Method and system for confirming the metering performance of multi-mode fusion electric vehicle charging facilities

Abstract

The present invention provides a multi-mode fusion method and system for confirming the metering performance of electric vehicle charging facilities, including an online calculation link for charging facility operation errors, a classification processing link, and a metering performance confirmation link; the online calculation link for charging facility operation errors includes three sub-links: data acquisition and processing, model calculation of operation errors, and measurement uncertainty assessment of operation errors. The present invention adopts a multi-mode fusion metering technology solution of "online error calculation + classification sampling verification + metering performance confirmation", improves monitoring efficiency and realizes dynamic monitoring through online calculation, uses classification sampling verification to reduce on-site calibration workload and cost, and ensures the credibility of online calculation results. The metering performance confirmation link can promptly identify unqualified charging piles, prevent systemic risks, and realize economical, continuous monitoring and dynamic supervision of electricity metering operation errors of large-scale electric vehicle charging facilities.

Description

Technical Field

[0001] The present invention relates to the technical field of electric vehicle charging facility verification and measurement confirmation, and in particular to a method and system for confirming the measurement performance of electric vehicle charging facilities. Background Art

[0002] The increasing penetration rate of new energy electric vehicles in my country and the continued rise in the number of electric vehicles on the road are driving the development of electric vehicle charging infrastructure. The number of electric vehicle users is currently climbing, and the operational services of charging facilities are gaining increasing attention. The measurement accuracy of charging pile electricity trade, a core service indicator, directly determines the fairness and reliability of trade settlements and ultimately the healthy development of the electric vehicle industry. Furthermore, electric vehicle charging piles are now included in the catalog of mandatory measurement instruments, requiring regular calibration of operating charging piles.

[0003] The rapid growth in the scale of charging piles has brought huge challenges to the calibration work. The current calibration method, which mainly relies on on-site calibration, has problems such as low efficiency and high cost, and it is becoming increasingly difficult to meet the needs of comprehensive calibration of charging piles.

[0004] To this end, a large number of researchers have begun to explore efficient detection methods suitable for large-scale detection. There are mainly two technical routes:

[0005] The first is remote calibration equipment and technology for charging piles based on IoT technology, such as upgrading physical calibration equipment and installing remote metering modules;

[0006] The second is the charging pile error analysis and verification technology based on data-driven methods, such as the charging pile out-of-tolerance prediction method based on historical data, and the error evaluation method based on vehicle-pile interaction data.

[0007] Regarding the latter technical approach, Liu Wei et al. proposed an Advanced Measurement Infrastructure (AMI) data-driven method for assessing the state of metering errors in electric vehicle charging facilities (Electric Power Automation Equipment, 2022, Vol. 042, No. 010). They established a charging facility metering error model and used high-frequency charging data from the power company's AMI to solve the model, enabling state assessment of the metering errors of operating charging facilities. State Grid Hubei Electric Power Company proposed a method for aligning the amount of electricity in charging piles within a charging station and calculating metering errors (Chinese Invention No. CN115575884A). Using charging station operation data and transaction data from each charging pile, they established an energy conservation model for the metered electricity at the charging station and each charging pile, ultimately solving for the error parameters. In summary, current methods for evaluating the metering performance of electric vehicle charging facilities (mostly charging guns) rely primarily on periodic on-site calibration. While periodic on-site calibration offers high reliability, it is labor-intensive, costly, and inefficient. Furthermore, online monitoring is not possible, making it difficult to promptly identify charging facilities with substandard metering performance. However, existing online methods for calculating metering errors are limited by data quality, resulting in a significant risk of miscalculation. Furthermore, existing metering performance evaluation techniques cannot cover all sites, and no solutions are available for charging facilities that are not suitable for existing metering performance evaluation methods. Existing solutions primarily rely on a single technical approach. Although many literature and standards suggest that combining different methods to comprehensively assess charging pile errors is beneficial, a viable technical approach has yet to be identified. Summary of the Invention

