Mathematical modeling method for metering error of charging facility

Abstract

The invention discloses a mathematical modeling method for a charging facility metering error, and the method comprises the steps: building a first energy conservation model of a charging station area, in a # imgabs0 # formula, Psi sigma is the power supply amount of a charging station general meter, Psi DC, i is the electric quantity of a DC metering module in a charger, Psi eta, i is the power loss amount of an AC / DC power module in the charger, and Psi eta is the electric quantity of a DC metering module in the charger; psi is the power consumption of monitoring, communication and other equipment in the station, and psi 1 is the loss of a line in the station; based on the active power and the reactive power, the energy conservation model is perfected, and a second energy conservation model is obtained; constructing an electric vehicle charging facility metering operation error mathematical model based on the second energy conservation model; by considering various sources of charging facility metering errors, the precision and reliability of the model are remarkably improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of electric vehicle charging facility metering, and in particular relates to a mathematical modeling method for charging facility metering errors. Background Art

[0002] With the popularity of electric vehicles, the metering accuracy of charging facilities has become a key factor affecting user fee settlement and operational efficiency. In related technologies, the metering error analysis methods of charging facilities mostly rely on a single factor or a simple linear model, which is difficult to fully reflect the complex error sources; Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide a mathematical modeling method for the metering error of charging facilities, so as to solve the technical problems that the existing methods for analyzing the metering error of charging facilities mostly rely on a single factor or a simple linear model, which makes it difficult to fully reflect the complex sources of error.

[0004] Technical solution of the present invention:

[0005] A mathematical modeling method for charging facility metering errors, characterized in that the method comprises:

[0006] The first energy conservation model of the charging station area is established, and the equation is as follows:

[0007]

[0008] Where, Σ is the power supply of the charging station main meter, Ψ DC,i is the power of the DC metering module inside the charger, η,i is the power loss of the AC / DC power module inside the charger, s is the power consumption of monitoring, communication and other equipment in the station, and Ψ1 is the line loss in the station;

[0009] Based on the active power and the reactive power, the energy conservation model is improved to obtain a second energy conservation model;

[0010] A mathematical model of metering operation error of electric vehicle charging facilities is constructed based on the second energy conservation model.

[0011] Based on the active power and reactive power, the energy conservation model is improved to obtain a second energy conservation model, which specifically includes:

[0012] Based on the first energy conservation model, the active power conservation model of the charging station is derived, and the equation is as follows:

[0013]

[0014] Where, P Σis the total meter power, P i is the power of charger i, P S , P1 are the power of the station equipment and the power of the station line loss respectively, η is the conversion efficiency of the AC / DC power module;

[0015] Based on the active power conservation model, a line loss power model is constructed, and the equation is as follows:

[0016]

[0017] Where, P i is the active power on the charger i branch, Q i Reactive power on charger branch i, U i is the terminal voltage of the node where charger i is located, U j is the terminal voltage of the node where charger j is located;

[0018] Substituting the line loss power model into the active power conservation model, the second energy conservation model is obtained, and the equation is as follows:

[0019]

[0020] Where P′ i =C0+C1P DC,i +C2P 2 DC,i , P DC,i is the DC active power output by charger i, ε0 is the fixed loss of monitoring, communication and other equipment in the station, and T is the metering period of the energy meter.

[0021] Constructing a line loss power model based on the active power conservation model specifically includes:

[0022] Construct the station line loss model, the equation is as follows:

[0023]

[0024] Where, I i is the current on the charger branch i; “*” indicates the conjugate of the vector;

[0025] Will I i and I j The line loss power model is obtained by respectively using the active power and reactive power on the respective branches.

[0026] Based on the active power and reactive power, the energy conservation model is improved to obtain a second energy conservation model, which specifically includes:

[0027] Construct the conversion efficiency model of the AC / DC power module. The equation is as follows:

[0028] η=(C0+C1P AC +C2P 2 AC ) / P AC ;

[0029] Where, P AC is the output power of the AC / DC power module, and the coefficients C0, C1, and C2 are determined by the data fitting method based on the field measurement data;

[0030] Substituting the conversion efficiency model into the active power conservation model, the second energy conservation model is obtained.

