A metering monitoring method for multi-type resource access of a virtual power plant

Abstract

This application discloses a metering and monitoring method for multi-type resource access in virtual power plants, relating to the field of virtual power plant technology. It analyzes the accuracy of each metering device based on the environmental impact analysis results and interference voltage impact analysis results of each metering device at the virtual power plant resource access point. Based on the accuracy analysis results of each metering device at the virtual power plant resource access point, it selects suitable metering devices for each resource access point. It quantifies the capacitive coupling effect of external high-voltage circuits on the equipment casing and the electromagnetic induction effect of the internal space electric field on sensitive signal traces by introducing parameters such as the relative projected area of ​​the high-voltage conductor and the equipment casing, minimum distance, voltage to ground, input impedance, trace length of high-resistivity nodes on printed circuit boards, interlayer spacing, electric field change rate, and equivalent complex impedance modulus. These two parameters are then combined for evaluation, fully covering the complete electromagnetic interference transmission chain from the external primary system to the internal secondary weak current circuit.

Description

Technical Field

[0001] This application belongs to the field of virtual power plants, specifically a metering and monitoring method for multi-type resource access in virtual power plants. Background Technology

[0002] Virtual power plants are a new type of power operation mode that aggregates and coordinates diverse distributed energy resources such as distributed power sources, energy storage systems, controllable loads, and electric vehicles through advanced information and communication technologies and software systems. Their stable operation is highly dependent on the accurate metering and real-time monitoring of electrical quantities at each resource access point. However, virtual power plant resource access points are usually scattered in diverse scenarios such as substations, industrial plants, commercial buildings, and residential power distribution networks. The operating environment of metering equipment is complex and variable, and there are many types of electromagnetic interference sources with varying intensities, which poses a serious challenge to the accuracy and reliability of metering data. Existing metrological monitoring methods mainly focus on calibrating the accuracy level of the metrological equipment itself or compensating for and correcting metrological errors due to single environmental factors (such as temperature and humidity), and generally suffer from the following technical defects: 1. The physical impact of magnetic field disturbances caused by the deterioration of the internal operating condition of the metering equipment on the metering accuracy is not fully considered. Most existing methods directly establish a linear or nonlinear correspondence between ambient temperature and humidity and metering error, while ignoring the complete causal transmission chain that environmental stress induces the degradation of the magnetic properties of the iron core and insulation aging, which in turn leads to the aggravation of internal stray magnetic field disturbances and ultimately affects the metering accuracy. As a result, the implicit metering deviation caused by the internal state shift after the equipment has been in operation for a long time cannot be effectively identified and quantified. 2. Existing methods for analyzing electric field and electromagnetic coupling interference are relatively crude, usually only focusing on whether the macroscopic electromagnetic field strength exceeds the specified limit. They lack refined modeling and quantitative calculation of microscopic electromagnetic compatibility mechanisms such as parasitic capacitance coupling paths and sensitive trace induction at high-resistivity nodes on printed circuit boards. It is difficult to accurately assess the superposition effect of multiple interference voltages between the external space electric field of the equipment casing and the weak signal loops at the circuit board level inside the equipment. In order to solve the problems proposed in this background technology, this application designs a metering and monitoring method for multi-type resource access in virtual power plants. Summary of the Invention

[0003] To address the aforementioned technical shortcomings, this application proposes a metering and monitoring method for multi-type resource access in virtual power plants.

[0004] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: This application provides a metering and monitoring method for multi-type resource access in virtual power plants, which includes the following specific steps: S1. Obtain data on the environmental magnetic field disturbance, electric field and electromagnetic influence parameters, and performance of the metering equipment at each metering device in the virtual power plant resource access point. S2. Based on the data on the magnetic field disturbance of each metering device at the virtual power plant resource access point, conduct an environmental impact analysis of each metering device. S3. Based on the electric field and electromagnetic influence parameter data of the virtual power plant resource access point and the performance data of the metering equipment, conduct an analysis of the interference voltage influence of each metering device. S4. Based on the environmental impact analysis results and interference voltage impact analysis results of each metering device at the virtual power plant resource access point, conduct an accuracy analysis of each metering device. S5. Based on the accuracy analysis results of each metering device at the virtual power plant resource access point, select suitable metering devices for each virtual power plant resource access point.

[0005] It should be noted that, as a preferred technical solution for metering and monitoring methods for multi-type resource access in virtual power plants, the specific steps of S1 are as follows: S11. Obtain data on the environmental magnetic field disturbance of each metering device at the virtual power plant resource access point through current transformers, temperature sensors, metering equipment design data, nameplate markings, rated secondary output voltage and output power of the metering equipment, and product manuals. Among them, the data on the environmental magnetic field disturbance of each metering device at the virtual power plant resource access point includes the core excitation current distortion rate, winding DC resistance deviation rate, increment of insulation dielectric loss tangent, rated working magnetic flux density of the equipment, slope coefficient of the core magnetization curve near the inflection point, standard magnetic flux amplitude corresponding to the rated induced electromotive force on the secondary side of the metering equipment, effective coupling area of ​​the winding, and number of turns. S12. Obtain the electric field and electromagnetic influence parameter data of the virtual power plant resource access point through the spatial relationship between the high-voltage conductor and the metering equipment, the power distribution equipment layout diagram, and the substation bus voltage transformer. Among them, the electric field and electromagnetic influence parameter data of the virtual power plant resource access point are the relative projected area of ​​the high-voltage conductor and the shell of each metering equipment at the virtual power plant resource access point, the minimum distance from the high-voltage conductor to the shell of each metering equipment, and the voltage of the high-voltage conductor to ground. S13. Obtain performance data of virtual power plant resource access point metering equipment through product technical manuals, printed circuit board layout diagrams, printed circuit board stack-up structure design documents, miniature fiber optic electric field sensors, circuit schematics, and component data sheets. Among them, the performance data of virtual power plant resource access point metering equipment includes the input impedance of each metering device, the trace length of the printed circuit board connecting the high-resistance node inside each metering device, the vertical distance from the trace layer to the reference ground plane, the time change rate of the average electric field intensity in the internal space of the metering device, and the equivalent complex impedance modulus between the high-resistance node and the ground layer of the printed circuit board. S14. Store the acquired data in the storage component for use in the analysis process.

