Method and device for calculating corrected electric quantity of electric energy meter, electronic equipment and storage medium

Abstract

The invention provides an electric energy meter correction electric quantity calculation method and device, electronic equipment and a storage medium. The method comprises the steps of obtaining metering historical data of a target electric energy meter; analyzing the metering historical data by adopting a phase angle feature portrait algorithm, and identifying a wiring error type corresponding to the target electric energy meter; determining a corresponding correction transformation matrix based on the wiring error type; and calculating the corrected electric quantity of the target electric energy meter based on the corrected transformation matrix. The invention provides a novel calculation scheme for the corrected electric quantity of the electric energy meter, the corrected electric quantity of the electric energy meter is calculated more accurately by adopting an advanced algorithm and a mathematical model, the interference of human factors is reduced, various complex wiring error conditions can be adapted, and the calculation efficiency is improved. Therefore, the accuracy and reliability of the correction electric quantity calculation method of the electric energy meter of the power system are improved.

Description

Technical Field

[0001] The present application relates to the field of electric power calculation technology, and in particular to a method, device, electronic device and storage medium for calculating corrected electric power of an electric energy meter. Background Art

[0002] With the continuous expansion and intelligence of the power system, the accuracy of the energy meter, as a key device for measuring the energy consumed by power equipment, is crucial to both power suppliers and consumers. However, in practical applications, the wiring error of the energy meter is a common problem, which will lead to inaccurate energy measurement, thus affecting the fairness of power transactions and the economic benefits of the power system.

[0003] At present, the method widely used by power supply companies to calculate the amount of electricity corrected for incorrect wiring of electric energy meters is the "correction coefficient method". This method is based on the ideal working model of electric energy meters and corrects the metering deviation caused by incorrect wiring by calculating a correction coefficient, where the correction coefficient is obtained by comparing the correct power and the incorrect power, and then the coefficient is used to calculate the amount of electricity to be compensated or refunded.

[0004] However, the existing corrected power calculation method has some limitations: it is mainly applicable to the case of three-phase load balance, and its correction effect is not good for unbalanced loads or special wiring methods; in addition, under certain types of wiring errors, such as current and voltage not corresponding, the correction coefficient may not be calculated, resulting in the inability to obtain effective corrected power. At the same time, since the calculation of the correction coefficient depends on the selection of the average power factor, different choices may lead to significant differences in the correction value, which increases the influence of human factors and reduces the reliability of the calculation results. It can be seen that the existing corrected power calculation method has low accuracy and reliability, and poor applicability.

[0005] The preceding description is intended to provide general background information and does not necessarily constitute prior art. Summary of the invention

[0006] In response to the above technical problems, the present application provides a method, device, electronic device and storage medium for calculating the corrected electricity quantity of an electric energy meter, which solves the problems of low accuracy and low reliability in the prior art, more accurately calculates the corrected electricity quantity of the electric energy meter, reduces interference from human factors, and can adapt to various complex wiring error situations, thereby improving the accuracy and reliability of the power system's calculation of the corrected electricity quantity of the electric energy meter.

[0007] In order to solve the above technical problems, the present application provides a method for calculating the corrected electric quantity of an electric energy meter, comprising the following steps:

[0008] Obtain the historical measurement data of the target electric energy meter;

[0009] The phase angle feature profiling algorithm is used to analyze the metering historical data to identify the wiring error type corresponding to the target electric energy meter;

[0010] Based on the wiring error type, determining a corresponding correction transformation matrix;

[0011] Based on the correction transformation matrix, a corrected electric quantity of the target electric energy meter is calculated.

[0012] Furthermore, in some embodiments, the phase angle feature portrait algorithm is constructed by:

[0013] Obtaining operating data of multiple different types of electric energy meters;

[0014] Performing data preprocessing on the operation data to obtain preprocessed operation data;

[0015] Extracting corresponding phase angle features and power features from the preprocessed operating data;

[0016] Classifying the phase angle features and the power features according to different wiring types, and constructing a typical phase angle feature learning set;

[0017] A preset machine learning algorithm is trained based on the typical phase angle feature learning set to obtain a phase angle feature portrait algorithm.