[0031] Constructing the conversion efficiency model of the AC / DC power module, including:

[0032] The power loss in building an AC / DC power module is calculated as follows:

[0033] P η =(1-η(P AC ))P AC

[0034] Where, P η is the power loss of the AC / DC power module, η(P AC ) is the AC / DC power module with an output power of P AC The conversion efficiency when

[0035] The conversion efficiency model is constructed based on the power loss.

[0036] A mathematical model of metering operation error of electric vehicle charging facilities is constructed based on the second energy conservation model, which is characterized by specifically including:

[0037] Obtain network system power consumption data;

[0038] performing item discretization processing on the second energy conservation model based on the network system power consumption data to obtain a third energy conservation model;

[0039] Based on the third energy conservation model, a mathematical model of metering operation error of the electric vehicle charging facility is constructed.

[0040] The second energy conservation model is discretized based on the network system power consumption data to obtain a third energy conservation model, which specifically includes:

[0041] Based on the second energy conservation model, the DC power consumed by the charger, the active line loss component contributed by the active power, and the reactive line loss component contributed by the reactive power are calculated as follows:

[0042]

[0043] Where R0 is the resistance per unit length, R i is the resistance value of charger i, P DC , i is the DC active power output by charger i, C0, C1, C2 are model coefficients, P i , Q i are the active power and reactive power on the charger i branch, U i 、U j are the terminal voltages of the nodes where chargers i and j are located respectively;

[0044] The DC power, the active line loss component, and the reactive line loss component are discretized to obtain the following equations for calculating the discretized DC power, the discretized active line loss component, and the discretized reactive line loss component:

[0045]

[0046] Where, is the actual power of charger i in the pth sampling interval, C0, C1, C2 are model coefficients, N j is the number of times the charging process is used during the measurement cycle, ΔT p is the sampling interval;

[0047]

[0048] Where N k is the number of data in the kth measurement period, ΔT j is the sampling time interval within the jth measurement cycle, Ψ′ i,k is the AC active power of the charger in the kth metering cycle;

[0049]

[0050] Where β0 is the line loss coefficient caused by reactive power;

[0051] The discretized DC power calculation formula, the discretized active line loss component calculation formula, and the discretized reactive line loss component calculation formula are respectively replaced with the corresponding DC power, the active line loss component, and the reactive line loss component, and combined with the second energy conservation model, the third energy conservation model is obtained:

[0052]

[0053] Based on the third energy conservation model, a mathematical model of the metering operation error of the electric vehicle charging facility is constructed, specifically including:

[0054] Simplify the true value of the power and obtain the simplified true value of the power. The calculation formula is as follows:

[0055]

[0056] Where, ε i Charger i metering point power measurement error, φ i is the electricity measurement value;

[0057] Based on the simplified true value of the electric quantity and the third energy conservation model, the mathematical model of the metering operation error of the electric vehicle charging facility is obtained, and the equation is as follows:

[0058]

[0059] Where, ΔT j ,y,Ψ ΣQ and U0 are charging process data and total meter data, y is the active power of the AC total meter, Ψ ΣQ is the amount of electricity generated by reactive power, U0 is the total meter terminal voltage of the station, i is the true value of the power measurement value, ε0, R0, ε i 、R i (i=1, 2, ..., n), β0 is the parameter to be solved.

[0060] Beneficial effects of the present invention:

[0061] The present invention further considers the influence of active power and reactive power on the basis of the first energy conservation model, and can improve the model to more accurately reflect the energy flow of the charging station. It also uses the established second energy conservation model to construct a mathematical model to evaluate and quantify the metering operation errors of electric vehicle charging facilities, taking into account various sources of metering errors of charging facilities, and significantly improving the accuracy and reliability of the model.

[0062] By establishing an energy conservation model, an active power conservation model, a line loss power model and a power module conversion efficiency model, the present invention further comprehensively considers various sources of charging facility metering errors, and significantly improves the accuracy and reliability of the model.