[0006] It should be noted that, as a preferred technical solution for metering and monitoring methods for multi-type resource access in virtual power plants, S2 includes the following specific steps: Based on the core excitation current distortion rate, winding DC resistance deviation rate, increment of insulation dielectric loss tangent, rated operating magnetic flux density, slope coefficient of the core magnetization curve near the inflection point, standard magnetic flux amplitude corresponding to the rated induced electromotive force on the secondary side of the metering equipment, effective coupling area of ​​the winding, and number of turns, an environmental impact analysis of each metering device is performed. The specific process of the environmental impact analysis of each metering device is as follows: [The remaining text appears to be incomplete and requires further context.] Multiplying the core excitation current distortion rate by the winding DC resistance offset rate and adding the increment of the insulation dielectric loss tangent, we obtain the comprehensive index of internal operational anomalies for each metering device. Multiplying the comprehensive index of internal operational anomalies for each metering device by the rated operating magnetic flux density of the device and then by the slope coefficient of the core magnetization curve near the inflection point, we obtain the induced magnetic field disturbance intensity for each metering device. Multiplying the induced magnetic field disturbance intensity for each metering device by the effective coupling area of ​​the winding and then by the number of turns, and then dividing by the standard magnetic flux amplitude corresponding to the rated induced electromotive force on the secondary side of the metering device, we obtain the environmental impact analysis results for each metering device.

[0007] It should be noted that, as a preferred technical solution for metering and monitoring methods for multi-type resource access in virtual power plants, the specific steps of S3 are as follows: S31. Calculate the interference voltage generated by the parasitic capacitance coupling of each metering device based on the relative projected area of ​​the high-voltage conductor and the casing of each metering device at the virtual power plant resource access point, the minimum distance from the high-voltage conductor to the casing of each metering device, the voltage of the high-voltage conductor to ground, and the input impedance of each metering device. S32. Calculate the interference voltage generated by the high-resistance nodes of each metering device based on the trace length of the printed circuit board connecting the high-resistance node inside each metering device of the virtual power plant resource access point, the vertical distance from the layer where the trace is located to the reference ground plane, the time change rate of the average electric field intensity inside the metering device, and the equivalent complex impedance modulus between the high-resistance node and the ground layer of the printed circuit board. S33. Analyze the impact of interference voltage on each metering device based on the interference voltage generated by parasitic capacitance coupling and the interference voltage generated by high-resistance nodes.

[0008] It should be noted that, as a preferred technical solution for metering and monitoring methods for multi-type resource access in virtual power plants, the specific steps of S31 are as follows: The interference voltage generated by parasitic capacitance coupling of each metering device is calculated based on the relative projected area between the high-voltage conductor at the virtual power plant resource access point and the casing of each metering device, the minimum distance from the high-voltage conductor to the casing of each metering device, the voltage of the high-voltage conductor to ground, and the input impedance of each metering device. Specifically, the calculation process for the interference voltage generated by parasitic capacitance coupling of each metering device is as follows: the relative projected area between the high-voltage conductor at the virtual power plant resource access point and the casing of each metering device is divided by the minimum distance from the high-voltage conductor to the casing of each metering device, and then multiplied by the vacuum dielectric constant to obtain the parasitic capacitance of each metering device; the parasitic capacitance of each metering device is multiplied by the voltage of the high-voltage conductor to ground, the angular frequency of the power frequency electric field, and the magnitude of the input impedance of the metering device to obtain the interference voltage generated by parasitic capacitance coupling of each metering device.

[0009] It should be noted that, as a preferred technical solution for metering and monitoring methods for accessing multiple types of resources in a virtual power plant, the specific steps of S32 are as follows: The interference voltage generated by the high-resistance nodes of each metering device is calculated based on the trace length of the printed circuit board connecting the high-resistance node inside each metering device at the virtual power plant resource access point, the vertical distance from the trace layer to the reference ground plane, the time-varying rate of change of the average electric field intensity inside the metering device, and the equivalent complex impedance modulus between the high-resistance node and the ground plane of the printed circuit board. Specifically, the calculation process involves multiplying the trace length of the printed circuit board connecting the high-resistance node and the vertical distance from the trace layer to the reference ground plane to obtain the equivalent projected area of ​​the trace in the vertical electric field direction; multiplying the equivalent projected area of ​​the trace in the vertical electric field direction, the time-varying rate of change of the average electric field intensity inside the metering device, and the vacuum dielectric constant to obtain the minute current induced on the trace by the change in the spatial electric field; and multiplying the minute current induced on the trace by the equivalent complex impedance modulus between the high-resistance node and the ground plane of the printed circuit board to obtain the interference voltage generated by the high-resistance node of each metering device.

[0010] It should be noted that, as a preferred technical solution for metering and monitoring methods for accessing multiple types of resources in a virtual power plant, the specific steps of S33 are as follows: obtaining the interference voltage generated by parasitic capacitance coupling of each metering device and the interference voltage generated by high-resistance nodes; adding the magnitudes of the interference voltage generated by parasitic capacitance coupling of each metering device and the interference voltage generated by high-resistance nodes to obtain the common-mode interference voltage experienced by each metering device; dividing the common-mode interference voltage experienced by each metering device by the product of the common-mode rejection ratio and the rated voltage of each metering device to obtain the impact analysis results of the interference voltage of each metering device.

