A cloud-edge collaborative metering monitoring system and method

Abstract

The present invention discloses a cloud-edge collaborative metering monitoring system and method, which belongs to the field of metrology calibration. The system of the present invention includes: an acquisition unit, connected to a mutual inductor, to acquire voltage data and current data at the high-voltage end of the power grid side of a substation; a communication unit, receiving voltage data and current data at the high-voltage end of the power grid side, and transmitting a self-monitoring signal to a self-monitoring module; a self-monitoring module, measuring voltage data and current data according to the self-monitoring signal, comparing the acquired voltage data and current data with the measured voltage data and current data, and obtaining a self-monitoring evaluation result; a metering monitoring unit, evaluating the self-monitoring evaluation result. The present invention can realize accurate monitoring of errors in digital metering equipment of substations, and provide intelligent operation and maintenance solutions for metering systems for substation managers.

Description

Technical Field

[0001] The present invention relates to the field of metrology and calibration, and more specifically, to a cloud-edge collaborative metrology monitoring system. Background Art

[0002] State Grid Corporation of China has built over 4,000 smart substations, and these are now widely used in various sectors, including power grids, power plants, and railways. However, digital metering systems, typically comprised of electronic transformers, merging units, and digital energy meters, still serve only as measurement points for assessment purposes in smart substations. They have not replaced traditional analog metering systems as instruments for electricity bill settlement. This limitation is primarily due to the need to improve the reliability of digital metering systems.

[0003] With the development trend of digitalization, digital metering systems are widely used in smart substations with technical features such as digital measurement, functional integration, and communication networking. Digital metering systems contain a large number of electronic components. The high voltage and strong electromagnetic characteristics of substations can easily cause component failures, resulting in reduced system reliability. In order to improve the measurement accuracy and operational reliability of digital metering systems, the China Electric Power Research Institute has carried out research on self-monitoring technology. However, if self-monitoring technology is only applied to a single device, it will face the problem of how to ensure the reliability of the self-monitoring technology itself, which has led to the failure of the technology to be promoted. Therefore, the present invention establishes a cloud-edge collaborative management system based on self-monitoring technology to effectively solve the problem of doubts about the reliability of the self-monitoring technology itself. Summary of the Invention

[0004] The present invention proposes a cloud-edge collaborative metering monitoring system to achieve remote management of the metering system of a smart substation, including:

[0005] The acquisition unit is connected to the transformer to collect voltage and current data at the high-voltage end of the substation grid side;

[0006] The communication unit receives the voltage and current data from the high-voltage terminal of the grid side and transmits the self-monitoring signal to the self-monitoring module;

[0007] a self-monitoring module, which measures voltage data and current data according to a self-monitoring signal, compares the collected voltage data and current data with the measured voltage data and current data, and obtains a self-monitoring evaluation result;

[0008] The metrological monitoring unit evaluates the self-monitoring evaluation results.

[0009] Optionally, the metering monitoring unit is set in a metering center or a centralized control station.

[0010] Optionally, the metering monitoring unit and the self-monitoring module are arranged in an N+1 mode, specifically one metering monitoring unit manages N self-monitoring modules.

[0011] Optionally, the self-monitoring module includes: a reference signal generator and a self-monitoring chip.

[0012] The present invention also proposes a digital metering monitoring method suitable for cloud-edge collaboration, including:

[0013] Collect voltage and current data at the high-voltage end of the substation grid side;

[0014] measuring voltage data and current data according to the self-monitoring signal, comparing the collected voltage data and current data with the measured voltage data and current data, and obtaining a self-monitoring evaluation result;

[0015] The present invention can realize accurate error monitoring of digital metering equipment in substations and provide substation managers with an intelligent operation and maintenance solution for the metering system. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a structural diagram of a cloud-edge collaborative metering and monitoring system of the present invention;

[0017] Figure 2 This is the architecture diagram of the wired transmission cloud-edge collaborative substation digital metering system of the present invention;

[0018] Figure 3 This is the architecture diagram of the cloud-edge collaborative substation digital metering system with wireless transmission of the present invention;