[0018] Furthermore, in some embodiments, the adopting of a phase angle feature profiling algorithm to analyze the metering history data to identify the wiring error type corresponding to the target electric energy meter includes:

[0019] The phase angle feature profiling algorithm is used to extract features from the historical metering data to obtain the phase angle features and power features of the target electric energy meter;

[0020] Integrate the phase angle feature and the power feature to obtain a comprehensive feature vector;

[0021] Matching the comprehensive feature vector with the typical phase angle features in the typical phase angle feature learning set to obtain a plurality of matching combinations with the highest matching degree;

[0022] Calculating the Euclidean distances corresponding to the plurality of matching results respectively, taking the matching combination with the smallest Euclidean distance as the voltage connection combination corresponding to the target electric energy meter, and generating a matching result;

[0023] The wiring error type of the target electric energy meter is determined according to the matching result.

[0024] Further, in some embodiments, determining a corresponding correction transformation matrix based on the wiring error type includes:

[0025] Based on the wiring error type, constructing a correction model corresponding to the target electric energy meter;

[0026] A corresponding correction transformation matrix is ​​determined based on the correction model.

[0027] Furthermore, in some embodiments, constructing a correction model corresponding to the target electric energy meter based on the wiring error type includes:

[0028] Determine the standard phase angle of the target electric energy meter under the correct wiring condition;

[0029] determining an actual phase angle of the target electric energy meter based on the wiring error type;

[0030] Calculating a phase difference between the standard phase angle and the actual phase angle;

[0031] A corresponding correction transformation matrix is ​​constructed based on the phase difference as a correction model corresponding to the target electric energy meter.

[0032] Further, in some embodiments, determining a corresponding correction transformation matrix based on the correction model includes:

[0033] Calculating the theoretical power of the target electric energy meter under the correct wiring condition;

[0034] determining a correction transformation matrix of the target electric energy meter based on the wiring error type;

[0035] The actual power is corrected based on the correction transformation matrix to obtain a corrected actual measured power.

[0036] Furthermore, in some embodiments, the calculating the corrected electric quantity of the target electric energy meter based on the corrected transformation matrix includes:

[0037] Determining the time interval for recording the target electric energy meter data;

[0038] Collecting current data and voltage data of the target electric energy meter in each time interval;

[0039] Based on the current data and the voltage data collected from the target electric energy meter in each time interval, the metering power data of each time interval is corrected by correcting the transformation matrix to obtain the corrected actual measured power;

[0040] Based on the actual measured power, the power of the target electric energy meter in each time interval is calculated to obtain the corrected power of each time interval;

[0041] All corrected electricity quantities for each time interval are accumulated to obtain the total corrected electricity quantity for the entire billing period.

[0042] Accordingly, the present application also provides a device for calculating corrected electric quantity of an electric energy meter, which is characterized by comprising:

[0043] An acquisition module is used to acquire the historical measurement data of the target electric energy meter;

[0044] An analysis module, configured to analyze the metering history data using a phase angle feature profiling algorithm to identify a wiring error type corresponding to the target electric energy meter;

[0045] A determination module, configured to determine a corresponding correction transformation matrix based on the wiring error type;

[0046] A calculation module is used to calculate the corrected electric quantity of the target electric energy meter based on the corrected transformation matrix.

[0047] The present application also provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of the method for correcting the electric energy meter electric quantity calculation as described above are performed.

[0048] The present application also provides a storage medium storing a computer program that can be loaded by a processor and execute the method for calculating the corrected electric quantity of an electric energy meter as described above.