[0011] It should be noted that, as a preferred technical solution for metering and monitoring methods for accessing multiple types of resources in a virtual power plant, the specific steps of S4 are as follows: obtaining the environmental impact analysis results and interference voltage impact analysis results of each metering device at the virtual power plant resource access point, and then weighting and summing the environmental impact analysis results and interference voltage impact analysis results of each metering device to obtain the accuracy analysis results of each metering device.

[0012] It should be noted that, as a preferred technical solution for metering and monitoring methods for multiple types of resource access in virtual power plants, the specific steps of S5 are as follows: obtaining the accuracy analysis results of each metering device at the resource access point of the virtual power plant; arranging the accuracy analysis results of each metering device in ascending order; recording the metering device corresponding to the accuracy analysis result ranked first as the most accurate metering device for that resource access point of the virtual power plant; configuring the most accurate metering device for each resource access point of the virtual power plant to the corresponding access point; reading the metering value provided by the device; and using it as the final metering result for that resource access point of the virtual power plant. In this way, suitable metering devices are selected for each resource access point of the virtual power plant.

[0013] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention acquires data on the environmental magnetic field disturbance, electric field and electromagnetic influence parameters, and performance data of each metering device at the virtual power plant resource access point; it performs environmental impact analysis on each metering device based on the environmental magnetic field disturbance data; it performs interference voltage impact analysis on each metering device based on the electric field and electromagnetic influence parameters and performance data; it performs accuracy analysis on each metering device based on the environmental impact analysis results and interference voltage impact analysis results; it selects suitable metering devices for each virtual power plant resource access point based on the accuracy analysis results; and it achieves a quantitative representation of the degree of stray magnetic field disturbance caused by internal state deviations such as long-term aging and insulation degradation of the metering device by integrating and calculating multiple source state parameters such as core excitation current distortion rate, winding DC resistance deviation rate, and insulation dielectric loss tangent increment, thus truly reflecting the health of the equipment itself. The implicit impact of environmental conditions on metering accuracy is investigated. The capacitive coupling effect of external high-voltage circuits on the equipment casing is quantified by introducing parameters such as the relative projected area of ​​the high-voltage conductor and the equipment casing, minimum distance, voltage to ground, and input impedance. The electromagnetic induction effect of the internal electric field on sensitive signal traces is quantified by introducing parameters such as the trace length of high-resistance nodes on printed circuit boards, interlayer spacing, electric field change rate, and equivalent complex impedance modulus. These two parameters are then combined to form a common-mode interference voltage, which is normalized and evaluated using the common-mode rejection ratio. This comprehensively covers the entire electromagnetic interference transmission chain from the external primary system to the internal secondary weak-voltage circuit, making the analysis results more comprehensive and accurate. The environmental impact analysis results are weighted and fused with the interference voltage impact analysis results to generate the accuracy analysis results of each metering device under the actual operating conditions at the current access point. Based on these results, candidate metering devices are ranked in ascending order, and the device with the best accuracy is selected and configured at the corresponding access point. This reduces the risk of data deviation caused by mismatch between the metering device and the on-site electromagnetic and operating environment, improving the accuracy and reliability of the overall monitoring data of the virtual power plant. Attached Figure Description

[0014] Figure 1 This is a schematic diagram of the overall process of a metering and monitoring method for accessing multiple types of resources in a virtual power plant, as described in this application.

[0015] Figure 2 This is a schematic diagram illustrating the process of obtaining the environmental impact analysis results of each metering device in a metering and monitoring method for multi-type resource access in a virtual power plant, as described in this application.

[0016] Figure 3 This is a schematic diagram of step S3 of a metering and monitoring method for multi-type resource access in a virtual power plant, as described in this application.

[0017] Figure 4 This is a schematic diagram illustrating the process of obtaining the interference voltage impact analysis results of each metering device in a metering and monitoring method for multi-type resource access in a virtual power plant, as described in this application. Detailed Implementation

[0018] To better understand this application, various aspects of this application will be described in more detail with reference to the accompanying drawings.

[0019] To address the technical problems raised in the background art, this application provides a preferred embodiment: The specific content of this embodiment is as follows: like Figure 1 As shown, a metering and monitoring method for multi-type resource access in virtual power plants includes the following specific steps: S1. Obtain data on the environmental magnetic field disturbance, electric field and electromagnetic influence parameters, and performance of the metering equipment at each metering device in the virtual power plant resource access point. In this embodiment, the specific steps of S1 are as follows: S11. Data on the magnetic field disturbance of each metering device at the virtual power plant resource access point includes the core excitation current distortion rate, winding DC resistance deviation rate, increment of insulation dielectric loss tangent, rated operating magnetic flux density, slope coefficient of the core magnetization curve near the inflection point, standard magnetic flux amplitude corresponding to the rated induced electromotive force on the secondary side of the metering device, effective coupling area and number of turns of the winding; the excitation branch current waveform is collected through the Rogowski coil or Hall current sensor connected in series in the secondary circuit of the current transformer, and the total harmonic distortion rate is calculated after fast Fourier transform (the ratio of the sum of the effective values ​​of harmonics other than the fundamental wave to the effective value of the fundamental wave) to obtain the core excitation current distortion rate of each metering device; the temperature sensor built into the metering device monitors the average winding temperature, and the real-time resistance value is converted relative to the factory reference temperature by combining the temperature coefficient of resistance of the copper conductor. The percentage deviation of the resistance value under a given degree is used to obtain the DC resistance deviation rate of the winding; the phase difference tangent of the leakage current and voltage is calculated in real time using the voltage divider signal of the end screen of the capacitive voltage transformer, and the increment of the insulation loss tangent is obtained by subtracting the reference value at the initial stage of operation of the metering equipment; the rated working magnetic flux density of the equipment is obtained from the design data of the metering equipment; the typical magnetization curve is found by the iron core material grade marked on the nameplate of the metering equipment, and the slope value near the inflection point is read from the magnetization curve, which is the slope coefficient of the iron core magnetization curve near the inflection point; the standard magnetic flux amplitude corresponding to the rated induced electromotive force on the secondary side of the metering equipment is calculated by the rated output voltage and output power of the secondary side of the metering equipment; the effective coupling area and number of turns of the winding are the effective iron core cross-sectional area and the number of turns of the secondary winding, which are obtained from the product manual.