[0019] Figure 4 This is a diagram showing the architecture of the self-monitoring module of the local digital metering equipment of the present invention;

[0020] Figure 5 The cloud-edge collaborative electric energy metering and monitoring method of the present invention;

[0021] Figure 6 This is the cloud-edge collaborative algorithm based on self-monitoring technology of the present invention;

[0022] Figure 7 This is a flow chart of a cloud-edge collaborative metering monitoring method of the present invention. DETAILED DESCRIPTION

[0023] Exemplary embodiments of the present invention will now be described with reference to the accompanying drawings. However, the present invention may be embodied in many different forms and is not limited to the embodiments described herein. These embodiments are provided to provide a thorough and complete disclosure of the present invention and to fully convey the scope of the present invention to those skilled in the art. The terminology used in the exemplary embodiments shown in the accompanying drawings is not intended to limit the present invention. In the accompanying drawings, identical elements are denoted by the same reference numerals.

[0024] Unless otherwise specified, the terms used herein (including technical terms) have the meanings commonly understood by those skilled in the art. In addition, it is understood that terms defined in commonly used dictionaries should be understood to have the same meanings as those in the context of the relevant fields, and should not be understood as idealized or overly formal meanings.

[0025] The present invention proposes a cloud-edge collaborative metering monitoring system 100, such as Figure 1 Shown, including:

[0026] The acquisition unit 101 is connected to the transformer to collect voltage and current data at the high-voltage end of the substation grid side;

[0027] The communication unit 102 receives voltage and current data from the high-voltage terminal of the grid side and transmits a self-monitoring signal to the self-monitoring module;

[0028] The self-monitoring module 103 measures voltage data and current data according to the self-monitoring signal, compares the collected voltage data and current data with the measured voltage data and current data, and obtains a self-monitoring evaluation result;

[0029] The metering monitoring unit 104 evaluates the self-monitoring evaluation results.

[0030] Among them, the metering monitoring unit is set in the metering center or centralized control station.

[0031] The metering monitoring unit and the self-monitoring module are arranged in an N+1 mode, specifically one metering monitoring unit manages N self-monitoring modules.

[0032] The self-monitoring module includes: a reference signal generator and a self-monitoring chip.

[0033] The present invention will be further described below in conjunction with embodiments:

[0034] Figure 2 This is a digital metering and monitoring system implemented according to the present invention, using wired transmission within the substation's intranet. The data transmission chain is as follows: voltage and current transformers transmit data to a merging unit, where a self-monitoring module is connected in parallel and transmits the data to a digital energy meter. Within the substation, an energy acquisition terminal or energy controller transmits the data via the dispatching data network to the TMR system. Remotely, the dispatcher pushes the data to a remote energy metering, monitoring, and analysis system. Finally, the data analysis results are pushed to the substation's application server via the integrated data network, providing an intelligent operation and maintenance solution for substation managers.

[0035] Figure 3 The present invention is a digital metering and monitoring system implemented through wireless transmission in the substation network. Figure 3As shown in Figure 1, a self-monitoring module with wireless transmission is added to the merging unit. Figure 1 Unlike wired transmission, wireless transmission is not restricted by the fiber optic cabling and connection ports of the substation. The self-monitoring module of the merging unit can receive remote data analysis results, modify monitoring parameters, and ensure the accuracy of monitoring results.

[0036] Figure 4 In the self-monitoring module implemented according to the present invention, a reference signal source is connected in parallel to a traditional metering link, a standard signal is injected through the reference signal, and after the standard signal is distinguished by Fourier transform, a signal detection module is used to determine whether the sampling size of the standard signal after analog-to-digital conversion in the traditional metering link meets the requirements.