[0063] The present invention simplifies the AC side voltage processing, selects the reactive power line loss coefficient, and dynamically models the AC / DC power module efficiency, making the model easier to apply in practice and adaptable to operating conditions under different charging power.

[0064] The present invention utilizes existing AMI data. Compared with traditional charging facility measurement and testing methods, it does not require additional hardware and equipment investment, is easy to promote large-scale application, and can effectively protect the accurate measurement of electric vehicle charging facilities and the rights and interests of consumers.

[0065] This solves the technical problems that the existing methods for analyzing metering errors of charging facilities mostly rely on single factors or simple linear models, making it difficult to fully reflect complex error sources. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 A flowchart of a mathematical modeling method for charging facility measurement errors provided by one embodiment of the present invention;

[0067] Figure 2 A flowchart of a mathematical modeling method for charging facility metering errors provided in another embodiment of the present invention;

[0068] Figure 3 A block diagram of an electronic device according to an embodiment of the present invention;

[0069] Figure 4 A schematic diagram of the implementation results of the mathematical modeling method for charging facility metering errors provided by one embodiment of the present invention.

[0070] Description of the drawings: 110, processor; 120, memory. DETAILED DESCRIPTION

[0071] Considering that most existing models are based on static assumptions and do not fully consider dynamic characteristics, for example, the conversion efficiency of the AC / DC power module inside the charger will change under different charging powers, resulting in inaccurate error estimation, and the traditional charging facility measurement and testing method is mainly for professional metrology and calibration personnel to carry multiple charging facility on-site calibration devices and use the actual load calibration of the charging facility under test to verify the performance one by one, which has the disadvantages of large verification loss, low efficiency and high cost. The present invention solves the above technical problems.

[0072] The following is combined with Figures 1 to 4 The present invention is further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the relevant invention and are not intended to limit the invention. It should also be noted that for ease of description, only the parts relevant to the invention are shown in the accompanying drawings.

[0073] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in this application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0074] Please refer to Figure 1 , which is a flowchart of a mathematical modeling method for charging facility measurement errors according to an embodiment of the present invention, and includes the following steps:

[0075] Step S101: Establish a first energy conservation model for the charging station area. The equation is as follows:

[0076]

[0077] Where, Σ is the power supply of the charging station main meter, Ψ DC,i is the power of the DC metering module inside the charger, η,i is the power loss of the AC / DC power module inside the charger, s is the power consumption of monitoring, communication and other equipment in the station, and Ψ1 is the line loss in the station.

[0078] Step S103: Based on the active power and the reactive power, the energy conservation model is improved to obtain a second energy conservation model.

[0079] Step S105: constructing a mathematical model of metering operation error of electric vehicle charging facilities based on the second energy conservation model.

[0080] In this embodiment, according to the law of conservation of energy, the AC side power received by the station area master meter is equal to the sum of the power consumed by each charging pile and equipment in the station and the line loss. Based on this, the energy conservation equation of the entire charging station area can be established.

[0081] By establishing a first energy conservation model for charging stations, we can establish the energy balance between the AC power received by the charging station master meter, the power consumed by each charger, in-station equipment, and line losses. Building on this first energy conservation model, by further considering the impact of active and reactive power, we can refine the model to more accurately reflect the energy flow within the charging station. Active power, the power component that directly participates in electrical energy conversion, is crucial for electric vehicle charging. Reactive power, while not directly involved in electrical energy conversion, is essential for maintaining stable power system operation. In charging stations, reactive power primarily affects voltage stability and line losses. Using the second energy conservation model, we construct a mathematical model to evaluate and quantify the metering errors of electric vehicle charging facilities. Based on the error analysis results, we can propose recommendations for improving the metering accuracy of charging facilities, such as replacing metering equipment and optimizing equipment maintenance schedules.

[0082] Through the above steps, the energy conservation model of electric vehicle charging stations can be systematically established and improved, thereby providing a scientific basis for the accurate metering and efficient operation of charging facilities. It can also realize online monitoring and abnormal warning of the metering performance of electric vehicle charging facilities, ensure the accurate metering of charging facilities, and enhance the intelligent remote operation and maintenance capabilities of electric vehicle charging facilities. On the basis of ensuring accurate and reliable metering of charging facilities, it can reduce operation and maintenance costs.

