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

Abstract

The invention provides a method and a system for confirming metering performance of a multi-mode fusion electric vehicle charging facility. The method comprises a charging facility operation error online calculation link, a classification processing link and a metering performance confirmation link, the charging facility operation error on-line calculation link comprises three sub-links of data acquisition and processing, operation error calculation by a model, and operation error measurement uncertainty evaluation. According to the method, a multi-mode fusion metering technical scheme of error online calculation, classified sampling check and metering performance confirmation is adopted, the monitoring efficiency is improved through online calculation, dynamic monitoring is achieved, the field verification workload and cost are reduced through classified sampling check, and meanwhile the credibility of an online calculation result is ensured. And in the metering performance confirmation link, unqualified charging piles can be identified in time, systematic risks are prevented, and economical and continuous monitoring and dynamic supervision of electric energy metering operation errors of large-scale electric vehicle charging facilities are realized.

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 an electric vehicle charging facility. Background Art

[0002] The penetration rate of new energy electric vehicles in my country has gradually increased, and the number of electric vehicles has continued to increase, which has also promoted the construction of electric vehicle charging facilities. By the end of September 2024, the number of public charging piles for electric vehicles in China will increase to 3.329 million, including 1.501 million DC charging piles and 1.827 million AC charging piles, with a pile-to-vehicle increment ratio of 1:2.6. At present, the number of electric vehicle users continues to rise, and the attention paid to the operation services of charging facilities is increasing. Among them, the measurement accuracy of charging pile electricity trade, as a core service indicator, directly determines the fairness and reliability of trade settlement, and ultimately determines the healthy development of the electric vehicle industry. In addition, electric vehicle charging piles are currently included in the catalog of compulsory verification measuring instruments, requiring regular verification of charging piles in operation.

[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 has become 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, mainly in the following two technical routes:

[0005] The first is the remote calibration equipment and technology of charging piles based on the Internet of Things technology, such as upgrading physical calibration equipment and adding 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] For the latter technical route, Liu Wei et al. proposed an advanced measurement system (AMI) data-driven method for evaluating the state of metering operation errors of electric vehicle charging facilities (Electric Power Automation Equipment, 2022, Vol. 042, No. 010), established a charging facility metering operation error model, and used the high-frequency charging data from the power company's AMI to solve the model, realizing the state evaluation of the metering operation errors of the operating charging facilities. State Grid Hubei Electric Power Company proposed a method for aligning the power of charging piles in a charging station and calculating the metering error (China Invention No. CN115575884A), using the charging station operation data and the transaction data of each charging pile to establish an energy conservation model for the metering power of the charging station and each charging pile, and finally solve the error parameters. In summary, the current metering performance evaluation method of electric vehicle charging facilities (mostly charging guns at present) mainly relies on periodic on-site calibration, which has high reliability, but the calibration task is heavy, the cost is high, the efficiency is low, and online monitoring cannot be achieved, making it difficult to timely detect charging facilities with unqualified metering performance. However, the existing online calculation method of metering error is restricted by data quality, and the calculation results have a high risk of misjudgment. In addition, the existing technical metering performance evaluation cannot cover all sites, and no corresponding solution is given for charging facilities that are not applicable to the existing metering performance evaluation method. The existing solution mainly relies on a single technical means. Although many documents and specifications have proposed that it is beneficial to make a comprehensive judgment on the error of charging piles by combining different means, no feasible technical route has been seen yet. Summary of the invention

[0008] The technical problem to be solved by the present invention is to provide a multi-mode integrated electric vehicle charging facility metering performance confirmation method and system, which adopts a multi-mode comprehensive metering technical solution of "online error calculation + classified sampling verification + metering performance confirmation", combines the advantages of different modes, and greatly improves the monitoring efficiency through online calculation. The classified sampling / unit-by-unit verification method not only greatly reduces the workload of manual verification, but also effectively guarantees the credibility of the online calculation results. And under the framework of the existing legal measurement, a practical technical route is given for the use of online calculation results. The economical, continuous monitoring and dynamic supervision of the operation errors of electric energy metering of large-scale electric vehicle charging facilities are realized.