[0008] The technical problem to be solved by this invention is to provide a multi-mode integrated method and system for confirming the metering performance of electric vehicle charging facilities. This method employs a multi-mode integrated metering technology solution combining "online error calculation + classified sampling verification + metering performance confirmation," combining the advantages of different modes. Online calculation significantly improves monitoring efficiency, while classified sampling / unit-by-unit verification significantly reduces the manual verification workload while ensuring the credibility of online calculation results. Furthermore, a feasible technical approach for utilizing online calculation results within the existing legal metrology framework is provided. This method achieves economical, continuous monitoring and dynamic supervision of operational errors in electricity metering for large-scale electric vehicle charging facilities.

[0009] In a first aspect, the present invention provides a method for confirming the metering performance of a multi-mode integrated electric vehicle charging facility, including an online calculation step of charging facility operation errors, a classification processing step, and a metering performance confirmation step;

[0010] The online calculation of charging facility operational errors includes: obtaining charging station master meter data and charging data of charging facilities within the charging station through an online platform (charging data of charging facilities is obtained with charging guns as the smallest unit); establishing an online calculation model for operational errors based on the law of conservation of energy, using the charging station master meter data as a standard to calculate the operational errors of each charging facility within the charging station; conducting on-site calibration of some charging facilities, and analyzing the calculation process of the operational errors of each charging facility based on the on-site calibration results, thereby accurately evaluating the calculation error uncertainty of the online error calculation model;

[0011] The classification and processing step includes: classifying and processing the charging facilities based on the evaluation results of the operating errors and uncertainties of each charging facility in the charging station obtained through online calculation, combined with the activity level, annual power consumption, and historical online evaluation conclusions of the charging station and charging facilities;

[0012] The metering performance confirmation link includes: confirming the metering performance of the charging facility based on the results of the online calculation link and the classification processing link of the charging facility operation error, and forming an online evaluation report on the metering performance of the charging facility.

[0013] Furthermore, the charging station master meter data and the charging data of the charging facilities in the charging station are collected, cleaned, analyzed, and stored by the online evaluation platform for charging facility metering performance, and then processed to prevent tampering and loss. The corresponding relationship between the charging station, master meter account number, transformer file and comprehensive rate is established and provided;

[0014] The charging station master meter data is the frozen data of voltage, current, power, power factor, and power consumption at 96 points per day of the charging station master meter;

[0015] The charging data of the charging facilities in the charging station must be at least 3 months of operation, with no less than m × 90 charging order data or more than 1 month of high-frequency charging process data, where m is the total number of charging facilities in the station, and the frequency of high-frequency data is no less than 1 minute / time;

[0016] If there is non-charging electricity load in the charging station, it will be metered separately.

[0017] Furthermore, the formula for establishing an online calculation model for operation error based on the law of conservation of energy is expressed as follows:

[0018]

[0019] Where:

[0020] E y ——The total power supply of the charging station;

[0021] m——the total number of charging facilities in the charging station;

[0022] E j ——Charging power of each charging facility;

[0023] η——Conversion efficiency of charging facilities, the conversion efficiency of AC charging facilities is 1;

[0024] γ j ——Operational errors of each charging facility;

[0025] E u - line loss;

[0026] E0 - the fixed loss within the charging station, including the power consumption of the display screen of the charging facility;

[0027] E in - The power consumption of other equipment in the charging station except the charging equipment;

[0028] By collecting charging data, a system of equations consisting of no less than m+2 equations is formed. Solving the system of equations can obtain the operating error γ of each charging facility. j , m is the total number of charging facilities in the station.