[0049] Implementing the embodiments of the present application has the following beneficial effects:

[0050] As described above, the present application provides a method, device, electronic device and storage medium for calculating the corrected electricity quantity of an electric energy meter, and the method for calculating the corrected electricity quantity of an electric energy meter includes: obtaining the metering history data of the target electric energy meter; using the phase angle feature portrait algorithm to analyze the metering history data and identify the wiring error type corresponding to the target electric energy meter; based on the wiring error type, determining the corresponding correction transformation matrix; based on the correction transformation matrix, calculating the corrected electricity quantity of the target electric energy meter. The present application provides a method for calculating the corrected electricity quantity of an electric energy meter, which can more accurately calculate the corrected electricity quantity of an electric energy meter and reduce the interference of human factors by adopting advanced algorithms and mathematical models, thereby improving the accuracy and reliability of the electric energy meter correction calculation by the power system, and can be applied to various complex wiring error situations, effectively improving the applicability of the method for calculating the corrected electricity quantity of an electric energy meter by the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present application, and together with the specification are used to explain the principles of the present application. In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the description of the embodiments are briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor.

[0052] Figure 1 It is a flowchart of a method for calculating corrected electric quantity of an electric energy meter provided in an embodiment of the present application;

[0053] Figure 2 It is another flowchart of the method for calculating the corrected electric quantity of an electric energy meter provided in an embodiment of the present application;

[0054] Figure 3 is a schematic diagram of a typical phase angle feature learning set provided in an embodiment of the present application;

[0055] Figure 4 It is a schematic diagram of the process of phase angle combination matching provided in an embodiment of the present application;

[0056] Figure 5 It is a schematic diagram of the process of voltage wiring combination matching provided in an embodiment of the present application;

[0057] Figure 6 This is a schematic diagram showing the correct phase angle provided by the embodiment of the present application;

[0058] Figure 7 It is a schematic diagram of the phase angle A phase with reverse polarity provided in the embodiment of the present application;

[0059] Figure 8 is a schematic diagram of the minimum interval accumulation method provided in an embodiment of the present application;

[0060] Fig. 9 It is a structural schematic diagram of a device for calculating corrected electric quantity of an electric energy meter provided in an embodiment of the present application;

[0061] Fig.10 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0062] The realization of the purpose, functional features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. The above-mentioned drawings have shown clear embodiments of this application, which will be described in more detail later. These drawings and textual descriptions are not intended to limit the scope of the concept of this application in any way, but to illustrate the concept of this application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0063] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0064] It should be noted that, in this article, the terms "include", "comprises" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element. In addition, components, features, and elements with the same name in different embodiments of the present application may have the same meaning or different meanings, and their specific meanings need to be determined by their explanation in the specific embodiment or further combined with the context of the specific embodiment.

[0065] It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0066] In the subsequent description, the suffixes such as "module", "component" or "unit" used to represent elements are only used to facilitate the description of the present application, and have no specific meanings. Therefore, "module", "component" or "unit" can be used in a mixed manner.

[0067] Due to various objective and subjective factors, wiring errors in metering devices often occur. There are various forms of wiring errors in metering devices, which can cause the electric energy meter to run faster or slower, or even stop. When a wiring error occurs in a metering device, the wrong wiring should be corrected first, and then the calculation of the error power should be performed to provide the basis for the error power to the power company and customers in a timely manner. At present, power supply companies generally use the "correction coefficient method" to calculate the error power of metering devices. Assuming that the error power is Wc, the power correction coefficient K is obtained according to the power or power expression, and the power Wb to be compensated can be calculated. The calculation process is as follows: Calculate the power correction coefficient K = correct power / error power; Calculate the power Wb to be compensated = (|K|-1)Wc. From the calculation principle, it can be seen that the existing technology has the following defects: (1) The correction coefficient method is only applicable to the case of three-phase load balance; (2) Some error types (such as when the current and voltage do not correspond, the correction coefficient is infinite) cannot be calculated; (3) Generally, the average power factor over a certain period of time during normal operation is used as the basis for calculating the correction coefficient, but the average power factor is selected as 0.7 or 0.9, and the calculation results differ by 10 times.