[0083] Step S103, based on the active power and the reactive power, improves the energy conservation model to obtain a second energy conservation model, which specifically includes the following steps:

[0084] Step S1031: deriving the active power conservation model of the charging station based on the first energy conservation model. The equation is as follows:

[0085]

[0086] The active power conservation equation of the charging station is derived from the energy conservation equation to express the relationship between the power of the total meter and the power of each charger, the equipment in the station, and the line loss. Σ is the total meter power, P i is the power of charger i, P S , P1 are the power of the station equipment and the power of the station line loss respectively, and η is the conversion efficiency of the AC / DC power module.

[0087] Step S1033: Construct a line loss power model based on the active power conservation model. The equation is as follows:

[0088]

[0089] Where, P i is the active power on the charger i branch, Q i Reactive power on charger branch i, U i is the terminal voltage of the node where charger i is located, U j is the terminal voltage of the node where charger j is located.

[0090] Step S1035: Substitute the line loss power model into the active power conservation model to obtain a second energy conservation model. The equation is as follows:

[0091]

[0092] Where P′ i =C0+C1P DC ,i+C2P 2 DC,i , P DC , i is the DC active power output by charger i, ε0 is the fixed loss of monitoring, communication and other equipment in the station, and T is the metering period of the electric energy meter.

[0093] Through the above steps, the energy flow of a charging station can be accurately calculated, including the output power of the charger, line losses, and the energy consumption of the station's equipment. This analysis of energy flow helps identify the main sources of energy loss, allowing measures to reduce losses and improve charging efficiency. Accurate energy consumption analysis can help optimize charging station operation strategies, reduce unnecessary energy consumption, and thus lower operation and maintenance costs. Precise energy management allows for more efficient utilization of grid energy and reduces waste. By building and refining energy conservation models, the operational efficiency and intelligence level of electric vehicle charging stations can be significantly improved.

[0094] The expression of line loss power is given and further rewritten into a more specific calculation form through the relationship between current and voltage. Step S1033, constructing a line loss power model based on the active power conservation model, specifically includes the following steps:

[0095] Step S10331: Construct a station line loss model, the equation is as follows:

[0096]

[0097] Where, I i is the current on the charger branch i; “*” represents the conjugate of the vector.

[0098] Step S10333: I i and I j The line loss power model is obtained by expressing it with the active power and reactive power on each branch.

[0099] In this embodiment, the first The first one represents the self-loss caused by the reference line resistance R0, and the second one represents the mutual loss between different charger branches. represents the loss caused by the resistance of each charger branch. By simplifying the expression, a more concise line loss power model can be derived for calculating the energy loss within the charging station. This allows for accurate calculation of the energy loss within the charging station, providing data support for optimizing charging station operations. By analyzing line losses, measures can be taken to reduce unnecessary energy loss and improve energy efficiency.

[0100] Step S1033, based on the active power and the reactive power, improves the energy conservation model to obtain a second energy conservation model, which specifically includes the following steps:

[0101] Step S10335: Construct a conversion efficiency model of the AC / DC power module. The equation is as follows:

[0102] η=(C0+C1P AC +C2P 2 AC ) / PAC (6).

[0103] Where, P AC is the output power of the AC / DC power module. The coefficients C0, C1, and C2 are determined by the data fitting method based on the field measurement data.

[0104] The values ​​of the d coefficients C0, C1, and C2 in equation (6) are 7.56948693×10 2 9.94796287×10 -1 and 5.85326901×10 -2 .

[0105] Step S10337: Substitute the conversion efficiency model into the active power conservation model to obtain a second energy conservation model.

[0106] In this embodiment, the impact of conversion efficiency on energy conservation is taken into account by substituting the conversion efficiency model η into the active power conservation model. This results in a more accurate energy conservation model that more precisely describes the energy flow and conversion process in the charging station. Therefore, by integrating the AC / DC power module's conversion efficiency model into the active power conservation model, a more comprehensive energy conservation model can be obtained.