[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 link of charging facility operation errors, a classification processing link, and a metering performance confirmation link;

[0010] The online calculation link of the charging facility operation error includes: obtaining the charging station master table data and the charging data of the charging facilities in the charging station through the online platform (the charging data of the charging facilities is obtained with the charging gun as the smallest unit); establishing an online calculation model of the operation error according to the law of conservation of energy, using the charging station master table data as a standard, and calculating the operation error of each charging facility in the charging station; conducting on-site calibration of some charging facilities, and analyzing the calculation process of the operation error of each charging facility in combination with the on-site calibration results, so as to accurately evaluate the calculation error uncertainty of the error online 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 the charging facilities in the charging station obtained through online calculation, combined with the activity of the charging station and the charging facilities, the annual power consumption and the historical online evaluation conclusions;

[0012] The metering performance confirmation link includes: confirming the metering performance of the charging facilities according to 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 facilities.

[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 the metering performance of charging facilities, and then processed for tamper-proof and loss-proof, and the corresponding relationship between the charging station, master meter account number, transformer file, and comprehensive multiple is established before being provided;

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

[0015] The charging data of the charging facilities in the charging station requires 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 high-frequency data is not 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——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 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 online calculation model of the evaluation error 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 field 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] Take the confidence probability P as 95%, the coverage factor as k=2, and the expanded uncertainty as U:

[0037] U=ku c #(6) Further, 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%, and the processing is to directly enter the measurement performance confirmation link;

[0039] For the second category, the ranges of the operating 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 entering the metrological performance confirmation process;

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

[0041] For the fourth category, if the operating 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 one by one, and then enter the metrological performance confirmation process.

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

[0043] S1. Determine the batch 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 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 site of the charging station and the sample of the charging facilities for sampling;

[0046] S4. Conduct on-site verification for each of the sampled charging facility samples one by one according to JJG 1148 and JJG 1149 and make a conformity judgment, and at the same time enter the verification results into the online evaluation platform;

[0047] S5. Judge whether the verification results of the sampled charging facility samples are qualified;

[0048] S6. Judge the batch results of the charging facilities.

[0049] Furthermore, in the metrological performance confirmation process, the specific metrological performance confirmation of the charging facilities is as follows:

[0050] For the charging facilities of the first category, the metrological performance is confirmed as qualified;

[0051] For the charging facilities of the second category, after sampling verification, the metrological performance is confirmed. If the batch sampling verification is qualified, the metrological performance is confirmed as batch qualified; if the batch sampling verification is unqualified, the metrological performance is confirmed as batch unqualified; if the sampling verification of the charging facilities within the batch is qualified, the metrological performance is confirmed as the charging facility qualified; if the sampling verification of the charging facilities within the batch is unqualified, the metrological performance is confirmed as the charging facility unqualified;

[0052] For the third category of charging facilities, if the on-site verification 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 verification 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 calibration shall be carried out in accordance with JJG 1148 and JJG 1149. A calibration certificate shall be issued for those who pass the calibration, and a calibration result notice shall be issued for those who fail the calibration.

[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: adopting a multi-mode comprehensive metering technical solution of "online error calculation + classification sampling verification + metering performance confirmation", including three links of online calculation of charging facility operation errors, classification processing and metering performance confirmation; thus having the following effects:

[0056] 1. Utilize online analysis and real-time calculation of big data to identify out-of-tolerance measurement characteristics of electric vehicle charging facilities and dynamically monitor abnormal charging. Timely identify unqualified charging facilities, improve and supplement the current periodic verification, and prevent systemic risks. Reduce the workload of periodic verification and improve the efficiency of verification.

[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 various types of charging facilities, and provides a practical and complete method for confirming the metering performance of charging facilities, balancing the workload of on-site inspections and the control of unqualified risks, and improving regulatory 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 according to 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 listed below. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0060] Figure 1 It is a schematic diagram of the framework of the system of the present invention;

[0061] Figure 2 is a flow chart of the method in Embodiment 1 of the present invention;

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

[0063] The embodiment of the present invention provides a method for confirming the metering performance of electric vehicle charging facilities with multi-mode integration, adopts a multi-mode comprehensive metering technical solution of "online error calculation + classified sampling verification + metering performance confirmation", combines the advantages of different modes, greatly improves the monitoring efficiency through online calculation, and greatly reduces the workload of manual verification through classified sampling / unit-by-unit verification, while effectively ensuring the credibility of online calculation results. In addition, a practical technical route is given for the use of online calculation results under the framework of existing legal measurement. The economical, continuous monitoring and dynamic supervision of the operation errors of electric energy metering of large-scale electric vehicle charging facilities are realized.