[0037] The self-monitoring evaluation method for the merged unit is as follows:

[0038]

[0039]

[0040] In formula 1, V A For the evaluation of the amplitude of the electrical parameters by self-monitoring technology, A LINE Read the self-monitoring signal amplitude for the traditional metering loop, A SS is the standard amplitude of the self-monitoring signal, and k is the ratio difference evaluation adjustment coefficient. is the evaluation of the phase of the electrical parameters by the self-monitoring technology, f LINE The self-calibration signal frequency read by the traditional measurement loop after analog-to-digital conversion, f DSP is the self-calibration signal frequency after analog-to-digital conversion, is the phase adjustment coefficient, and k is the angle difference evaluation adjustment coefficient.

[0041] Figure 5 and Figure 6 This is a cloud-edge collaborative monitoring method implemented according to the present invention. Station-side self-monitoring evaluates the phase and amplitude of the merging unit and simultaneously analyzes local self-calibration data. The theoretical analysis of self-monitoring data is based on the following: Given a sufficient number of merging unit samples for substation self-monitoring, the average error evaluation of the merging unit self-monitoring will approach a true value, representing the actual trend of the merging unit phase and amplitude.

[0042] The substation self-monitoring technology evaluation matrix is ​​as follows, where the self-monitoring amplitude evaluation matrix is ​​as shown in formula (3), and the self-monitoring phase evaluation matrix is ​​as shown in formula (4). For substations that cannot form a matrix, the mean value is used to complete the matrix:

[0043]

[0044]

[0045] In formula 3 is the evaluation value of the amplitude by the self-monitoring technology of the j-th merging unit of the i-th substation, where is the evaluation value of the phase by the self-monitoring technology of the j-th merging unit in the i-th substation.

[0046] The method for judging the true value of the self-monitoring theory is as follows:

[0047]

[0048]

[0049] In formula 5, V A is the amplitude evaluation value of the self-monitoring technology, N 11 to N 1n is the amplitude self-monitoring value of the first substation 1 to n merging units, N k1 to N kn is the amplitude self-monitoring value of the merging unit 1 to n in the k-th substation. is the evaluation value of the phase by the self-monitoring technology, N 11 to N 1n is the phase self-monitoring value of the merging units 1 to n in the first substation, N k1 to N kn is the phase self-monitoring value of merging units 1 to n in the k-th substation.

[0050] When the difference between the calculated value of a merging unit self-monitoring in the substation and the true value is greater than the set threshold, it is considered that there may be an error in the self-monitoring of this merging unit and a mark is made.

[0051] Cloud calibration is performed based on the inter-substation loss constraint analysis. The inter-station line loss is calculated using Equation 7:

[0052]

[0053] In formula 7, R is the line resistance per unit length, L is the line length, and ΔP M is the difference in total active meter reading power, ΔP T is the active power loss, ΔQ M is the difference in total reactive power reading, ΔQ T is the reactive loss, U0 is the rated voltage, and T is the system operating time.

[0054] When the calculated amount of electric energy measured by the digital electric energy meter after self-calibration between substations is greater than the line loss threshold, it is determined that the measurement of the merging unit after self-monitoring is still abnormal and a secondary mark is performed.

[0055] When a merging unit is marked once by the local self-monitoring technology and standardized twice by the cloud-edge big data technology, it is considered that there may be an abnormality in the self-monitoring of the merging unit. The self-monitoring function of the merging unit is restarted again, and the parameters are adjusted to make the self-monitoring evaluation value of the merging unit closer to the mean.

[0056] With the development of digitalization and intelligence of power grids, the cloud-edge collaborative monitoring form proposed in this invention improves the evaluation credibility of the digital metering and monitoring system, and can ensure the accuracy and reliability of online monitoring.

[0057] The present invention also proposes a digital metering monitoring method suitable for cloud-edge collaboration, such as Figure 7 Shown, including:

[0058] Collect voltage and current data at the high-voltage end of the substation grid side;

[0059] measuring voltage data and current data according to the self-monitoring signal, comparing the collected voltage data and current data with the measured voltage data and current data, and obtaining a self-monitoring evaluation result;

[0060] Evaluate the self-monitoring evaluation results based on the obtained self-monitoring evaluation results.

[0061] The present invention can realize accurate error monitoring of digital metering equipment in substations and provide substation managers with an intelligent operation and maintenance solution for the metering system.