[0020] S12. The electric field and electromagnetic influence parameters of the virtual power plant resource access point include the relative projected area of ​​the high-voltage conductor and the casing of each metering device, the minimum distance from the high-voltage conductor to the casing of each metering device, and the voltage of the high-voltage conductor to ground. The spatial relationship between the high-voltage conductor and the metering equipment is determined through the substation primary system wiring diagram, plan layout, or 3D design model. Then, the diameter and length of the high-voltage conductor are obtained from the design drawings or equipment nameplates. The conductor is approximated as a rectangular flat conductor, and its projected area in the direction of the equipment casing is calculated (when there is an angle between the high-voltage conductor and the equipment casing, the effective projected area is taken, i.e., the actual area multiplied by the cosine of the angle). This method is used to obtain the relative projected area between the high-voltage conductor and the casing of each metering device at the virtual power plant resource access point. The design nominal distance is consulted from the distribution equipment layout diagram to obtain the minimum distance from the high-voltage conductor to the casing of each metering device. The voltage of the high-voltage conductor to ground is obtained by multiplying the measured value of the secondary side of the substation bus voltage transformer by the transformation ratio. S13. Performance data for virtual power plant resource access point metering equipment includes the input impedance of each metering device, the trace length of the printed circuit board connecting to high-impedance nodes inside each metering device, the vertical distance from the trace layer to the reference ground plane, the time-varying rate of change of the average electric field intensity inside the metering device, and the equivalent complex impedance modulus between the high-impedance node and the ground plane of the printed circuit board. The input impedance of each metering device is obtained from its product technical manual. The actual trace length connecting to high-impedance nodes (e.g., operational amplifier input, analog-to-digital converter sample-and-hold capacitor pin, reference voltage source output, etc.) is directly measured from the printed circuit board layout diagram in the metering device hardware design file. The trace length connecting to high-impedance nodes on the printed circuit board inside each metering device is obtained in this way. The dielectric thickness between the signal layer containing the trace and the nearest complete reference ground plane is obtained based on the dielectric thickness parameters of each layer marked in the printed circuit board stack-up structure design file. The thickness of the dielectric layer between the surface layers is the vertical distance from the layer where the trace is located to the reference ground plane (for multilayer boards with four or more layers, the vertical distance from the layer where the trace is located to the reference ground plane is the thickness of the core board or prepreg between the signal layer and the adjacent ground layer); based on the miniature fiber optic electric field sensor placed inside the casing of the metering equipment near the high-impedance node trace area, the peak value of the power frequency electric field intensity at that location is measured under normal operating conditions (at the same time, an oscilloscope is needed to verify that the electric field waveform basically conforms to the sine law), and then the corresponding angular frequency value is calculated according to the rated frequency of the power system. The time change rate of the average electric field intensity in the internal space of the metering equipment is obtained by multiplying the measured peak value of the electric field intensity by the angular frequency; by consulting the circuit schematic diagram and component datasheet of the metering equipment, the equivalent parallel network of amplifier input bias resistors, sampling capacitors, protective devices and PCB insulation resistance connected to the high-impedance node is identified, and the equivalent complex impedance modulus between the high-impedance node and the printed circuit board ground layer is calculated based on the nominal values ​​of each component and the capacitive reactance and impedance characteristics at the operating frequency. S14. Store the acquired data in the storage component for use in the analysis process.