[0068] In response to the above technical problems, the embodiments of the present application provide a method, device, electronic device and storage medium for calculating the corrected electricity quantity of an electricity meter. By adopting advanced algorithms and mathematical models, the corrected electricity quantity of the electricity meter can be more accurately calculated, the interference of human factors can be reduced, and it can adapt to various complex wiring error situations, thereby improving the accuracy and reliability of electricity calculation.

[0069] The embodiments of the present application provide a method, device, electronic device and storage medium for calculating corrected electricity quantity of an electric energy meter.

[0070] Among them, the electric energy meter correction power calculation device can be deployed in a terminal or a server. The server can include an independently running server or a distributed server, or a server cluster composed of multiple servers. The terminal can include a mobile phone, a tablet computer or a personal computer (PC, Personal Computer).

[0071] It should be noted that the order of description of the following embodiments is not intended to limit the priority order of the embodiments.

[0072] The present application provides a method for calculating the corrected electricity quantity of an electric energy meter, comprising: obtaining the metering history data of a target electric energy meter; analyzing the metering history data using a phase angle feature portrait algorithm to identify the wiring error type corresponding to the target electric energy meter; determining the corresponding correction transformation matrix based on the wiring error type; and calculating the corrected electricity quantity of the target electric energy meter based on the correction transformation matrix.

[0073] See also Figure 1 , Figure 1 The flowchart of the method for calculating the corrected electric quantity of an electric energy meter provided in the embodiment of the present application is shown in FIG. The method for calculating the corrected electric quantity of an electric energy meter provided in the embodiment can be executed in a power supply system, and the method for calculating the corrected electric quantity of an electric energy meter can specifically include the following steps:

[0074] S1. Obtain the historical measurement data of the target electric energy meter;

[0075] Specifically, for step S1, this step mainly collects the power data, current, voltage, power factor and other historical measurement data stored in the power meter register from the power meter; these data are usually automatically recorded by the power meter and can be read in real time or periodically through a communication interface (such as RS485, Ethernet, wireless communication, etc.).

[0076] S2. Use the phase angle feature profiling algorithm to analyze the historical metering data and identify the wiring error type corresponding to the target electric energy meter;

[0077] Specifically, for step S2, the collected historical data is analyzed using a self-developed phase angle feature profiling algorithm to identify the wiring error type of the electric energy meter. The algorithm can be a machine learning-based model that identifies different wiring error features by training learning sets, which include electric energy meter data of normal wiring and various incorrect wirings, as well as typical phase angle feature sets.

[0078] S3. Based on the wiring error type, determine the corresponding correction transformation matrix;

[0079] Specifically, for step S3, the wiring error type obtained by analysis is used to determine the correction transformation matrix using the model corresponding to the algorithm. This step requires the construction of a correction model, which constructs a correction transformation matrix based on the phase difference between the standard phase angle and the actual phase angle, and the matrix can correct the power calculation according to the actual wiring error.

[0080] S4. Based on the correction transformation matrix, calculate the corrected power of the target energy meter;

[0081] Specifically, for step S4, the correction transformation matrix determined in step 3 is used to calculate the corrected power for the current and voltage data in each time interval, and the corrected power is calculated. This process may involve calculating and correcting the power for each 15-minute interval (or smaller time interval), and then accumulating these corrected power quantities to obtain the total corrected power quantity for the entire billing period.

[0082] It can be seen that the method for calculating the corrected electricity quantity of an electric energy meter provided in this embodiment can more accurately calculate the electricity quantity deviation caused by wiring errors by using more advanced algorithms and correction models; the automated calculation method reduces the interference of human factors and improves the objectivity and fairness of electricity quantity calculation; provides a more scientific and reliable electricity quantity correction method, which helps to improve customers' trust in the accuracy of the power supply department's calculation of the corrected electricity quantity; accurate corrected electricity quantity calculation provides strong technical support for the power supply department in providing evidence for the rights protection of supplementary electricity quantity, and enhances the legal effect; the automated method reduces the workload and time of manual calculation and improves work efficiency; the method is not limited to a specific type of electric energy meter, but can be widely used in various types of electric energy meters, and has strong adaptability and versatility.