[0107] Considering that the conversion efficiency of the AC / DC power module inside the charger changes at different charging powers, which affects the accuracy of the mathematical model of the charging facility metering operation error, it is necessary to establish a model of the conversion efficiency of the AC / DC power module at different charging powers. Based on step S10335, the conversion efficiency model of the AC / DC power module is constructed, which specifically includes the following steps:

[0108] Step S103351: Construct the power loss of the AC / DC power module. The equation is as follows:

[0109] P η =(1-η(P AC ))P AC (5).

[0110] Where, P η is the power loss of the AC / DC power module, which represents the electric energy that is not effectively utilized during the conversion process, η(P AC ) is the AC / DC power module with an output power of P AC The conversion efficiency when .

[0111] Substituting equations (5) and (6) into equation (2) and integrating them, we can obtain the second energy conservation model.

[0112] Step S103353: Construct a conversion efficiency model based on the power loss.

[0113] In this embodiment, the power loss model is used to construct a more comprehensive conversion efficiency model to describe the efficiency of the AC / DC power module under different operating conditions. By accurately calculating the conversion efficiency, the energy efficiency of the charging station can be more accurately analyzed and the main sources of energy loss can be identified. Based on this accurate conversion efficiency model, the charging strategy can be optimized to reduce unnecessary energy loss and improve charging efficiency.

[0114] Step S105, constructing a mathematical model of metering operation error of electric vehicle charging facilities based on the second energy conservation model, specifically includes the following steps:

[0115] Step S1051: Acquire network system power consumption data.

[0116] Step S1053: performing item discretization processing on the second energy conservation model based on the network system power consumption data to obtain a third energy conservation model.

[0117] Step S1055: Based on the third energy conservation model, a mathematical model of metering operation errors of electric vehicle charging facilities is constructed.

[0118] In this embodiment, electricity usage data is collected from smart meters and monitoring systems at electric vehicle charging stations. This data typically includes real-time power, current, voltage, and energy consumption information for each charger, ensuring data integrity and accuracy, providing reliable input for subsequent model construction. Network system electricity usage data can be collected by Advanced Metering Infrastructure (AMI). AMI data covers a variety of operating parameters of charging facilities, facilitating a comprehensive assessment of metering errors.

[0119] Discretizing the continuous variables in the second energy conservation model allows it to adapt to actual electricity usage data. For example, the continuous power variable is converted into discrete power measurements. Discretizing each item in the model allows it to directly use data collected from electricity meters and monitoring systems. This results in a more specific third energy conservation model that better reflects actual operating conditions. This third energy conservation model can identify the main sources of error, providing guidance for reducing errors and optimizing charging station operations.

[0120] Step S1053, performing item discretization processing on the second energy conservation model based on the network system power consumption data to obtain a third energy conservation model, specifically comprising the following steps:

[0121] Step S10531: Based on the second energy conservation model, the DC power consumed by the charger, the active line loss component contributed by the active power, and the reactive line loss component contributed by the reactive power are calculated using the following formula:

[0122]

[0123] Where R0 is the resistance per unit length, R i is the resistance value of charger i, P DC , i is the DC active power output by charger i, C0, C1, C2 are model coefficients, P i , Q i are the active power and reactive power on the charger i branch, U i 、U j are the terminal voltages of the nodes where chargers i and j are located respectively.

[0124] Step S10533: Discretize the DC power, active line loss component, and reactive line loss component, respectively, to obtain the following equations for calculating the discretized DC power, the discretized active line loss component, and the discretized reactive line loss component:

[0125] Ψ ΣDC,i The actual power consumed by charger i in the sampling interval ΔT p The expression inside.

[0126]

[0127] Among them, based on the massive charging facility electricity consumption data provided by AMI and considering the discreteness of the data, the items in the equation are discretized and expressed using meter electricity data.

[0128] Where, is the actual power of charger i in the pth sampling interval, C0, C1, C2 are model coefficients, N j is the number of times the charging process is used during the measurement cycle, ΔT p is the sampling interval.