[0029] Furthermore, the calculation error uncertainty of the evaluation error online calculation model includes:

[0030] Determine the sources of uncertainty, including:

[0031] a) Uncertainty component u1 introduced by algorithm repeatability;

[0032] b) Uncertainty component u2 introduced by on-site verification;

[0033] c) The uncertainty component u3 introduced by the deviation between the on-site verification error value and the algorithm calculation error value;

[0034] The combined uncertainty u is obtained by combining the uncertainty components from different sources mentioned above. c :

[0035]

[0036] Assume the confidence probability P is 95%, the coverage factor is k=2, and the expanded uncertainty is U:

[0037] U=ku c Furthermore, the classification and processing of charging facilities are specifically as follows:

[0038] Category 1: The range of operating error γ and uncertainty U is |γ|≤2% and U≤2%. The process is to directly enter the metrological performance confirmation link;

[0039] For the second category, the ranges of the running error γ and the uncertainty U are 2% < |γ| ≤ 3% and U ≤ 3%, or |γ| ≤ 2% and 2% < U ≤ 3%. The treatment requires verification through on-site verification or sampling verification, and then enter the metrological performance confirmation process;

[0040] For the third category, the ranges of the running error γ and the uncertainty U are |γ| > 3% or U > 3%. The treatment is to conduct on-site verification for each unit, and then enter the metrological performance confirmation process;

[0041] For the fourth category, if the running error γ and the uncertainty U of the charging facilities are incalculable or not connected to the platform, the treatment is to conduct on-site verification for each unit, and then enter the metrological performance confirmation process.

[0042] Furthermore, the process of the sampling verification includes:

[0043] S1. Determine the batches of the charging facilities;

[0044] S2. Develop a sampling plan, select an appropriate Acceptable Quality Limit (AQL) and inspection level according to the actual situation, and determine the sample size for sampling inspection and reserve inspection; the sampling plan follows the random principle, and the sample serial numbers are generated by the random number table method, the random number dice method or the playing card method;

[0045] S3. Select the sites of the charging stations and the samples of the charging facilities for sampling; <​​​​​​​​​​​​​​​​​​​For the third category of charging facilities, if the on-site inspection is qualified and the measurement is confirmed as qualified, a verification certificate will be issued and the online evaluation report will show that it is qualified; if the on-site inspection is unqualified and the measurement is confirmed as unqualified, a verification result notice will be issued and the online evaluation report will show that it is unqualified;

[0053] For the fourth category of charging facilities, on-site inspection shall be carried out in accordance with JJG 1148 and JJG 1149. A inspection certificate shall be issued for those that pass the inspection, and a inspection result notice shall be issued for those that fail the inspection.

[0054] In a second aspect, the present invention provides a multi-mode integrated electric vehicle charging facility metering performance confirmation system for implementing the method described in the first aspect.

[0055] One or more technical solutions provided by the present invention have at least the following technical effects or advantages: a multi-mode integrated metering technology solution of "online error calculation + classified sampling verification + metering performance confirmation" is adopted, including three steps: online calculation of charging facility operation errors, classified processing, and metering performance confirmation; thus, the following effects are achieved:

[0056] 1. Leveraging online big data analysis and real-time calculations, this system identifies out-of-tolerance metering characteristics of electric vehicle charging facilities and dynamically monitors charging anomalies. This system promptly identifies substandard charging facilities, complements and improves current periodic verification, and prevents systemic risks. This reduces the workload of periodic verification and improves its efficiency.

[0057] 2. The introduction of classification concepts and sampling verification, on the one hand, reduces the risk of calculation results caused by data quality constraints of existing technologies, and on the other hand, solves the problem that existing technologies cannot cover all types of charging facilities, provides a practical and complete method for confirming the metering performance of charging facilities, balances the workload of on-site inspections and the control of unqualified risks, and improves supervision efficiency.

[0058] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are specifically listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0060] Figure 1 Schematic diagram of the framework of the system of the present invention;

[0061] Figure 2 This is a flowchart of the method in Example 1 of the present invention;

[0062] Figure 3This is a structural block diagram of the system in Example 2 of the present invention. DETAILED DESCRIPTION

[0063] The present invention provides a multi-mode integrated method for confirming the metering performance of electric vehicle charging facilities. This method utilizes a multi-mode integrated metering technology solution combining online error calculation, classified sampling verification, and metering performance confirmation. Combining the advantages of different modes, this method significantly improves monitoring efficiency through online calculation. Classified sampling and unit-by-unit verification significantly reduces the manual verification workload while ensuring the credibility of online calculation results. Furthermore, a practical and feasible technical approach for utilizing online calculation results within the existing legal metrology framework is provided. This approach enables economical, continuous monitoring, and dynamic oversight of operational errors in electricity metering for large-scale electric vehicle charging facilities.