[0021] S2. Based on the data on the magnetic field disturbance of each metering device at the virtual power plant resource access point, conduct an environmental impact analysis of each metering device. like Figure 2As shown, in this embodiment, S2 includes the following specific steps: Environmental impact analysis of each metering device is performed based on the core excitation current distortion rate, winding DC resistance deviation rate, increment of insulation dielectric loss tangent, rated operating magnetic flux density, slope coefficient of the core magnetization curve near the inflection point, standard magnetic flux amplitude corresponding to the rated induced electromotive force on the secondary side of the metering device, effective coupling area of ​​the winding, and number of turns. Specifically, the environmental impact analysis process for each metering device is as follows: The core excitation current distortion rate data of each metering device is multiplied by the winding DC resistance deviation rate, and then the increment of the insulation dielectric loss tangent is added to obtain the comprehensive index of internal operational anomalies for each metering device. This comprehensive index is then multiplied by the rated operating magnetic flux density of the device and then by the slope coefficient of the core magnetization curve near the inflection point to obtain the induced magnetic field disturbance intensity of each metering device. Finally, the induced magnetic field disturbance intensity is multiplied by the effective coupling area of ​​the winding and then by the number of turns, and then divided by the standard magnetic flux amplitude corresponding to the rated induced electromotive force on the secondary side of the metering device to obtain the environmental impact analysis results for each metering device. It should be noted that when a normal iron core operates in the linear segment of its magnetization curve, the excitation current is close to a sine wave with extremely low distortion. However, when the permeability of the iron core decreases due to overheating, mechanical vibration, or residual magnetism, the operating point enters the inflection point of the saturation region, and the excitation current exhibits a peaked wave rich in odd harmonics, resulting in increased distortion. The DC resistance deviation rate of the winding reflects the degree of conductor heating and aging, as well as the loosening of connection points. Long-term overload or poor contact in metering equipment can lead to increased resistance, altering the load characteristics of the secondary circuit and thus affecting accuracy. Multiplying this by the excitation current distortion rate in calculations indicates the impact of winding thermal aging on excitation characteristics. The amplification effect of distortion; the increment of the insulation dielectric loss tangent represents the severity of insulation moisture degradation or partial discharge. Increased dielectric loss leads to distortion of the electric field distribution inside the equipment. Simultaneously, leakage current flowing through the core or shielding layer generates an additional unbalanced magnetomotive force in the core, supplementing the internal operating anomaly comprehensive index with magnetic field disturbances caused by non-excitation circuit factors. The internal operating anomaly comprehensive index reflects the degree of equipment state deviation under the combined effects of core magnetic performance degradation, winding conductor heating and aging, and insulation moisture degradation. Rated magnetic flux density is the basis for measuring the intensity of magnetic field disturbances. For reference, the magnetic flux change caused by abnormal operation is scaled proportionally based on the rated magnetic flux density, making the disturbance intensity comparable between different metering devices. The slope coefficient of the core magnetization curve near the inflection point reflects the sensitivity of the core to changes in excitation current in the nonlinear region. When abnormal operation of the equipment causes distortion of the excitation current, the operating point will move near the inflection point. The larger the slope coefficient of the core magnetization curve near the inflection point, the more severe the magnetic flux density disturbance caused by abnormal operation of the equipment. According to Faraday's law of electromagnetic induction, the induced magnetic field disturbance intensity of each metering device is multiplied by the measured... The effective coupling area of ​​the measuring winding is multiplied by the number of turns and then divided by the standard magnetic flux amplitude corresponding to the rated induced electromotive force on the secondary side of the measuring equipment. This yields the amplitude of the additional induced electromotive force generated on the secondary winding by the disturbing magnetic field. The standard magnetic flux amplitude corresponding to the rated induced electromotive force on the secondary side is used as the normalized denominator to convert the additional induced electromotive force into a proportional value relative to the rated magnetic flux. The final environmental impact analysis result for each measuring equipment is a dimensionless coefficient, which reflects the relative degree of influence of internal magnetic field disturbance on measuring accuracy. A larger environmental impact analysis result for the measuring equipment indicates a greater impact on error.

[0022] S3. Based on the electric field and electromagnetic influence parameter data of the virtual power plant resource access point and the performance data of the metering equipment, conduct an analysis of the interference voltage influence of each metering device. like Figure 3 As shown, in this embodiment, the specific steps of S3 are as follows: S31. Calculate the interference voltage generated by the parasitic capacitance coupling of each metering device based on the relative projected area of ​​the high-voltage conductor and the casing of each metering device at the virtual power plant resource access point, the minimum distance from the high-voltage conductor to the casing of each metering device, the voltage of the high-voltage conductor to ground, and the input impedance of each metering device. In this embodiment, the specific steps of S31 are as follows: The interference voltage generated by the parasitic capacitance coupling of each metering device is calculated based on the relative projected area between the high-voltage conductor at the virtual power plant resource access point and the casing of each metering device, the minimum distance from the high-voltage conductor to the casing of each metering device, the voltage of the high-voltage conductor to ground, and the input impedance of each metering device. Specifically, the calculation process for the interference voltage generated by the parasitic capacitance coupling of each metering device is as follows: the relative projected area between the high-voltage conductor at the virtual power plant resource access point and the casing of each metering device is divided by the minimum distance from the high-voltage conductor to the casing of each metering device, and then multiplied by the vacuum dielectric constant to obtain the parasitic capacitance of each metering device; the parasitic capacitance of each metering device is multiplied by the voltage of the high-voltage conductor to ground (i.e., the amplitude of the coupling source voltage, here taken as the phase voltage), the angular frequency of the power frequency electric field, and the magnitude of the input impedance of the metering device (i.e., the equivalent impedance to ground of the coupled port) to obtain the interference voltage generated by the parasitic capacitance coupling of each metering device. It should be noted that the parasitic capacitance coupling interference voltage calculated in this step reflects the amplitude of the common-mode interference component coupled from the high-voltage conductor to the metering equipment casing through the spatial parasitic capacitance; the vacuum dielectric constant is taken as 8.854 × 10⁻⁶. -12 F / m, the angular frequency of the power frequency electric field ω=2πf, where f is the rated frequency of the virtual power plant power system, generally 50Hz or 60Hz; the input impedance magnitude of the metering equipment refers to the equivalent impedance amplitude of the equipment casing to the reference ground plane. When the equipment casing is directly grounded, the grounding loop impedance value is taken; when the casing is floating, the measured value of the distributed impedance of the casing to ground is taken; the nominal phase voltage of the system, as the amplitude of the coupling source voltage, can provide a conservative but reasonable interference estimation benchmark under the condition of lack of real-time voltage monitoring data, ensuring that the analysis results are applicable to most operating conditions; incorporating the grounding state of the equipment casing into the input impedance value can reflect the difference in the transmission efficiency of coupling interference by different grounding methods, avoid the interference voltage calculation value from deviating significantly from reality due to ignoring the grounding impedance, and improve the accuracy of interference source quantitative analysis.