[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 error calculation + classified 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 total meter data of the charging station and the charging data of the charging facilities provided by the charging facility operation service platform. Through big data modeling and analysis, the operation error of the charging facilities is calculated online; 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 the following three key points:

[0065] 1. Multi-mode fusion technology: including three core links: online error calculation, classification sampling verification and measurement performance confirmation. Among them, the online calculation link of charging facility operation error is divided into three parts, including data acquisition and processing, model calculation of operation error, and measurement uncertainty assessment of operation error;

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

[0067] 3. Metrology performance confirmation: Different metrology performance confirmations are implemented for different categories of online evaluation, and the corresponding performance online evaluation report is output.

[0068] Embodiment 1

[0069] like Figure 1 to Figure 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 link of the charging facility operation error includes the following three sub-links:

[0071] 1. Data acquisition and processing: The charging station master meter data and the charging data of the charging facilities in the charging station are acquired through the online platform; 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 tamper-proof and loss-proof processing is performed, and the corresponding relationship between the charging station, master meter account number, transformer file and comprehensive multiple is established before it is provided;

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

[0073] The charging data of the charging facilities in the charging station is required to be 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 topology structure composed of the master table and sub-tables, according to the characteristics of the data collected on the user side, the relationship between the master table and the sub-tables is explored, and an online calculation model of the operation error is established according to the law of conservation of energy. The master table data of the charging station is used as a standard to calculate the operation error of each charging facility in the charging station;

[0076] The online calculation model of operation error is established based on the law of conservation of energy: "Total power supply of charging station" = "Sum of actual power consumption of all charging facilities" + "Line loss" + "Fixed loss in station" + "Power consumption of other equipment in station", and 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——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 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, and analyze the calculation process of the operating errors of each charging facility in combination with the on-site calibration results, so as to accurately assess the calculation error uncertainty of the online error calculation model; the calculation error uncertainty of the online error calculation model includes the source of the judgment uncertainty, and the sources of uncertainty include the following three types:

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

[0090] That is, the uncertainty component introduced by the dispersion of the measurement results of the calibrated charging facilities, mainly including the influence of quantization errors caused by clock deviation, 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] The on-site verification is completed according to the current verification procedures for charging facilities, and the selected charging facilities are verified twice; the uncertainty of the on-site verification results is mainly composed of the traceability to the standard, the number of indication digits of the charging facility and the measurement repeatability, and the uncertainty components are mainly evaluated using the Type B evaluation of measurement uncertainty [JJF 1001, 5.21];

[0093] c) The uncertainty component u3 introduced by the deviation between the field 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 components are 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 the above different sources, 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 #(9)

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

[0100] 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 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 processing is to require assistance from on-site verification or sampling verification for inspection, 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 high risk of non-conformity, the processing is to conduct on-site verification for each unit for inspection, 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 losses or lack of access to the online evaluation platform, there is a certain risk of failure. Therefore, the processing described requires on-site calibration and verification of each unit before entering the measurement performance confirmation stage.

[0106] The sampling verification 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 according to the actual situation, and determine the sample size for random inspection and standby inspection; the sampling plan follows the principle of randomness, and the sample number is generated by the random number table method, random number dice method or playing card method;

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

[0110] S4. The sampled charging facilities are tested on site one by one in accordance with JJG 1148 and JJG 1149, and their eligibility is determined. The test results are entered 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] The sampling should follow the random principle. The sample should be selected according to the simple random sampling method in GB / T 10111. The sample number of random sampling can be generated by random number table method, random number dice method, playing card method, etc.

[0115] After selecting the charging facility sampling samples, the samples (guns) shall be inspected on site one by one in accordance with JJG 1148 and JJG 1149, and the qualification shall be determined. The metrological performance of the gun shall be confirmed based on the inspection results. The allowable error limit of the sampling on-site inspection of charging facilities shall meet the requirements of JJG 1148 and JJG 1149.

[0116] Batch statistics and qualification determination: According to the on-site inspection results of the first sampling samples, the number of charging facilities (guns) 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 verification 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 facilities according to 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 facilities.

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

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

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

[0123] Table 2 Measurement confirmation and result expression after sampling verification of the second type of charging facilities

[0124]

[0125] For the third category of charging facilities, if the on-site verification 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 verification 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 calibration shall be carried out in accordance with JJG 1148 and JJG 1149. A calibration certificate shall be issued for those who pass the calibration, and a calibration result notice shall be issued for those who fail the calibration.