[0062] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code. The scheme in the embodiment of the present application can be implemented in various computer languages, for example, object-oriented programming language Java and literal translation scripting language JavaScript, etc.

[0063] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0064] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0065] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0066] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present application.

[0067] Obviously, those skilled in the art may make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application is intended to include these modifications and variations.

Claims

1. A cloud-edge collaborative metering monitoring system, comprising: The acquisition unit is connected to the transformer to collect voltage and current data at the high-voltage end of the substation grid side; The communication unit receives the voltage and current data from the high-voltage terminal of the grid side and transmits the self-monitoring signal to the self-monitoring module; a self-monitoring module, which measures voltage data and current data according to a self-monitoring signal, compares the collected voltage data and current data with the measured voltage data and current data, and obtains a self-monitoring evaluation result; The metrology monitoring unit evaluates the self-monitoring evaluation results; The monitoring and evaluation methods are as follows: In formula 1, V A For the evaluation of the amplitude of the electrical parameters by self-monitoring technology, A LINE Read the self-monitoring signal amplitude for the traditional metering loop, A SS is the standard amplitude of the self-monitoring signal, k is the ratio difference evaluation adjustment coefficient, and in Formula 2 is the evaluation of the phase of the electrical parameters by the self-monitoring technology, f LINE The self-calibration signal frequency read by the traditional measurement loop after analog-to-digital conversion, f DSP is the self-calibration signal frequency after analog-to-digital conversion, is the phase adjustment coefficient, k is the angle difference evaluation adjustment coefficient; Station-side self-monitoring completes the evaluation of the merging unit phase and amplitude, and also completes the local-side self-calibration data analysis. The theoretical analysis of self-monitoring data is based on the following: when there are enough samples of the substation self-monitoring merging unit, the average error evaluation value of the merging unit self-monitoring will infinitely approach a true value. This true value is the actual change trend of the merging unit phase and amplitude. The substation self-monitoring technology evaluation matrix is ​​as follows, where the self-monitoring amplitude evaluation matrix is ​​as shown in formula (3), and the self-monitoring phase evaluation matrix is ​​as shown in formula (4). For substations that cannot form a matrix, the mean value is used to complete the matrix: In formula 3 is the evaluation value of the amplitude by the self-monitoring technology of the j-th merging unit of the i-th substation, where is the evaluation value of the phase by the self-monitoring technology of the j-th merging unit in the i-th substation; The method for judging the true value of the self-monitoring theory is as follows: In formula 5, V A is the amplitude evaluation value of the self-monitoring technology, N 11 to N 1n is the amplitude self-monitoring value of the first substation 1 to n merging units, N k1 to N kn is the amplitude self-monitoring value of the merging units 1 to n in the k-th substation, where is the evaluation value of the phase by the self-monitoring technology, N 11 to N 1n is the phase self-monitoring value of the merging units 1 to n in the first substation, N k1 to N kn is the phase self-monitoring value of merging units 1 to n in the k-th substation; When the difference between the calculated value of a merging unit self-monitoring and the true value in the substation is greater than the set threshold, it is considered that there may be an error in the self-monitoring of this merging unit and a mark is made; Cloud calibration is performed based on the inter-substation loss constraint analysis. The inter-station line loss is calculated using Equation 7: In formula 7, R is the line resistance per unit length, L is the line length, and ΔP M is the difference in total active meter reading power, ΔP T is the active power loss, ΔQ M is the difference in total reactive power reading, ΔQ T is the reactive loss, U0 is the rated voltage, and T is the system operation time; When the calculated amount of electric energy measured by the digital electric energy meter after self-calibration between substations is greater than the line loss threshold, it is judged that the measurement of the merging unit after self-monitoring is still abnormal and a secondary mark is performed; When a merging unit is marked once by the local self-monitoring technology and standardized twice by the cloud-edge big data technology, it is considered that there may be an abnormality in the self-monitoring of the merging unit. The self-monitoring function of the merging unit is restarted again, and the parameters are adjusted to make the self-monitoring evaluation value of the merging unit closer to the mean.