[0064] The technical solution in the embodiment of the present invention has the following overall idea: adopting the multi-mode comprehensive metering technical solution of "online calculation of errors + classification sampling verification + metering performance confirmation", first, the online evaluation platform for metering performance of charging facilities cooperates with the charging station electricity consumption information collection system to provide the charging station total meter data, and the charging facility charging data provided by the charging facility operation service platform, and calculates the charging facility operation error online through big data modeling and analysis; secondly, based on the online calculation results and operation data, the charging facilities are classified, and corresponding metering performance confirmation strategies are adopted for different categories; finally, sampling verification and on-site calibration are carried out according to the classification results, and feedback and iteration are given to the online evaluation platform after metering performance confirmation, and an online performance evaluation report is output to realize the identification of metering performance deviations of charging facilities and dynamic supervision of charging anomalies. Among them, there are three key points:

[0065] 1. Multi-mode fusion technology: This includes three core steps: online error calculation, classified sampling verification, and measurement performance confirmation. The online calculation of charging facility operation errors is further divided into three parts: data acquisition and processing, model calculation of operation errors, and measurement uncertainty assessment of operation errors.

[0066] 2. Classification: Based on online calculation results and operational data, charging facilities are divided into four categories through online evaluation, and different verification and inspection strategies are determined for each category;

[0067] 3. Metrological performance confirmation: Different metrological performance confirmations are implemented for different categories of online evaluation, and corresponding online performance evaluation reports are output.

[0068] Example 1

[0069] like Figures 1 to 2As shown, this embodiment provides a method for confirming the metering performance of a multi-mode integrated electric vehicle charging facility, including an online calculation link of charging facility operation errors, a classification processing link, and a metering performance confirmation link.

[0070] The online calculation of charging facility operation error includes the following three sub-steps:

[0071] 1. Data Acquisition and Processing: The charging station master meter data and the charging data of the charging facilities within the charging station are acquired through the online platform. The charging station master meter data and the charging data of the charging facilities within the charging station are collected, cleaned, analyzed, and stored by the online evaluation platform for charging facility metering performance. The data is then processed to prevent tampering and loss, and the corresponding relationship between the charging station, master meter account number, transformer file, and comprehensive ratio is established before it is provided.

[0072] The charging station master meter data is the frozen data of voltage, current, power, power factor, and power consumption at 96 points per day of the charging station master meter;

[0073] The charging data of the charging facilities in the charging station is required to be that the charging facilities have been in operation for more than 3 months, with no less than m×90 charging order data or more than 1 month of high-frequency data of the charging process, where m is the total number of charging facilities in the station, and the frequency of the high-frequency data is not less than 1 minute / time.

[0074] If there is non-charging electricity load in the charging station, it will be metered separately.

[0075] 2. Model calculation: Based on the tree-like topology structure consisting of the master meter and sub-meters, and according to the characteristics of the data collected on the user side, the relationship between the master meter and sub-meters is explored. Based on the law of conservation of energy, an online calculation model for operating errors is established. Using the master meter data of the charging station as a standard, the operating errors of each charging facility in the charging station are calculated.

[0076] The online calculation model for operation error is established based on the law of conservation of energy: "Total power supply of charging station" = "the sum of actual power consumption of all charging facilities" + "line loss" + "fixed loss in the station" + "power consumption of other equipment in the station". The formula is shown in formula (7):

[0077]

[0078] Where:

[0079] E y ——The total power supply of the charging station;

[0080] m——the total number of charging facilities in the charging station;

[0081] E j ——Charging power of each charging facility;

[0082] η——Conversion efficiency of charging facilities, the conversion efficiency of AC charging facilities is 1;

[0083] γ j ——Operational errors of each charging facility;

[0084] E u - line loss;

[0085] E0 - the fixed loss within the charging station, including the power consumption of the display screen of the charging facility;

[0086] E in - The power consumption of other equipment in the charging station except the charging equipment;

[0087] By collecting charging data, a system of equations consisting of no less than m+2 equations is formed. Solving the system of equations can obtain the operating error γ of each charging facility. j , m is the total number of charging facilities in the station.