[0023] S32. Calculate the interference voltage generated by the high-resistance nodes of each metering device based on the trace length of the printed circuit board connecting the high-resistance node inside each metering device of the virtual power plant resource access point, the vertical distance from the layer where the trace is located to the reference ground plane, the time change rate of the average electric field intensity inside the metering device, and the equivalent complex impedance modulus between the high-resistance node and the ground layer of the printed circuit board. In this embodiment, the specific steps of S32 are as follows: The interference voltage generated by the high-resistance nodes of each metering device is calculated based on the trace length of the printed circuit board connecting the high-resistance node inside each metering device of the virtual power plant resource access point, the vertical distance from the trace layer to the reference ground plane, the time-varying rate of change of the average electric field strength inside the metering device, and the equivalent complex impedance modulus between the high-resistance node and the ground plane of the printed circuit board. Specifically, the calculation process involves multiplying the trace length of the printed circuit board connecting the high-resistance node and the vertical distance from the trace layer to the reference ground plane to obtain the equivalent projected area of ​​the trace in the vertical electric field direction; multiplying the equivalent projected area of ​​the trace in the vertical electric field direction, the time-varying rate of change of the average electric field strength inside the metering device, and the vacuum dielectric constant to obtain the minute current induced on the trace by the change in the spatial electric field; and multiplying the minute current induced on the trace by the equivalent complex impedance modulus between the high-resistance node and the ground plane of the printed circuit board to obtain the interference voltage generated by the high-resistance node of each metering device. It should be noted that in this step, the final result of the high-impedance node interference voltage reflects the differential-mode or common-mode interference voltage component induced by the traces connected to the high-impedance nodes on the printed circuit board inside the metering equipment in the time-varying spatial electric field; the product of the trace length and the interlayer spacing represents the effective projected area of ​​the trace in the direction perpendicular to the electric field, and its product with the rate of change of the spatial electric field, combined with the vacuum dielectric constant, yields the trace-induced displacement current; extending the interference coupling path from the macroscopic structure outside the equipment to the microscopic trace level of the circuit board inside the equipment, while paying attention to the external electromagnetic environment, the blank of the induced effect of the internal sensitive nodes is not ignored; by quantifying the product of the high-impedance node induced current and impedance, the weak points inside the equipment that are susceptible to interference can be accurately reflected, reducing the risk of implicit metering deviations caused by defects in the internal circuit layout.

[0024] S33. Analyze the impact of interference voltage on each metering device based on the interference voltage generated by parasitic capacitance coupling and the interference voltage generated by high-resistance nodes. like Figure 4 As shown, in this embodiment, the specific steps of S33 are as follows: obtain the interference voltage generated by the parasitic capacitance coupling of each metering device and the interference voltage generated by the high-resistance node; add the interference voltage magnitude generated by the parasitic capacitance coupling of each metering device and the interference voltage magnitude generated by the high-resistance node to obtain the common-mode interference voltage experienced by each metering device; divide the common-mode interference voltage experienced by each metering device by the product of the common-mode rejection ratio and the rated voltage of each metering device to obtain the interference voltage impact analysis results of each metering device. It should be noted that the magnitudes of parasitic capacitive coupling interference voltage and high-impedance node induced interference voltage are superimposed in phase to quickly synthesize the comprehensive effect of multiple interference sources. This avoids the complex vector synthesis uncertainty caused by the difficulty in obtaining phase information, and provides consistent and robust interference assessment results for batch equipment evaluation in the scenario of multiple access points in virtual power plants. The interference voltage is normalized with the common-mode rejection ratio and rated voltage, so that the analysis results of different metering devices are comparable horizontally, which facilitates the subsequent selection of the optimal metering device based on a unified scale.

[0025] S4. Based on the environmental impact analysis results and interference voltage impact analysis results of each metering device at the virtual power plant resource access point, conduct an accuracy analysis of each metering device. In this embodiment, the specific steps of S4 are as follows: obtain the environmental impact analysis results and interference voltage impact analysis results of each metering device at the virtual power plant resource access point, and add the weighted environmental impact analysis results and interference voltage impact analysis results of each metering device to obtain the accuracy analysis results of each metering device; It should be noted that by integrating the effects of internal magnetic field disturbances and external electromagnetic interference, the true performance of metering equipment under the coupling of multiple physical fields is comprehensively characterized. This provides scientific decision-making support for the accurate matching of metering equipment at each resource access point of the virtual power plant, ensuring the quality of the measurement data foundation upon which the coordinated regulation of the virtual power plant's source-grid-load-storage system relies. A smaller value in the metering equipment accuracy analysis indicates better overall performance and more reliable metering output under the environmental and electromagnetic conditions at that access point. Weighting method: When the access point is located in an open outdoor environment (e.g., outdoor transformer substations, pole-mounted transformer areas, rooftop photovoltaic junction points, etc.), and the metering equipment has been in operation for more than five years or shows signs of insulation aging during inspections, the magnetic field disturbances caused by abnormal operation such as core magnetic degradation and winding insulation deterioration constitute the dominant factor affecting metering accuracy. In this case, the environmental impact analysis result is weighted at 0.6. The weight of the environmental impact analysis result is 0.7, and the weight of the interference voltage impact analysis result is 0.3 to 0.4 (when the equipment has been in operation for more than eight years or the environment is in a high temperature and high humidity environment all year round, the weight of the environmental impact analysis result is the upper limit of 0.7, and the weight of the interference voltage impact analysis result is 0.3); when the access point is located in a strong electromagnetic interference area (such as the high voltage distribution equipment bay of the substation, the area near the high power frequency converter or reactor room, the area near the electrified railway traction station, etc.) or the metering equipment is newly put into operation and in good internal condition, the interference voltage generated by the external electric field coupling and the internal circuit board induction constitutes the dominant factor affecting the metering accuracy. In this case, the weight of the environmental impact analysis result is 0.3 to 0.4, and the weight of the interference voltage impact analysis result is 0.6 to 0.7 (when the access point is near the high voltage bus and there is no shielding measure, the weight of the environmental impact analysis result is 0.3, and the weight of the interference voltage impact analysis result is the upper limit of 0.7).