[0083] Furthermore, in some embodiments, the construction method of the phase angle feature portrait algorithm in this embodiment includes:

[0084] Obtaining operating data of multiple different types of electric energy meters;

[0085] Performing data preprocessing on the operation data to obtain preprocessed operation data;

[0086] Extracting corresponding phase angle features and power features from the preprocessed operating data;

[0087] The phase angle features and power features are classified according to different wiring types, and a typical phase angle feature learning set is constructed;

[0088] The preset machine learning algorithm is trained based on the typical phase angle feature learning set to obtain the phase angle feature portrait algorithm.

[0089] Specifically, this embodiment also provides a method for constructing a phase angle feature portrait algorithm, and the specific steps are as follows: First, obtain the operating data of multiple different types of electric energy meters, collect the operating data from different types of electric energy meters, these operating data may include voltage, current, power factor, power, etc., these operating data may come from electric energy meters of different manufacturers and different models to ensure the generalization ability and adaptability of the algorithm. Then, perform data preprocessing on the operating data, and clean and format the collected raw data for subsequent analysis. The preprocessing may include steps such as denoising, outlier processing, data standardization, and missing value processing. Next, extract phase angle features and power features, and extract key features such as phase angle and power from the preprocessed data. Feature extraction can use methods such as Fourier transform and wavelet transform to identify periodic changes and important frequency components. Next, classify and construct a typical phase angle feature learning set, classify the extracted features according to the different wiring types of the electric energy meter, and construct a learning set. The learning set includes data of normal wiring and various known wrong wiring types for training machine learning models. Finally, the constructed learning set is used to train the preset machine learning algorithms to identify different wiring error types. The algorithms used include support vector machines (SVM), random forests, neural networks, etc., which are able to learn from large amounts of data and identify complex patterns.

[0090] This embodiment uses a machine learning algorithm to more accurately identify the type of wiring errors in an electric energy meter. By collecting and analyzing multiple types of electric energy meter data, the algorithm can adapt to different electric energy meters and environmental conditions. Automated feature extraction and classification reduce manual intervention and improve the efficiency and consistency of data processing. The influence of human factors in data preprocessing and feature extraction is reduced, and data quality is improved. Through automated preprocessing and feature extraction, the speed and accuracy of data processing are greatly improved. By using multiple types of electric energy meter data for training, the algorithm can better adapt to new or unknown types of electric energy meters.

[0091] In a specific embodiment, the typical phase angle feature learning set is the core technology of this embodiment. The typical phase angle feature learning set is constructed based on the voltage, current, power phase angle related principles of the power system, the energy meter measurement related principles and business rules. The generated data fully reflects the power value of each component of the three-phase three-wire and three-phase four-wire meters under theoretical conditions, and the corresponding relationship between the voltage combination relationship and the current combination relationship. The concept of the learning set is as follows Figure 3 As shown, the learning set contains 6 voltage combinations with each of them as the benchmark subset, active power, reactive power, component angles, phase voltage, phase current power factor angle and other main data, which correspond to the metering data active power and reactive power.

[0092] Further, in some embodiments, step S2 of "using a phase angle feature profile algorithm to analyze the metering history data to identify the wiring error type corresponding to the target electric energy meter" may specifically include:

[0093] S21. Use the phase angle feature profiling algorithm to extract features from the historical metering data to obtain the phase angle features and power features of the target electric energy meter;

[0094] S22. Integrate the phase angle feature and the power feature to obtain a comprehensive feature vector;

[0095] S23. Matching the comprehensive feature vector with the typical phase angle features in the typical phase angle feature learning set to obtain several matching combinations with the highest matching degree;

[0096] S24. Calculate the Euclidean distances corresponding to several matching results respectively, and use the matching combination with the smallest Euclidean distance as the voltage connection combination corresponding to the target electric energy meter to generate a matching result;

[0097] S25. Determine the wiring error type of the target electric energy meter according to the matching result.

