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

Abstract

The invention relates to a data matching method and device in charging facility verification and electronic equipment, and the method comprises the steps: obtaining a plurality of charging orders of a to-be-verified charging facility through an operation system of the charging facility; matching corresponding charging event buckets according to the starting time of each charging order, wherein the plurality of charging event buckets are obtained by dividing a plurality of charging events based on own starting time; and for each charging order, the charging event corresponding to the charging order is matched in the charging event bucket corresponding to the charging order according to the target similarity, and the target similarity is obtained by performing weighted summation on the starting time proximity, the duration proximity, the time interval overlapping degree and the electric quantity proximity. Compared with a matching mode of traversing all charging events, the method has the technical effect of higher efficiency. The problem of low data matching efficiency of a data matching method in charging facility verification at present is solved.

Description

Technical Field

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

[0002] In the online measurement and verification of charging facilities, the charging process data can be measured separately by adding an independent remote measurement and verification module. After the charging pile remote verification platform (referred to as the verification platform) obtains the complete charging event data through the remote measurement and verification module, the charging event data is matched and compared with the charging order data of the charging pile operator management system (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 the verification of charging facilities is mainly based on the start and end time of the data and uses the method of traversing all the charging data for data matching. First, because it needs to traverse all the charging data, the data matching efficiency is low; secondly, when the start time or end time of the data is lost, data matching cannot be performed or the matching accuracy is significantly reduced.

[0003] There is currently no effective solution to the problem of low data matching efficiency in the current data matching methods used in charging facility verification. Summary of the invention

[0004] The present invention provides a data matching method, device and electronic device for charging facility verification to solve the problem of low data matching efficiency of the current data matching method for charging facility verification.

[0005] In a first aspect, the present invention provides a data matching method for charging facility verification, which includes: 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 powerS e Perform weighted summation to obtain .

[0006] In a second aspect, the present invention provides a data matching device for charging facility verification, comprising: 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 .

[0007] In a third aspect, the present invention provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the data matching method in the charging facility verification described in the first aspect.

[0008] Compared with the related art, the data matching method in the charging facility verification provided by the present invention first divides a number of charging events into a plurality of charging event buckets, and when performing data matching, preferentially matches the charging event bucket corresponding to the charging order, and then continues to match the corresponding charging events in the charging event bucket, which has a more efficient technical effect compared to the matching method of traversing all charging events. The problem of low data matching efficiency of the current data matching method in the charging facility verification is solved.

[0009] At the same time, when matching charging events and charging orders, 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 to achieve more accurate matching.

[0010] 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 readily apparent. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 is a flow chart of the data matching method in the charging facility verification provided in this embodiment; Figure 2 It is an architectural diagram of the data matching device in the charging facility verification provided in this embodiment. DETAILED DESCRIPTION

[0012] In order to more clearly understand the purpose, technical solutions and advantages of the present application, the present application is described and illustrated below in conjunction with the accompanying drawings and embodiments.

[0013] Unless otherwise defined, the technical terms or scientific terms involved in this application shall have the general meaning understood by people with general skills in the technical field to which this application belongs. The words "one", "a", "the", "these" and the like in this application do not indicate a quantitative limitation, and they may be singular or plural. The terms "include", "comprise", "have" and any variants thereof involved in this application are intended to cover non-exclusive inclusions; for example, a process, method and system, product or device comprising 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 to these processes, methods, products or devices. The words "connect", "connected", "coupled" and the like involved in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The "multiple" involved in this application refers to two or more. "And / or" describes the association relationship of associated objects, indicating that there may be three relationships, for example, "A and / or B" may mean: A exists alone, A and B exist at the same time, and B exists alone. Generally, the character " / " indicates that the objects associated with each other are in an "or" relationship. The terms "first", "second", "third", etc. in this application are only used to distinguish similar objects and do not represent a specific ordering of the objects.

[0014] In this embodiment, a data matching method for charging facility verification is provided. Figure 1 is a flow chart of the data matching method in the charging facility verification provided in this embodiment. Figure 1 As shown, the process includes: step S110, step S120 and step S130.

[0015] Step S110, obtaining a plurality of charging orders of the charging facility to be inspected through the operation system of the charging facility. In this embodiment, the charging facility is a plurality of charging piles.

[0016] When it is necessary to calibrate the charging facility, all charging orders within a calibration cycle are obtained from the operating system of the charging facility. Each charging order should include information such as the start time, end time, and power of the order. However, in some cases, the charging order may be missing the start time or the end time. For such charging events, how this embodiment handles them will be described in detail later. After obtaining the charging order, it is necessary to match these charging orders with the charging events. The data of the charging events are obtained by the remote metering and calibration module by measuring the charging facilities to be calibrated. Each charging event will also include information such as the start time, end time, and power of the event. It should be noted that the data matching method in the charging facility calibration of this embodiment is applied to the remote calibration platform of the charging facility, and the remote metering and calibration module is a local module within the platform, so the charging event generally does not have a situation where the start time or end time is lost. Among them, the charging event i can be expressed as a quaternary group: . , , and They are start time, end time, duration and power. At the same time, the maximum effective charging time (maximum order duration) of the charging facility to be inspected can also be set according to the actual situation. d max and minimum effective charging time (minimum order duration) d min .