[0026] S5. Based on the accuracy analysis results of each metering device at the virtual power plant resource access point, select suitable metering devices for each virtual power plant resource access point.

[0027] In this embodiment, the specific steps of S5 are as follows: obtain the accuracy analysis results of each metering device at the virtual power plant resource access point, sort the accuracy analysis results of each metering device in ascending order, record the metering device corresponding to the accuracy analysis result ranked first as the most accurate metering device for the virtual power plant resource access point, configure the most accurate metering device of each resource access point of the virtual power plant to the corresponding access point, read the metering value provided by the device, and use it as the final metering result of the virtual power plant resource access point, and select suitable metering devices for each resource access point of the virtual power plant in this way; It should be noted that the virtual power plant aggregates various power resources such as distributed photovoltaics, wind turbines, energy storage systems, controllable loads, and charging piles. These resources are physically dispersed and located in environments with vastly different characteristics (e.g., high temperature and humidity, salt spray, strong vibration). Furthermore, the electromagnetic environment at the grid connection point is complex (e.g., inverter harmonic interference, transient overvoltage during switching operations). These factors make the virtual power plant highly susceptible to environmental disturbances or measurement errors by the equipment itself, which can lead to deviations in dispatching instructions and inaccurate settlement data. Therefore, it is essential to select metering equipment with the least interference at each resource access point of the virtual power plant to ensure the quality of the measurement data foundation upon which the coordinated regulation of the virtual power plant's source, grid, load, and storage depends.

[0028] Based on the above implementation, this embodiment has the following advantages over the prior art: This embodiment acquires data on the environmental magnetic field disturbance, electric field and electromagnetic influence parameters, and performance data of each metering device at the virtual power plant resource access point; it performs environmental impact analysis on each metering device based on the environmental magnetic field disturbance data; it performs interference voltage impact analysis on each metering device based on the electric field and electromagnetic influence parameter data and performance data of the virtual power plant resource access point; it performs accuracy analysis on each metering device based on the environmental impact analysis results and interference voltage impact analysis results; it selects suitable metering devices for each virtual power plant resource access point based on the accuracy analysis results; and it achieves a quantitative representation of the degree of stray magnetic field disturbance caused by internal state deviations such as long-term aging and insulation deterioration of the metering device by integrating and calculating multiple source state parameters such as core excitation current distortion rate, winding DC resistance deviation rate, and insulation dielectric loss tangent increment, thus truly reflecting the equipment's internal state deviation. The system addresses the implicit impact of the device's own health status on metering accuracy. It quantifies the capacitive coupling effect of external high-voltage circuits on the device casing by introducing parameters such as the relative projected area of ​​the high-voltage conductor and the device casing, minimum distance, voltage to ground, and input impedance. It then quantifies the electromagnetic induction effect of the internal electric field on sensitive signal traces by introducing parameters such as the trace length of high-resistance nodes on printed circuit boards, interlayer spacing, electric field change rate, and equivalent complex impedance modulus. These two parameters are combined to form a common-mode interference voltage, which is then normalized and evaluated using the common-mode rejection ratio. This comprehensively covers the entire electromagnetic interference transmission chain from the external primary system to the internal secondary weak-voltage circuit, making the analysis results more comprehensive and accurate. The environmental impact analysis results are weighted and fused with the interference voltage impact analysis results to generate accuracy analysis results for each metering device under the actual operating conditions at the current access point. Based on these results, candidate metering devices are ranked in ascending order, and the device with the highest accuracy is selected and configured at the corresponding access point. This reduces the risk of data deviation caused by incompatibility between the metering device and the on-site electromagnetic and operating environment, improving the accuracy and reliability of the overall monitoring data of the virtual power plant.

[0029] The specific steps for each unit module to implement its corresponding function in the metering and monitoring method for multi-type resource access of virtual power plants described above can be found in the embodiments of the metering and monitoring method for multi-type resource access of virtual power plants described above, and will not be repeated here.

[0030] The above description is merely a preferred embodiment of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of this application is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the foregoing application concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features with similar functions claimed in this application.

Claims

1. A metering and monitoring method for multi-type resource access in virtual power plants, characterized in that, include: S1. Obtain data on the environmental magnetic field disturbance, electric field and electromagnetic influence parameters, and performance of the metering equipment at each metering device in the virtual power plant resource access point. S2. Based on the data on the magnetic field disturbance of each metering device at the virtual power plant resource access point, conduct an environmental impact analysis of each metering device. S3. Based on the electric field and electromagnetic influence parameter data of the virtual power plant resource access point and the performance data of the metering equipment, conduct an analysis of the interference voltage influence of each metering device. S4. Based on the environmental impact analysis results and interference voltage impact analysis results of each metering device at the virtual power plant resource access point, conduct an accuracy analysis of each metering device. S5. Based on the accuracy analysis results of each metering device at the virtual power plant resource access point, select suitable metering devices for each virtual power plant resource access point.