2. According to the system of claim 1, the metering monitoring unit is set in a metering center or a centralized control station.

3. The system according to claim 1, wherein the metering monitoring unit and the self-monitoring module are arranged in an N+1 mode, specifically one metering monitoring unit manages N self-monitoring modules.

4. The system according to claim 1, wherein the self-monitoring module comprises: Reference signal generator and self-monitoring chip.

5. A cloud-edge collaborative metering monitoring method, the method comprising: Collect voltage and current data at the high-voltage end of the substation grid side; measuring voltage data and current data according to the self-monitoring signal, comparing the collected voltage data and current data with the measured voltage data and current data, and obtaining a self-monitoring evaluation result; Evaluate the self-monitoring and evaluation results based on the obtained self-monitoring and evaluation results; The monitoring and evaluation methods are as follows: In formula 1, V A For the evaluation of the amplitude of the electrical parameters by self-monitoring technology, A LINE Read the self-monitoring signal amplitude for the traditional metering loop, A SS is the standard amplitude of the self-monitoring signal, k is the ratio difference evaluation adjustment coefficient, and in Formula 2 is the evaluation of the phase of the electrical parameters by the self-monitoring technology, f LINE The self-calibration signal frequency read by the traditional measurement loop after analog-to-digital conversion, f DSP is the self-calibration signal frequency after analog-to-digital conversion, is the phase adjustment coefficient, k is the angle difference evaluation adjustment coefficient; Station-side self-monitoring completes the evaluation of the merging unit phase and amplitude, and also completes the local-side self-calibration data analysis. The theoretical analysis of self-monitoring data is based on the following: when there are enough samples of the substation self-monitoring merging unit, the average error evaluation value of the merging unit self-monitoring will infinitely approach a true value. This true value is the actual change trend of the merging unit phase and amplitude. The substation self-monitoring technology evaluation matrix is ​​as follows, where the self-monitoring amplitude evaluation matrix is ​​as shown in formula (3), and the self-monitoring phase evaluation matrix is ​​as shown in formula (4). For substations that cannot form a matrix, the mean value is used to complete the matrix: In formula 3 is the evaluation value of the amplitude by the self-monitoring technology of the j-th merging unit of the i-th substation, where is the evaluation value of the phase by the self-monitoring technology of the j-th merging unit in the i-th substation; The method for judging the true value of the self-monitoring theory is as follows: In formula 5, V A is the amplitude evaluation value of the self-monitoring technology, N 11 to N 1n is the amplitude self-monitoring value of the first substation 1 to n merging units, N k1 to N kn is the amplitude self-monitoring value of the merging units 1 to n in the k-th substation, where is the evaluation value of the phase by the self-monitoring technology, N 11 to N 1n is the phase self-monitoring value of the merging units 1 to n in the first substation, N k1 to N kn is the phase self-monitoring value of merging units 1 to n in the k-th substation; When the difference between the calculated value of a merging unit self-monitoring and the true value in the substation is greater than the set threshold, it is considered that there may be an error in the self-monitoring of this merging unit and a mark is made; Cloud calibration is performed based on the inter-substation loss constraint analysis. The inter-station line loss is calculated using Equation 7: In formula 7, R is the line resistance per unit length, L is the line length, and ΔP M is the difference in total active meter reading power, ΔP T is the active power loss, ΔQ M is the difference in total reactive power reading, ΔQ T is the reactive loss, U0 is the rated voltage, and T is the system operation time; When the calculated amount of electric energy measured by the digital electric energy meter after self-calibration between substations is greater than the line loss threshold, it is judged that the measurement of the merging unit after self-monitoring is still abnormal and a secondary mark is performed; When a merging unit is marked once by the local self-monitoring technology and standardized twice by the cloud-edge big data technology, it is considered that there may be an abnormality in the self-monitoring of the merging unit. The self-monitoring function of the merging unit is restarted again, and the parameters are adjusted to make the self-monitoring evaluation value of the merging unit closer to the mean.

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