[0129] The data during the charging process is used to calculate the line loss caused by the active power, and considering that the voltage drop between the main meter and the sub-meter in the charging station is small, the AC side terminal voltage U of each charger is calculated. i Reasonable simplification, there is U i ≈U0, U0 is the total meter terminal voltage of the station. Then Ψ ΣIP It can be expressed as follows:

[0130]

[0131] Where N kis the number of data in the kth measurement period, ΔT j is the sampling time interval within the jth measurement cycle, Ψ′ i,k is the actual AC active power of the charger in the kth metering cycle.

[0132] When selecting the line loss coefficient caused by reactive power, it is considered that the DC metering module in the DC charging station does not have the reactive power metering function. When the same type of charging stations are operating normally, the reactive power demand characteristics provided by the grid are similar. The line loss of the charging station is mainly caused by the line resistance. The power factor of the charging station in normal operation is kept above 0.9. Therefore, the reactive power of the total meter can be used to account for the line loss contributed by reactive power. ΣQ It can be expressed as follows:

[0133]

[0134] Where β0 is the line loss coefficient caused by reactive power.

[0135] Step S10535: Substitute the discretized DC power calculation formula, the discretized active line loss component calculation formula, and the discretized reactive line loss component calculation formula with the corresponding DC power, active line loss component, and reactive line loss component, respectively, and combine them with the second energy conservation model to obtain a third energy conservation model:

[0136]

[0137] Step S1055, based on the third energy conservation model, constructs a mathematical model of the metering operation error of the electric vehicle charging facility, which specifically includes the following steps:

[0138] Step S10551: Simplify the actual value of the power to obtain the simplified actual value of the power. The calculation formula is as follows:

[0139]

[0140] Where, ε i Charger i metering point power measurement error, φ i The power measurement value.

[0141] Among them, let the active power of the AC total meter be y, and the total meter power measurement error be ε y , the power measurement error of charger i is ε i , the electricity measurement value is φ i , the true value is Ψ i Considering ε i The value of is relatively small during normal operation, so the following relationship exists:

[0142] Step S10553: Based on the simplified true value of the electric quantity and the third energy conservation model, a mathematical model of the metering operation error of the electric vehicle charging facility is obtained, and the equation is as follows:

[0143]

[0144] (14) is established through (12) and (13). Where, ΔT j ,y,Ψ ΣQ and U0 are charging process data and total meter data, y is the active power of the AC total meter, Ψ ΣQ is the amount of electricity generated by reactive power, U0 is the total meter terminal voltage of the station, i is the true value of the power measurement value, ε0, R0, ε i 、R i (i=1, 2, ..., n), β0 is the parameter to be solved.

[0145] like Figure 3 As shown, the present invention also provides an electronic device, comprising: at least one processor 110; a memory 120 communicatively connected to the at least one processor 110; wherein the memory 120 stores instructions that can be executed by the at least one processor 110, and the instructions are executed by the at least one processor 110 to enable the at least one processor 110 to execute any one of the mathematical modeling methods of facility metering errors.

[0146] The present invention also provides a storage medium storing a computer program, which realizes any one of the electric vehicle charging methods when executed by a processor.

[0147] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct RAMbus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM). The various embodiments in this specification are described in a progressive manner, and similar parts between the various embodiments can be referenced to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the embodiments of the apparatus, device, and non-volatile computer storage medium, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referenced to the partial description of the method embodiments.

[0148] In another embodiment, Figure 2 As shown, the specific steps of the mathematical modeling method for charging facility metering error proposed in the present invention are:

[0149] Step S201. Establish an energy conservation model: According to the law of conservation of energy, the AC power received by the charging station master meter is equal to the sum of the power consumed by each charger and the equipment in the station and the line loss. Based on this, an energy conservation equation can be established.

[0150] Step S203: Derive the active power conservation model: Starting from the energy conservation equation, derive the active power conservation equation of the charging station.

[0151] Step S205: Establish a charging station line loss power model: provide an expression for line loss power, and further rewrite it into a more specific calculation form through the relationship between current and voltage.