2. The metering and monitoring method for multi-type resource access in virtual power plants as described in claim 1, characterized in that, S2 includes the following specific steps: Environmental impact analysis of each metering device is conducted based on the core excitation current distortion rate, winding DC resistance deviation rate, increment of insulation loss tangent, rated operating magnetic flux density, slope coefficient of the core magnetization curve near the inflection point, standard magnetic flux amplitude corresponding to the rated induced electromotive force on the secondary side of the metering device, effective coupling area of ​​the winding, and number of turns. Specifically, the environmental impact analysis process for each metering device is as follows: The core excitation current distortion rate data of each metering device is multiplied by the winding DC resistance deviation rate, and then the increment of the insulation loss tangent is added to obtain the comprehensive index of internal operational anomalies for each metering device. This comprehensive index is then multiplied by the rated operating magnetic flux density of the device and then by the slope coefficient of the core magnetization curve near the inflection point to obtain the induced magnetic field disturbance intensity of each metering device. Finally, the induced magnetic field disturbance intensity is multiplied by the effective coupling area of ​​the winding and then by the number of turns, and then divided by the standard magnetic flux amplitude corresponding to the rated induced electromotive force on the secondary side of the metering device to obtain the environmental impact analysis results for each metering device.

3. The metering and monitoring method for multi-type resource access in virtual power plants as described in claim 2, characterized in that, The specific steps of S3 are as follows: S31. Calculate the interference voltage generated by the parasitic capacitance coupling of each metering device based on the relative projected area of ​​the high-voltage conductor and the casing of each metering device at the virtual power plant resource access point, the minimum distance from the high-voltage conductor to the casing of each metering device, the voltage of the high-voltage conductor to ground, and the input impedance of each metering device. S32. Calculate the interference voltage generated by the high-resistance nodes of each metering device based on the trace length of the printed circuit board connecting the high-resistance node inside each metering device of the virtual power plant resource access point, the vertical distance from the layer where the trace is located to the reference ground plane, the time change rate of the average electric field intensity inside the metering device, and the equivalent complex impedance modulus between the high-resistance node and the ground layer of the printed circuit board. S33. Analyze the impact of interference voltage on each metering device based on the interference voltage generated by parasitic capacitance coupling and the interference voltage generated by high-resistance nodes.

4. The metering and monitoring method for multi-type resource access in virtual power plants as described in claim 3, characterized in that, The specific steps of S31 are as follows: The interference voltage generated by the parasitic capacitance coupling of each metering device is calculated based on the relative projected area between the high-voltage conductor at the virtual power plant resource access point and the casing of each metering device, the minimum distance from the high-voltage conductor to the casing of each metering device, the voltage of the high-voltage conductor to ground, and the input impedance of each metering device. Specifically, the calculation process for the interference voltage generated by the parasitic capacitance coupling of each metering device is as follows: the relative projected area between the high-voltage conductor at the virtual power plant resource access point and the casing of each metering device is divided by the minimum distance from the high-voltage conductor to the casing of each metering device, and then multiplied by the vacuum dielectric constant to obtain the parasitic capacitance of each metering device; the parasitic capacitance of each metering device is multiplied by the voltage of the high-voltage conductor to ground, the angular frequency of the power frequency electric field, and the magnitude of the input impedance of the metering device to obtain the interference voltage generated by the parasitic capacitance coupling of each metering device.

5. A metering and monitoring method for multi-type resource access in virtual power plants as described in claim 4, characterized in that, The specific steps of S32 are as follows: The interference voltage generated by the high-resistance nodes of each metering device is calculated based on the trace length of the printed circuit board connecting the high-resistance node inside each metering device of the virtual power plant resource access point, the vertical distance from the trace layer to the reference ground plane, the time-varying rate of change of the average electric field strength inside the metering device, and the equivalent complex impedance modulus between the high-resistance node and the ground plane of the printed circuit board. Specifically, the calculation process involves multiplying the trace length of the printed circuit board connecting the high-resistance node and the vertical distance from the trace layer to the reference ground plane to obtain the equivalent projected area of ​​the trace in the vertical electric field direction; multiplying the equivalent projected area of ​​the trace in the vertical electric field direction, the time-varying rate of change of the average electric field strength inside the metering device, and the vacuum dielectric constant to obtain the minute current induced on the trace by the change in the spatial electric field; and multiplying the minute current induced on the trace by the equivalent complex impedance modulus between the high-resistance node and the ground plane of the printed circuit board to obtain the interference voltage generated by the high-resistance node of each metering device.

6. The metering and monitoring method for multi-type resource access in virtual power plants as described in claim 5, characterized in that, The specific steps of S33 are as follows: obtain the interference voltage generated by the parasitic capacitance coupling of each metering device and the interference voltage generated by the high-resistance node; add the interference voltage magnitude generated by the parasitic capacitance coupling of each metering device and the interference voltage magnitude generated by the high-resistance node to obtain the common-mode interference voltage of each metering device; divide the common-mode interference voltage of each metering device by the product of the common-mode rejection ratio and the rated voltage of each metering device to obtain the interference voltage impact analysis results of each metering device.

7. A metering and monitoring method for multi-type resource access in virtual power plants as described in claim 6, characterized in that, The specific steps of S4 are as follows: obtain the environmental impact analysis results and interference voltage impact analysis results of each metering device at the virtual power plant resource access point, and add the weighted environmental impact analysis results and interference voltage impact analysis results of each metering device to obtain the accuracy analysis results of each metering device.

8. A metering and monitoring method for multi-type resource access in virtual power plants as described in claim 7, characterized in that, The specific steps of S5 are as follows: obtain the accuracy analysis results of each metering device at the virtual power plant resource access point, sort the accuracy analysis results of each metering device in ascending order, record the metering device corresponding to the first accuracy analysis result as the most accurate metering device for that virtual power plant resource access point, configure the most accurate metering device of each virtual power plant resource access point to the corresponding access point, read the metering value provided by the device, and use it as the final metering result of that virtual power plant resource access point, and select suitable metering devices for each virtual power plant resource access point in this way.

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