[0127] Embodiment 2

[0128] Based on the same inventive concept, the present 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, which is used to implement 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 table data and the charging data of the charging facilities in the charging station in real time through the online platform; establish an online calculation model of the operation error based on the principle of conservation of energy, use the charging station master table data as a standard, and calculate the operation error of each charging facility in the charging station; conduct on-site calibration of some charging facilities, and analyze the calculation process of the operation error of each charging facility in combination with the on-site calibration results, so as to accurately evaluate the calculation error uncertainty of the error online calculation model;

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

[0133] The metering performance confirmation module is used to confirm the metering performance of the charging facility according to 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 introduced in the second embodiment of the present invention is a device used to implement the method of the first embodiment of the present invention, those skilled in the art can understand the specific structure and deformation of the device based on the method introduced in the first embodiment of the present invention, so it is not described here in detail. All devices used in the method of the first embodiment of the present invention belong to the scope of protection of the present invention.

[0135] Although the specific implementation modes of the present invention are described above, those skilled in the art should understand that the specific implementation modes described are only 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 in 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 in that: It includes an online calculation link for the operation error of the charging facility, a classification and processing link, and a metrological performance confirmation link; The online calculation link for the operation error of the charging facility includes: obtaining the total station 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 station meter data of the charging station as the standard device to calculate the operation errors 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 errors of each charging facility, so as to accurately evaluate the measurement uncertainty of the operation errors 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 errors and measurement uncertainties of each charging facility in the charging station obtained by online calculation; The metrological performance confirmation link includes: conducting metrological performance confirmation on the charging facilities according to the results of the online calculation link and the classification and processing link of the operation errors of the charging facilities, and forming an online evaluation report on the metrological performance of the charging facilities.

2. The method for confirming the metering performance of a multi-mode fusion electric vehicle charging facility according to claim 1 is characterized in that: The total station 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 metrological performance of the charging facilities, then anti-tampering and anti-loss processing are carried out, and the corresponding relationship between the charging station, the total meter account number, the transformer file, and the comprehensive multiplication factor is established and provided; The total station meter data of the charging station is the frozen data of the voltage, current, power, power factor, and electricity quantity at 96 points in a day of the total station meter of the charging station; For the charging data of the charging facilities in the charging station, it is required 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 a non-charging electrical load in the charging station, it shall be separately metered.

3. The method for confirming the metering performance of a multi-mode fusion 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 internal 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 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 fusion electric vehicle charging facility according to claim 1 is characterized in that: The calculation error uncertainty of the evaluation 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 #(3)。 5. The method for confirming the metering performance of a multi-mode fusion 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 ranges of the operation error γ and the uncertainty U are |γ|≤2% and U≤2%, and the processing is to directly enter the metrological performance confirmation link; 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%, and the processing is to require on-site verification or sampling verification for verification, and then enter the metrological performance confirmation link; The third category, the range of operating error γ and uncertainty U is |γ|>3% or U>3%, and the treatment is to conduct on-site verification of each unit, and then enter the measurement 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 multi-mode fusion electric vehicle charging facilities according to claim 5 is characterized in that: The sampling 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 according to the actual situation, and determine the sample size for random inspection and standby inspection; the sampling plan follows the principle of randomness, and the sample number is generated by the random number table method, random number dice method or playing card method; S3. Select charging stations and charging facilities for sampling; S4. The sampled charging facilities are tested on site one by one in accordance with JJG 1148 and JJG 1149, and their eligibility is determined. The test results are entered 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 multi-mode fusion electric vehicle charging facilities according to claim 5 is characterized in that: In the measurement performance confirmation link, the measurement performance confirmation of the charging facility is specifically: For the charging facilities of the first category, the metering performance is confirmed to be qualified; For the second category of charging facilities, after the sampling verification, the metrological performance confirmation is carried out. If the batch sampling verification is qualified, the metrological performance is confirmed as qualified; if the batch sampling verification is unqualified, the metrological performance is confirmed as unqualified; if the charging facilities within the batch are qualified by sampling verification, the metrological performance is confirmed as qualified; if the charging facilities within the batch are unqualified by sampling verification, the metrological performance is confirmed as unqualified; For the third category of charging facilities, if the on-site verification 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 verification 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 calibration shall be carried out in accordance with JJG 1148 and JJG 1149. A calibration certificate shall be issued for those who pass the calibration, and a calibration result notice shall be issued for those who fail the calibration.

8. A multi-mode fusion 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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