[0088] 3. Error measurement uncertainty assessment: Conduct on-site calibration of some charging facilities. Combined with the on-site calibration results, analyze the calculation process of the operating errors of each charging facility to accurately assess the calculation error uncertainty of the online error calculation model. The assessment of the calculation error uncertainty of the online error calculation model includes determining the source of uncertainty, which includes the following three sources:

[0089] a) Uncertainty component u1 introduced by algorithm repeatability

[0090] The uncertainty component introduced by the dispersion of the measurement results of the calibrated charging facility mainly includes the influence of quantization errors caused by clock bias, data fluctuation, and data truncation. The uncertainty component is evaluated using the Type A evaluation of measurement uncertainty [JJF 1001, 5.20].

[0091] b) Uncertainty component u2 introduced by on-site verification

[0092] On-site verification was completed according to the current verification procedures for charging facilities, and the selected charging facilities were verified twice. The uncertainty of the on-site verification results is mainly composed of the traceability to the standard, the number of digits of the charging facility indication, and the measurement repeatability. The uncertainty components were mainly evaluated using the Type B evaluation of measurement uncertainty [JJF 1001, 5.21].

[0093] c) Uncertainty component u3 introduced by the deviation between the on-site verification error value and the algorithm calculation error value

[0094] The algorithm ability is measured by the deviation level of the error value calculated using on-site verification results and algorithms. Based on the deviation statistical law, its uncertainty component is obtained, and the uncertainty is evaluated using the Type A evaluation method (i.e., Type A evaluation of measurement uncertainty [JJF 1001, 5.20]).

[0095] After synthesizing the uncertainty components from different sources as above, the combined uncertainty u can be obtained. c :

[0096]

[0097] Taking the confidence probability P = 95% and the coverage factor k = 2, the expanded uncertainty U can be obtained as follows:

[0098] U = ku c

[0099] The classification and processing link includes: based on the evaluation results of the operation errors and uncertainties of each charging facility in the charging station obtained through online calculation, combined with the activity, annual electricity consumption, and historical online evaluation conclusions of the charging station and charging facilities, the charging facilities are classified and processed; further, the specific classification and processing of the charging facilities are shown in Table 1:

[0100] [[ID=2,2]]Table 1 Online evaluation classification

[0101]

[0102] The first category: the ranges of the operation error γ and the uncertainty U are |γ| ≤ 2% and U ≤ 2%. Since the operation error and the error uncertainty are small and the qualified credibility is high, it can directly enter the metrological performance confirmation link. Therefore, the said processing is to directly enter the metrological performance confirmation link.

[0103] The second category, the ranges of the operation error γ and the uncertainty U are 2% < |γ| ≤ 3% and U ≤ 3%, or |γ| ≤ 2% and 2% < U ≤ 3%. Since the calculated operation error uncertainty is large, the said processing is to require assistance from on-site verification or sampling verification for verification and then enter the metrological performance confirmation link.

[0104] The third category, the ranges of the operation error γ and the uncertainty U are |γ| > 3% or U > 3%. Since there is a large non-conformity risk, the said processing is to conduct on-site verification for each unit for verification and then enter the metrological performance confirmation link.

[0105] The fourth category is charging facilities whose operating error γ and uncertainty U cannot be calculated or are not connected to the platform. Due to problems with the charging station / pile files, missing data, abnormal charging station loss or lack of connection to the online evaluation platform, there is a certain risk of failure. Therefore, the processing described above requires on-site calibration and verification of each unit before entering the measurement performance confirmation stage.