[0098] Specifically, for step S2, first, the phase angle feature profiling algorithm is used to extract the phase angle feature and the power feature from the metering history data. The feature extraction includes calculating the phase difference of the voltage and current waveforms, and analyzing the power data to identify the load characteristics. Then, the extracted phase angle feature and power feature are integrated into a comprehensive feature vector. The integration of the feature vector involves normalization to ensure the comparability between different features. Next, the comprehensive feature vector is matched with the features in the typical phase angle feature learning set. The matching process can use pattern recognition techniques, such as the nearest neighbor algorithm, to find the most similar feature combination. The Euclidean distance is calculated for the matching results to evaluate the similarity between the feature vector and the features in the learning set. The calculation of the Euclidean distance may involve distance measurement in a multidimensional space to determine the closest match. Finally, the wiring error type of the electric energy meter is determined based on the matching results.

[0099] This embodiment can accurately identify the wiring error type of the electric energy meter through feature extraction and matching; the automated analysis process reduces manual intervention and improves processing speed and consistency; data-based feature matching and distance calculation provide a more objective basis for decision-making; through the use of comprehensive feature vectors, the misjudgment that may be caused by a single feature is reduced; the fast feature extraction and matching algorithm improves the efficiency of the overall processing flow; the algorithm can adapt to different electric energy meters and metering conditions and has strong versatility.

[0100] In a specific embodiment, Figure 4As shown in FIG. 1 , a set of voltage, current and power values ​​collected from the electric energy meter are converted into an array [B1], and are respectively trained with a typical phasor diagram library of six types of voltage reference combinations to obtain six training results corresponding to the six phase angle combinations with the highest matching degree; Figure 5 As shown, the six learning and training results are judged by using the Euclidean distance value, and the array [B1] corresponding to the voltage connection combination of the electric energy meter is determined by the minimum Euclidean distance value.

[0101] Further, in some embodiments, step S3 “determine a corresponding correction transformation matrix based on the wiring error type” may specifically include:

[0102] S31. Based on the wiring error type, construct a correction model corresponding to the target electric energy meter;

[0103] S32. Determine a corresponding correction transformation matrix based on the correction model.

[0104] Specifically, for step S3, according to the wiring error type of the electric energy meter, a correction model is constructed, which can describe the impact of incorrect wiring on the metering of the electric energy meter. The correction model is based on physical laws and circuit theory and the working principle of electric energy meter measurement, and takes into account factors such as the phase relationship between voltage and current and power factor. The correction model is constructed using a correction transformation matrix, which is used to correct the metering data of the electric energy meter to compensate for the electric energy metering deviation caused by the wiring error. The process of determining the correction transformation matrix includes algorithm calculation processes such as matrix operations and optimization algorithms. The construction of the correction model can determine the standard phase angle of the electric energy meter under the correct wiring condition, and calculate the phase difference based on the actual phase angle. This phase difference will be used to construct a wiring transformation matrix, which is the core part of the correction model. The calculation of the correction transformation matrix includes calculating the difference between the theoretical power and the actual power, and using the wiring transformation matrix to correct the actual power, so as to obtain a power consumption closer to the actual consumption.

[0105] This embodiment can more accurately calculate the power error caused by wiring errors by constructing a correction model and calculating the correction transformation matrix; the correction model provides a scientific theoretical basis, making the correction process more reasonable and reliable; the automated correction transformation matrix calculation reduces the interference of human factors and improves the objectivity and fairness of power calculation; the method can adapt to different types of wiring errors and has good versatility and flexibility; the automated correction transformation matrix calculation process improves the efficiency of power correction and reduces the workload of manual calculation.

[0106] Further, in some embodiments, step S31 "building a correction model corresponding to the target electric energy meter based on the wiring error type" may specifically include:

[0107] S311. Determine the standard phase angle of the target electric energy meter under the correct wiring conditions;

[0108] S312. Determine the actual phase angle of the target electric energy meter based on the wiring error type;

[0109] S313. Calculate the phase difference between the standard phase angle and the actual phase angle;

[0110] S314. Construct a corresponding wiring transformation matrix based on the phase difference as a correction model corresponding to the target electric energy meter.