[0152] Establish a conversion efficiency model for the AC / DC power module: Establish a model for the conversion efficiency of the AC / DC power module at different charging powers to avoid affecting the accuracy of the mathematical model of the metering operation error of the charging facility.

[0153] Establish a charging station metering error model based on AMI data: Based on the massive charging facility electricity consumption data provided by AMI and considering the discreteness of the data, the items in the equation are discretized and represented by meter power data.

[0154] Among them, the AC side terminal voltage is simplified: considering the small voltage drop between the main meter and the sub-meter, the AC side terminal voltage of each charger is reasonably simplified.

[0155] Select the line loss factor caused by reactive power.

[0156] Step S207. Combine the energy conservation equation: Combine the previous formulas to establish the energy conservation equation of the charging station based on the AMI data.

[0157] Step S209. Establishing a final mathematical model: Based on the above steps, a final mathematical model of the measurement operation error of the electric vehicle charging facility is established.

[0158] Specific application example: A charging station in a certain city was selected for pilot application. Its topology consists of 20 chargers, which is a typical tree topology. The charging station collects electricity usage data from the AC and DC meters of the charging piles during the two-week period from February 1 to February 14, 2025, and processes the collected data as shown in the following table:

[0159]

[0160]

[0161] The data was uploaded to the online monitoring system for the metering performance of electric vehicle charging facilities, and then the metering operation error was calculated. To verify the accuracy and reliability of the model calculation results, a blind test method was used to increase the deviation of 5% and -5% on the power consumption data of a single charger to simulate the metering anomaly of the charger. The error response rate γ shown in formula (15) was defined to quantitatively evaluate the accuracy of the model in identifying the metering operation error anomaly of the charging facility. The results are shown in the following table:

[0162]

[0163] Where Δσ0 is the set value of the power deviation, and Δσ is the change in the charger metering error calculated by the model based on the set value of the deviation. The larger the γ value, the more accurate the model is in identifying charger metering anomalies.

[0164] Table 2 Measurement operation error results

[0165]

[0166]

[0167] The error response rate of the entire pilot charging station is calculated as follows: Figure 4 As shown in the figure, the error response rate of all chargers is greater than 85%, indicating that the mathematical modeling method of metering error proposed in this paper has a high recognition accuracy for charging facilities with abnormal metering conditions.

Claims

1. A mathematical modeling method for charging facility metering errors, characterized by: The method comprises: The first energy conservation model of the charging station area is established, and the equation is as follows: Where, Σ is the power supply of the charging station main meter, Ψ DC,i is the power of the DC metering module inside the charger, η,i is the power loss of the AC / DC power module inside the charger, s is the power consumption of monitoring, communication and other equipment in the station, and Ψ1 is the line loss in the station; Based on the active power and the reactive power, the energy conservation model is improved to obtain a second energy conservation model; A mathematical model of metering operation errors of electric vehicle charging facilities is constructed based on the second energy conservation model.

2. The mathematical modeling method for charging facility measurement error according to claim 1, characterized in that: Based on the active power and reactive power, the energy conservation model is improved to obtain a second energy conservation model, which specifically includes: Based on the first energy conservation model, the active power conservation model of the charging station is derived, and the equation is as follows: Where, P Σ is the total meter power, P i is the power of charger i, P S , P1 are the power of the station equipment and the power of the station line loss respectively, η is the conversion efficiency of the AC / DC power module; Based on the active power conservation model, a line loss power model is constructed, and the equation is as follows: Where, P i is the active power on the charger i branch, Q i Reactive power on charger branch i, U i is the terminal voltage of the node where charger i is located, U j is the terminal voltage of the node where charger j is located; Substituting the line loss power model into the active power conservation model, the second energy conservation model is obtained, and the equation is as follows: Where P′ i =C0+C1P DC,i +C2P 2 DC,i , P DC,i is the DC active power output by charger i, ε0 is the fixed loss of monitoring, communication and other equipment in the station, and T is the metering period of the energy meter.

