066] It should be noted that the above-mentioned various modules can be functional modules or program modules, and can be implemented either by software or by hardware. For the modules implemented by hardware, the above-mentioned various modules can be located in the same processor; or the above-mentioned various modules can also be located in different processors in any combined form.

[0067] In this embodiment, an electronic device is also provided, including a memory and a processor. A computer program is stored in the memory, and the processor is set to run the computer program to execute the data matching method in the charging facility verification in this embodiment.

[0068] It should be understood that the specific embodiments described here are only used to explain this application, rather than to limit it. According to the embodiments provided in this application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of this application.

[0069] Obviously, the accompanying drawings are only some examples or embodiments of the present application. For those of ordinary skill in the art, the present application can also be applied to other similar situations based on these drawings without creative efforts. Additionally, it can be understood that although the work done during this development process may be complex and time-consuming, for those of ordinary skill in the art, certain design, manufacturing, or production changes made based on the technical content disclosed in the present application are only conventional technical means and should not be regarded as insufficient disclosure of the present application.

Claims

1. A data matching method for charging facility verification, characterized in that: include: Obtaining a number of charging orders of the charging facilities to be inspected through the operation system of the charging facilities; The corresponding charging event bucket is matched according to the start time of each charging order. Multiple charging event buckets are obtained by dividing several charging events based on their own start time. For each charging order, in its corresponding charging event bucket, according to the target similarity S i Match the corresponding charging event, target similarity S i The start time proximity S t , duration proximity S d , Time interval overlap S o Proximity to power S e Perform weighted summation to obtain; The steps of dividing multiple charging event buckets include: The verification period is divided into multiple time periods at equal intervals, and multiple charging events with start times in the same time period are divided into the same charging event bucket; For charging event buckets whose number of charging events exceeds the threshold, the target strategy is used to further divide the multiple charging events contained in it into multiple new charging event buckets. The target strategy is: ， in, Charging event bucket k time range, C is the capacity threshold of the charging event bucket, Represents charging event bucket k The storage capacity, Indicates the corresponding charging event bucket k The dynamic gain function is T min and T max Charging event buckets k The lower and upper limits of the time range, adg(x,a,b) is an adaptive particle function, which is used to x Constraints a and b between.

2. The data matching method in charging facility verification according to claim 1, characterized in that: The dynamic gain function is: ， in, Charging event bucket k Compared to the charging event bucket k -1 change in the number of events, and are weight adjustment parameters, A preset positive number.

3. The data matching method in charging facility verification according to claim 1, characterized in that: The charging event buckets corresponding to the start time of each charging order include: Add a time error to the start time of each charging order to obtain its start time range; For each charging order, at least one charging event bucket covering any point in its starting time range is used as its corresponding charging event bucket.

4. The data matching method in charging facility verification according to claim 1, characterized in that: For charging orders with missing start time, their start time is determined according to the maximum order duration and its end time; For charging orders with missing termination time, their termination time is determined according to the maximum order duration and its start time.

5. The data matching method in charging facility verification according to claim 4, characterized in that: For each charging order: in its corresponding charging event bucket, according to the target similarity S i Match the corresponding charging events, including: For each charging order: filter out the charging events whose power deviation ratio is greater than the threshold in the corresponding charging event bucket, and select the remaining charging events according to the target similarity. S i Match the corresponding charging event.

6. The data matching method in charging facility verification according to claim 4, characterized in that: Target Similarity S i The calculation formula is: ， in, There are four weights. When the start time or end time of the charging order is missing, are 0.3, 0.1, 0.1 and 0.5 respectively, otherwise, They are 0.3, 0.3, 0.3 and 0.1 respectively.

7. The data matching method in charging facility verification according to claim 1, characterized in that: Start time proximity S t The calculation formula is: ， Duration proximity S d The calculation formula is: ， Time interval overlap S o The calculation formula is: ， Battery Proximity S e The calculation formula is: ， in, and are the start time and end time of charging event i, W is the time length of the charging event bucket where charging event i is located, and are the start time and end time of charging order j respectively, d i is the duration of charging event i; for and The minimum value in for and The maximum value in ; is the power of charging event i, is the power of charging order j.

8. A data matching device for charging facility verification, characterized in that: include: An order acquisition module, used to acquire a number of charging orders of the charging facilities to be inspected through the operation system of the charging facilities; A first matching module is used to match the corresponding charging event bucket according to the start time of each charging order, and the multiple charging event buckets are obtained by dividing a number of charging events based on their own start time; The second matching module is used to match each charging order with the target similarity in the corresponding charging event bucket. S i Match the corresponding charging event, target similarity S i The start time proximity S t , duration proximity S d , Time interval overlap S o Proximity to power S e Perform weighted summation to obtain; The steps of dividing multiple charging event buckets include: The verification period is divided into multiple time periods at equal intervals, and multiple charging events with start times in the same time period are divided into the same charging event bucket; For charging event buckets whose number of charging events exceeds the threshold, the target strategy is used to further divide the multiple charging events contained in it into multiple new charging event buckets. The target strategy is: ， in, Charging event bucket k time range, C is the capacity threshold of the charging event bucket, Represents the charging event bucket k The storage capacity, Indicates the corresponding charging event bucket k The dynamic gain function is T min and T max Charging event buckets k The lower and upper limits of the time range, adg(x,a,b) is an adaptive particle function, which is used to x Constraints a and b between.

9. An electronic device, comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to run the computer program to execute the data matching method in charging facility certification according to any one of claims 1 to 7.

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