[0111] Specifically, for step S31, first, determine the standard phase angle of the electric energy meter under correct wiring conditions, which usually includes the correct ideal or expected phase relationship between the voltage and current waveforms measured by the metering element of the electric energy meter. You can refer to the technical specification of the electric energy meter or the standard data provided by the manufacturer. Then, based on the type of wiring error of the electric energy meter, determine the phase angle of the electric energy meter in actual operation. The determination of the actual phase angle involves field measurement or inference by analyzing historical data through machine learning algorithms. Calculate the difference between the standard phase angle and the actual phase angle to obtain the phase difference. The calculation process of the phase difference includes trigonometric functions and vector analysis to determine the exact phase relationship between the voltage and current waveforms. Finally, use the calculated phase difference to construct a correction transformation matrix, which is used to correct the metering data of the electric energy meter. The correction transformation matrix is ​​a mathematical tool used to describe and correct the deviation in the calculation of the electric quantity due to wiring errors.

[0112] This embodiment can accurately correct the erroneous metering data of the electric energy meter caused by wiring errors by accurately calculating the phase difference and constructing the correction transformation matrix; uses scientific methods to determine the phase angle and construct the correction model, thereby improving the accuracy and reliability of the correction process; the automated calculation process reduces manual intervention and improves processing speed and consistency; through the accurate calculation of the phase difference, the metering error caused by wiring errors is reduced; the fast phase difference calculation and the construction of the wiring transformation matrix improve the efficiency of the overall processing flow; the method can adapt to different electric energy meters and wiring error types and has strong versatility.

[0113] Further, in some embodiments, step S32 “determining a corresponding correction transformation matrix based on the correction model” may specifically include:

[0114] S321. Calculate the theoretical power of the target electric energy meter under correct wiring conditions;

[0115] S322. Determine the correction transformation matrix of the target electric energy meter based on the wiring error type;

[0116] S323. Correct the actual power based on the correction transformation matrix to obtain the corrected actual measured power.

[0117] Specifically, for step S32, the theoretical power is calculated using a preset formula based on the standard phase angle of the electric energy meter under correct wiring conditions and the known voltage and current values. The calculation of the theoretical power takes into account the phase relationship and power factor in the three-phase power system. According to the actual wiring error type of the electric energy meter and the measured voltage and current values, the actual correct power is corrected and calculated. The calculation of the actual correct power needs to take into account the phase angle change caused by the wiring error. The actual power is corrected using a correction transformation matrix to simulate the power measurement value if the electric energy meter is correctly wired. The correction process involves matrix operations, mapping the power vector calculated from the actual measured current and voltage to the corrected power vector. The correction transformation matrix, the formula can be expressed as a matrix relationship:

[0118]

[0119] The correction transformation matrix reflects the transformation relationship between the actual measured value and the theoretical value, and is used to correct the calculated power value of the electric energy meter.

[0120] This embodiment can correct the metering deviation caused by the wiring error of the electric energy meter by correcting the actual power; the method can adapt to various types of wiring errors and provide a customized correction transformation matrix; the automated calculation process improves the efficiency of power correction and reduces the workload of manual calculation; it provides a more scientific and reliable power correction method, which helps to improve customers' trust in the accuracy of the power supply department's calculation of the corrected power; accurate correction transformation matrix calculation provides strong technical support for the power supply department in proving its rights to collect additional power.

[0121] In a specific embodiment, the wiring transformation matrix principle is as follows Figure 6 As shown, when the electric energy meter is wired normally, the phase diagram is as follows Figure 6 As shown in the (correct phase angle diagram), the phase angle between U1 and I1 is The phase angle between U2 and I2 is The phase angle between U3 and I3 is

[0122] When the energy meter is wired incorrectly, the polarity of phase A is reversed, such as Figure 7 (Phase angle A is opposite in polarity) shows that the phase angle between U1 and I1 becomes In other words, the wrong wiring mode of the energy meter is the case where the polarity of phase A is reversed. From the perspective of phase angle, the phase angle between U1 and I1 is changed from the original Increased by 180° (i.e. ). U2 and I3 are connected correctly, and the phase angle remains unchanged. Based on the comparison and multiple verifications, the connection transformation matrix is ​​compiled.