[0017] Step S120, matching the corresponding charging event bucket according to the start time of each charging order, and the plurality of charging event buckets are obtained by dividing a plurality of charging events based on their own start times.

[0018] In the traditional data matching method, for each charging order, all charging events are traversed to match the corresponding charging event, but this method is inefficient. In this embodiment, for many charging events, they are pre-divided according to the start time and stored in different charging event buckets, so that each charging event bucket contains multiple charging events with the start time in the same time period.

[0019] Specifically, the steps of dividing multiple charging event buckets include: The calibration 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.

[0020] 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:

[0021] in, T ( k ) is the charging event bucket k time range, C is the capacity threshold of the charging event bucket, K ( k ) indicates the charging event bucket k The storage capacity, weight ( k ) 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, Δ K ( k ) is the charging event bucket k Compared to the charging event bucket k -1 change in the number of events, and are weight adjustment parameters, is a preset positive number used to determine whether the number of events has changed significantly. ,but weight ( k ) takes other values ​​(usually 1 or a constant), indicating that when the data change is not significant, there is no need to adjust the time range of the bucket. The change in the number of events can be the absolute value of the change in the number of events or the ratio.

[0022] The service life of a charging pile is usually about 10 years, so the time range for storing charging event data is also set to 10 years. To this end, first establish a first-level time index, and classify the charging event into the corresponding year, month, and day according to the charging start time. When the calibration cycle is one day, it can be divided into each 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:

[0023] in, B k Represents charging event bucket k , k is the index of the charging event bucket, represents the start time of charging event i, W The length of time for the charging event bucket, such as one hour.

[0024] Through the above steps, multiple charging event buckets are initially obtained. Taking into account that there are peak and trough periods of 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 the preset threshold, thereby reducing the pressure of subsequent charging order queries. This embodiment adopts a target strategy to re-divide the charging events in the charging event bucket where the number of charging events exceeds the threshold. The target strategy is essentially an adaptive particle bucketing strategy, and each charging event that needs to be stored is treated as a particle.

[0025] As described above, the division of charging event buckets is described. After the charging event buckets are divided, the corresponding charging event buckets can be matched for each charging order. Matching the corresponding charging event buckets according to the start time of each charging order specifically includes: adding 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 start time range is used as its corresponding charging event bucket.

[0026] Considering the data asynchrony between charging orders and charging events, even if the charging orders and charging events are corresponding, there may be deviations between their start time or end time. 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 12:00-13:00, and the time range of charging event bucket 6 is 13:00-14:00, if the starting time range of a charging order is between 12:55 and 13:03, then charging event buckets 5 and 6 both cover part of the starting time range of the charging order, and charging event buckets 5 and 6 are both used as the charging event buckets corresponding to the charging order.

[0027] Step S130: 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 .

[0028] In this embodiment, the case where the start time or end time of the charging order is lost is also considered. For a charging order whose start time is lost, its start time is determined according to the maximum order duration and its end time; for a charging order whose end time is lost, 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 inspected. d max For charging orders whose start time is missing, the start time can be obtained by subtracting the maximum order duration from its end time. For charging orders whose termination time is missing, its termination time can be obtained by adding its start time to the maximum order duration. .

[0029] In 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 lost, although the above steps can be used to calculate its start time, it may cause a greater error, that is, matching an inappropriate charging event bucket. Therefore, in this embodiment, for each charging order, the charging event bucket corresponding to it is matched according to the target similarity. S i Matching the corresponding charging events specifically includes: for each charging order: filtering out the charging events whose power deviation ratio is greater than the threshold in the corresponding charging event bucket, and matching the remaining charging events according to the target similarity S i Match the corresponding charging event.

[0030] Among them, the calculation formula of the power deviation ratio is: , is the power of charging event i, 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 (for example, 5%), it is considered that the charging event and the charging order are obviously mismatched, and there is no need to further calculate the target similarity between the two, which simplifies the matching process.

[0031] Correspondingly, in other embodiments, charging event buckets can also be used as basic units to consider whether to filter out. When the power deviation ratios of all charging events in a charging event bucket and the charging order to be matched are greater than a threshold, the charging event bucket is filtered out; otherwise, the charging event bucket is retained, and the target similarity between each charging event in the bucket and the charging order to be matched is subsequently calculated.

[0032] For the charging events that have not been screened out, continue to calculate their target similarity with the charging orders to be matched. S i The calculation formula is:

[0033] in, , , and There 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 They are 0.3, 0.3, 0.3 and 0.1 respectively.