[0106] The sampling inspection process includes:

[0107] S1. Determine the batch of charging facilities;

[0108] S2. Develop a sampling plan, select the appropriate acceptance quality limit (AQL) and inspection level based on actual conditions, and determine the sample size for random inspection and standby inspection; the sampling plan follows the principle of randomness, and the sample numbers are generated using a random number table, random dice, or playing card method;

[0109] S3. Select charging stations and charging facilities for sampling;

[0110] S4. Conduct on-site verification and qualification assessment of the sampled charging facilities in accordance with JJG 1148 and JJG 1149, and enter the verification results into the online evaluation platform.

[0111] S5. Determine whether the test results of the charging facility samples are qualified;

[0112] S6. Determine the batch results of charging facilities.

[0113] The sampling plan for single sampling, inspection level S-4, and AQL 2.5 is shown in GB / T 2828.1. 20% (≥1) of the sampling sample size is selected as the reserve sample size.

[0114] Samples should be drawn randomly. Samples should be selected according to the simple random sampling method in GB / T 10111. Random sampling sample numbers can be generated using methods such as random number tables, random dice, and playing cards.

[0115] After selecting charging facility samples for random inspection, each sample (gun) shall be individually verified on-site in accordance with JJG 1148 and JJG 1149, and a qualification assessment shall be conducted. The metrological performance of the gun shall be confirmed based on the verification results. The allowable error limits for random on-site inspection of charging facilities shall meet the requirements of JJG 1148 and JJG 1149.

[0116] Batch statistics and qualification determination: Based on the on-site inspection results of the first sampling samples, the number of charging facility (gun) samples that do not meet the requirements of JJG 1148 and JJG1149 is d;

[0117] When d≤Ac, the batch is judged as qualified, but the charging facility (gun) samples that failed the on-site inspection are judged as unqualified;

[0118] When d≥rejection number Re, the batch is judged to be unqualified, the charging facility (gun) samples that pass the on-site inspection are judged to be qualified, and the charging facility samples (gun) samples that fail the on-site inspection are judged to be unqualified.

[0119] The metering performance confirmation link includes: confirming the metering performance of the charging facility based on the results of the online calculation link and the classification processing link of the charging facility operation error, and forming an online evaluation report on the metering performance of the charging facility.

[0120] The specific confirmation of the metering performance of the charging facilities is:

[0121] For the first category of charging facilities, the metering performance is confirmed to be qualified;

[0122] For the second type of charging facilities, after sampling verification, metrological performance confirmation is carried out. If the batch sampling verification is qualified, the metrological performance is confirmed as qualified for the batch; if the batch sampling verification is unqualified, the metrological performance is confirmed as unqualified for the batch; if the charging facilities within the batch pass the sampling verification, the metrological performance is confirmed as qualified for the charging facilities; if the charging facilities within the batch fail the sampling verification, the metrological performance is confirmed as unqualified for the charging facilities; the specific expression is shown in Table 2.

[0123] Table 2 Measurement confirmation and result expression after sampling verification of Class II charging facilities

[0124]

[0125] For the third category of charging facilities, if the on-site inspection is qualified and the measurement is confirmed as qualified, a verification certificate will be issued and the online evaluation report will show that it is qualified; if the on-site inspection is unqualified and the measurement is confirmed as unqualified, a verification result notice will be issued and the online evaluation report will show that it is unqualified;

[0126] For the fourth category of charging facilities, on-site inspection shall be carried out in accordance with JJG 1148 and JJG 1149. A inspection certificate shall be issued for those that pass the inspection, and a inspection result notice shall be issued for those that fail the inspection.

[0127] Example 2

[0128] Based on the same inventive concept, this application also provides a device corresponding to the method in Example 1, see Example 2 for details.

[0129] like Figure 3 As shown, this embodiment provides a multi-mode integrated electric vehicle charging facility metering performance confirmation system for implementing the method described in Example 1.