3. The mathematical modeling method for charging facility measurement error according to claim 2, characterized in that: Constructing a line loss power model based on the active power conservation model specifically includes: Construct the station line loss model, the equation is as follows: Where, I i is the current on the charger branch i; "*" represents the conjugate of the vector; Will I i and I j The line loss power model is obtained by respectively using the active power and reactive power on the respective branches.

4. The mathematical modeling method for charging facility measurement error according to claim 2, characterized in that: Based on the active power and reactive power, the energy conservation model is improved to obtain a second energy conservation model, which specifically includes: Construct the conversion efficiency model of the AC / DC power module. The equation is as follows: η=(C0+C1P AC +C2P 2 AC ) / P AC ; Where, P AC is the output power of the AC / DC power module, and the coefficients C0, C1, and C2 are determined by the data fitting method based on the field measurement data; Substituting the conversion efficiency model into the active power conservation model, the second energy conservation model is obtained.

5. The mathematical modeling method for charging facility measurement error according to claim 4, characterized in that: Constructing the conversion efficiency model of the AC / DC power module, including: The power loss in building an AC / DC power module is calculated as follows: P η =(1-η(P AC ))P AC Where, P η is the power loss of the AC / DC power module, η(P AC ) is the AC / DC power module with an output power of P AC The conversion efficiency when The conversion efficiency model is constructed based on the power loss.

6. A mathematical modeling method for charging facility measurement error according to any one of claims 2 to 4, constructing an electric vehicle charging facility measurement operation error data based on the second energy conservation model. The learning model is characterized by Specifically include: Obtain network system power consumption data; performing item discretization processing on the second energy conservation model based on the network system power consumption data to obtain a third energy conservation model; Based on the third energy conservation model, a mathematical model of metering operation error of the electric vehicle charging facility is constructed.

7. The mathematical modeling method for charging facility measurement error according to claim 6, characterized in that: The second energy conservation model is discretized based on the network system power consumption data to obtain a third energy conservation model, which specifically includes: Based on the second energy conservation model, the DC power consumed by the charger, the active line loss component contributed by the active power, and the reactive line loss component contributed by the reactive power are calculated as follows: Where R0 is the resistance per unit length, R i is the resistance value of charger i, P DC , i is the DC active power output by charger i, C0, C1, C2 are model coefficients, P i , Q i are the active power and reactive power on the charger i branch, U i 、U j are the terminal voltages of the nodes where chargers i and j are located respectively; The DC power, the active line loss component, and the reactive line loss component are discretized to obtain the following equations for calculating the discretized DC power, the discretized active line loss component, and the discretized reactive line loss component: Where, is the actual power of charger i in the pth sampling interval, C0, C1, C2 are model coefficients, N j is the number of times the charging process is used during the measurement cycle, ΔT p is the sampling interval; Where N k is the number of data in the kth measurement period, ΔT j is the sampling time interval within the jth measurement cycle, Ψ′ i,k is the AC active power of the charger in the kth metering cycle; Where β0 is the line loss coefficient caused by reactive power; The discretized DC power calculation formula, the discretized active line loss component calculation formula, and the discretized reactive line loss component calculation formula are respectively replaced with the corresponding DC power, the active line loss component, and the reactive line loss component, and combined with the second energy conservation model, the third energy conservation model is obtained:

8. The mathematical modeling method for charging facility measurement error according to claim 7, characterized in that: Based on the third energy conservation model, a mathematical model of the metering operation error of the electric vehicle charging facility is constructed, specifically including: Simplify the true value of the power and obtain the simplified true value of the power. The calculation formula is as follows: Where, ε i Charger i metering point power measurement error, φ i is the electricity measurement value; Based on the simplified true value of the electric quantity and the third energy conservation model, the mathematical model of the metering operation error of the electric vehicle charging facility is obtained, and the equation is as follows: Where, ΔT j ,y,Ψ ΣQ and U0 are charging process data and total meter data, y is the active power of the AC total meter, Ψ ΣQ is the amount of electricity generated by reactive power, U0 is the total meter terminal voltage of the station, i is the true value of the power measurement value, ε0, R0, ε i 、R i (i=1, 2, ..., n), β0 is the parameter to be solved.

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