[0034] In different situations, the weight settings are different. When the start and end times of the charging order are complete, more emphasis is placed on the time overlap. When the start and end times of the charging order are unilaterally missing, more emphasis is placed on the electricity consumption overlap, because the start and end times of the charging order have a larger error at this time.

[0035] Furthermore, the start time proximity S t The calculation formula is:

[0036] Duration proximity S d The calculation formula is:

[0037] Time interval overlap S o The calculation formula is:

[0038] Battery Proximity S e The calculation formula is:

[0039] 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.

[0040] For each charging order to be matched, the charging event with the highest similarity to its target is selected as the corresponding charging event.

[0041] As described above, the data matching method for charging facility verification provided by the present invention is described through a complete embodiment.

[0042] From the above description, it can be seen that the data matching method first divides a number of charging events into multiple charging event buckets. When performing data matching, the charging event bucket corresponding to the charging order is matched first, and then the corresponding charging events are matched in the charging event bucket. Compared with the matching method of traversing all charging events, it has a more efficient technical effect. The problem of low data matching efficiency of the current data matching method in the verification of charging facilities is solved.

[0043] At the same time, when matching charging events and charging orders, the start time proximity between the two is calculated S t , duration proximity S d , Time interval overlap S o Proximity to power S e , measuring the target similarity between the two from multiple dimensions can achieve more accurate matching. The reason is that there may be minute-level deviations between charging orders and charging events, and there may be multiple charging orders (multiple charging piles) with similar start and end times in the same time period. It is impossible to accurately match charging events and charging orders based on the start and end times alone. For example, the charging events stored in the case are: Event 1: 10:02-10:35, charging 28kWh (user A actually charges); Event 2: 10:00-10:38, charging 35kWh (user B actually charges). Now there is one charging order that needs to be matched: appointment 10:00-10:40, expected charging 25kWh (user A, family car, low power demand). If only the start and end time factors are considered, it is obvious that event 2 meets the conditions more. After using 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.

[0044] In addition, charging events are preferentially divided into different charging event buckets according to time periods. In order to avoid serious unevenness in the number of events in different charging event buckets, the target strategy is continued to be used to further divide the charging event buckets whose event numbers exceed the threshold. Ultimately, the number of events in each charging event bucket is relatively balanced and does not exceed the threshold.

[0045] Finally, in the case where the charging order loses its start time or end time, the maximum order duration is used to determine the missing end time from the known start time or to determine the missing start time from the known end time. Considering that this method may introduce errors and thus match inappropriate charging event buckets, when calculating the target similarity between charging orders and charging events, the power deviation ratio between the two is calculated first, and only the target similarity between charging orders and charging events with a power deviation ratio less than the threshold is calculated, thereby avoiding some meaningless target similarity calculations and improving overall calculation efficiency.

[0046] In this embodiment, a data matching device for charging facility verification is also provided, which is used to implement the data matching method for charging facility verification in this embodiment, which has been described and will not be repeated. The terms "module", "unit", "subunit", etc. used below can implement a combination of software and / or hardware for predetermined functions. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0047] Figure 2 is a schematic diagram of the data matching device in the charging facility verification provided in this embodiment. Figure 2 The data matching device for charging facility verification provided in this embodiment includes: an order acquisition module, a first matching module and a second matching module.

[0048] Order acquisition module: used to obtain several charging orders of the charging facilities to be inspected through the operation system of the charging facilities; The 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 So Proximity to power S e Perform weighted summation to obtain .

[0049] It should be noted that the above modules can be functional modules or program modules, and can be implemented by software or hardware. For modules implemented by hardware, the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0050] In this embodiment, an electronic device is also provided, including a memory and a processor, wherein 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 the charging facility verification in this embodiment.

[0051] It should be understood that the specific embodiments described herein are only used to explain the application, rather than to limit it. Based on the embodiments provided in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the protection scope of this application.

[0052] Obviously, the drawings are only some examples or embodiments of the present application. For ordinary technicians in the field, the present application can also be applied to other similar situations based on these drawings without creative work. In addition, it is understandable that although the work done in this development process may be complicated and lengthy, for ordinary technicians in the field, certain changes in design, manufacturing or production based on the technical content disclosed in this application are only conventional technical means and should not be regarded as insufficient content disclosed in this 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 .

2. The data matching method in charging facility verification according to claim 1, characterized in that: 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, T ( k ) is the charging event bucket k time range, C is the capacity threshold of the charging event bucket, K ( k ) indicates the charging event bucket k The storage capacity, weight ( k ) 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.

3. The data matching method in charging facility verification according to claim 2, characterized in that: The dynamic gain function is: ， Among them, Δ K ( k ) is the 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.

4. 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.

5. 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.

6. The data matching method in charging facility verification according to claim 5, 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.

7. The data matching method in charging facility verification according to claim 5, characterized in that: Target Similarity S i The calculation formula is: ， in, , , and There 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 They are 0.3, 0.3, 0.3 and 0.1 respectively.

8. 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.

9. 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 .

10. 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 8.

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