[0130] The confirmation system of this embodiment includes an online calculation module for charging facility operation errors, a classification processing module, and a metering performance confirmation module;

[0131] The charging facility operation error online calculation module is used to obtain the charging station master meter data and the charging data of the charging facilities within the charging station in real time through the online platform; establish an online operation error calculation model based on the principle of conservation of energy, and use the charging station master meter data as a standard to calculate the operation error of each charging facility within the charging station; conduct on-site calibration of some charging facilities, and analyze the calculation process of the operation error of each charging facility based on the on-site calibration results, so as to accurately evaluate the calculation error uncertainty of the online error calculation model;

[0132] The classification and processing module is used to classify and process the charging facilities in the charging station based on the evaluation results of the operating errors and uncertainties of the charging facilities obtained by online calculation;

[0133] The metering performance confirmation module is used to confirm the metering performance of the charging facility based on the results of the charging facility operation error online calculation module and the classification processing module, and form an online evaluation report on the metering performance of the charging facility.

[0134] Since the system described in Example 2 of the present invention is the device used to implement the method of Example 1 of the present invention, those skilled in the art will be able to understand the specific structure and variations of the device based on the method described in Example 1 of the present invention, and therefore will not be described in detail here. All devices used in the method of Example 1 of the present invention fall within the scope of protection of the present invention.

[0135] Although the specific embodiments of the present invention are described above, those skilled in the art should understand that the specific embodiments described are merely illustrative and are not intended to limit the scope of the present invention. Equivalent modifications and changes made by those skilled in the art in accordance with the spirit of the present invention should be included within the scope of protection of the claims of the present invention.

Claims

1. A method for confirming the metering performance of a multi-mode integrated electric vehicle charging facility, characterized by: It includes an online calculation link for the operation error of the charging facility, a classification and processing link, and a metering performance confirmation link; The online calculation link for the operation error of the charging facility includes: obtaining the total meter data of the charging station and the charging data of the charging facilities in the charging station in real time through an online platform; establishing an online calculation model for the operation error based on the law of conservation of energy, using the total meter data of the charging station as the standard device to calculate the operation error of each charging facility in the charging station; conducting on-site verification on some charging facilities, and combining the on-site verification results to analyze the calculation process of the operation error of each charging facility, so as to accurately evaluate the measurement uncertainty of the operation error obtained by the online calculation model; The classification and processing link includes: classifying and processing the charging facilities based on the evaluation results of the operation error and measurement uncertainty of each charging facility in the charging station obtained by online calculation; The metering performance confirmation link includes: conducting metering performance confirmation on the charging facilities according to the results of the online calculation link and the classification and processing link of the operation error of the charging facility, and forming an online evaluation report on the metering performance of the charging facility.

2. The method for confirming the metering performance of a multi-mode integrated electric vehicle charging facility according to claim 1 is characterized in that: The total meter data of the charging station and the charging data of the charging facilities in the charging station are collected, cleaned, analyzed, stored by the online evaluation platform for the metering performance of the charging facility, and then processed for anti-tampering and anti-loss, and the corresponding relationship between the charging station, the total meter account number, the transformer file, and the comprehensive magnification is established and provided; The total meter data of the charging station is the frozen data of the voltage, current, power, power factor, and electricity quantity at 96 points a day of the total meter of the charging station; The charging data of the charging facilities in the charging station requires that the charging facilities operate for more than 3 months, with no less than m×90 charging order data or high-frequency data of the charging process for more than 1 month, where m is the total number of charging facilities in the station, and the frequency of the high-frequency data is not less than 1 minute / time; If there is non-charging power load in the charging station, it is metered separately.

3. The method for confirming the metering performance of a multi-mode integrated electric vehicle charging facility according to claim 1 is characterized in that: The formula for establishing the online calculation model for the operation error based on the law of conservation of energy is expressed as follows: In the formula: E y ——The total power supply of the charging station; m——The total number of charging facilities in the charging station; E j ——Charging power of each charging facility; η——The conversion efficiency of the charging facility; γ j ——Operational errors of each charging facility; E u - line loss; E0——The in-station fixed loss of the charging station, including the electricity consumption of the display screen of the charging facility; E in - The power consumption of other equipment in the charging station except the charging equipment; By collecting charging data, a system of equations consisting of no less than m+2 equations is formed. Solving the system of equations can obtain the operating error γ of each charging facility. j , m is the total number of charging facilities in the station.

4. The method for confirming the metering performance of a multi-mode integrated electric vehicle charging facility according to claim 1 is characterized in that: The calculation error uncertainty for evaluating the error online calculation model includes: Judging the sources of uncertainty, and the sources of uncertainty include: a) The uncertainty component u1 introduced by the algorithm repeatability; b) The uncertainty component u2 introduced by on-site verification; c) The uncertainty component u3 introduced by the deviation between the on-site verification error value and the algorithm calculation error value; The combined uncertainty u is obtained by combining the uncertainty components from different sources mentioned above. c : Taking the confidence probability P as 95%, the coverage factor as k = 2, and the expanded uncertainty as U: U=ku c .

5. The method for confirming the metering performance of a multi-mode integrated electric vehicle charging facility according to claim 1 is characterized in that: The specific classification and processing of the charging facilities are as follows: The first category: The range of the operation error γ and the uncertainty U is |γ|≤2% and U≤2%, and the processing is to directly enter the metering performance confirmation link; The second category, the range of the operation error γ and the uncertainty U is 2%<|γ|≤3% and U≤3%, or |γ|≤2% and 2%<U≤3%, and the processing is to require assistance from on-site verification or sampling verification and inspection, and then enter the metering performance confirmation link; Category III: The range of operating error γ and uncertainty U is |γ|>3% or U>3%. The treatment is to conduct on-site verification of each unit and then enter the metrological performance confirmation stage; The fourth category is charging facilities whose operating error γ and uncertainty U are uncalculated or not connected to the platform. In this case, the processing requires on-site calibration and verification of each device before entering the measurement performance confirmation stage.

6. The method for confirming the metering performance of a multi-mode integrated electric vehicle charging facility according to claim 5 is characterized in that: The sampling inspection and verification process includes: S1. Determine the batch of charging facilities; S2. Develop a sampling plan, select the appropriate acceptance quality limit (AQL) and inspection level based on actual conditions, and determine the sample size for random inspection and standby inspection; the sampling plan follows the principle of randomness, and the sample numbers are generated using a random number table, random dice, or playing card method; S3. Select charging stations and charging facilities for sampling; S4. Conduct on-site verification and qualification assessment of the sampled charging facilities in accordance with JJG 1148 and JJG 1149, and enter the verification results into the online evaluation platform. S5. Determine whether the test results of the charging facility samples are qualified; S6. Determine the batch results of charging facilities.

7. The method for confirming the metering performance of a multi-mode integrated electric vehicle charging facility according to claim 5 is characterized in that: In the measurement performance confirmation phase, the measurement performance confirmation of the charging facility is specifically: For the first category of charging facilities, the metering performance is confirmed to be qualified; For the second category of charging facilities, after sampling verification, metrological performance confirmation shall be carried out. If the batch sampling verification is qualified, the metrological performance shall be confirmed as qualified; if the batch sampling verification is unqualified, the metrological performance shall be confirmed as unqualified; if the charging facilities within the batch pass the sampling verification, the metrological performance shall be confirmed as qualified; if the charging facilities within the batch fail the sampling verification, the metrological performance shall be confirmed as unqualified; For the third category of charging facilities, if the on-site inspection is qualified and the measurement is confirmed as qualified, a verification certificate will be issued and the online evaluation report will show that it is qualified; if the on-site inspection is unqualified and the measurement is confirmed as unqualified, a verification result notice will be issued and the online evaluation report will show that it is unqualified; For the fourth category of charging facilities, on-site inspection shall be carried out in accordance with JJG 1148 and JJG 1149. A inspection certificate shall be issued for those that pass the inspection, and a inspection result notice shall be issued for those that fail the inspection.

8. A multi-mode integrated electric vehicle charging facility metering performance confirmation system, characterized by: Used to implement the method according to any one of claims 1 to 7.

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