[0123] In general, when the voltage combination of a three-phase three-wire electric energy meter is ABC and the current combination is Ia Ic, the correction transformation matrix is ​​as follows:

[0124]

[0125] When the voltage combination is ABC, and the current combination is -Ia, Ic, the correction transformation matrix is ​​as follows:

[0126]

[0127] Furthermore, in some embodiments, step S4 “calculating the corrected electric quantity of the target electric energy meter based on the corrected transformation matrix” may specifically include:

[0128] S41. Determine the time interval for recording target energy meter data;

[0129] S42. Collecting current data and voltage data of the target energy meter in each time interval;

[0130] S43. Based on the current data and voltage data of the target energy meter collected in each time interval, the metering power data of each time interval is corrected by correcting the transformation matrix to obtain the corrected actual measured power;

[0131] S44. Calculate the power of the target electric energy meter in each time interval based on the actual measured power, and obtain the corrected power of each time interval;

[0132] S45. Accumulate all corrected electric quantities in each time interval to obtain the total corrected electric quantity for the entire billing period.

[0133] Specifically, for step S4, the time interval for recording the data of the electric energy meter is determined, which is usually a fixed interval set by the electric energy meter or the relevant metering system, for example, data is recorded every 15 minutes. The determination of the time interval is the basis for the calculation of the electric energy, and it is necessary to ensure that it matches the data recording frequency of the electric energy meter. In each time interval, the metering data of the electric energy meter is collected, including voltage, current, power factor, etc. The collected data needs to be sufficiently accurate and complete for subsequent calculation of the electric energy. The electric energy of each time interval is calculated, and the collected metering data is used to calculate the electric energy in each time interval according to the working principle of the electric energy meter. The calculation of the electric energy involves a complex energy conversion formula, which needs to take into account the measurement error and environmental factors of the electric energy meter. The correction transformation matrix is ​​applied to correct the electric energy of each time interval to compensate for the metering deviation caused by wiring errors or other factors. The correction process needs to ensure the accurate application of the correction transformation matrix, and multiple iterative calculations are required to ensure the accuracy of the results. The corrected electric energy of all time intervals is accumulated to obtain the total corrected electric energy of the entire billing period. The accumulation process needs to ensure the accuracy and completeness of the data to avoid deviations in the calculation of the total electric energy.

[0134] By applying the correction transformation matrix, this embodiment can more accurately calculate the corrected electricity quantity of the electric energy meter and correct the metering deviation caused by the wiring of the electric energy meter; the automated electricity quantity calculation and correction process improves the processing speed and consistency and reduces human intervention; the calculation based on the actual metering data provides a more objective decision-making basis and enhances the credibility of the corrected electricity quantity calculation; the automated calculation process reduces the influence of human factors in the corrected electricity quantity calculation process; the rapid corrected electricity quantity calculation improves the efficiency of the overall processing process and reduces the operating cost; and provides a more scientific and reliable electricity quantity correction method, which helps to improve customers' trust in the accuracy of the corrected electricity quantity calculation of the power supply department.

[0135] In a specific embodiment, this embodiment uses the minimum interval accumulation method to calculate the total corrected electricity volume for the entire billing period. The minimum interval accumulation method is a calculation method developed based on the calculus principle in mathematics and the data granularity collected by the metering system (one record for each user every 15 minutes). Figure 8 As shown, P represents the component power, which is calculated by multiplying the voltage value collected in the metering automation system by the current value and then by the angle between the voltage and current according to the following formula:

[0136]

[0137] Where: is the arccosine value of the collected power factor value, P is the component power, U is the voltage value, and I is the current value.

[0138] The total power W calculated by the minimum interval accumulation method is equal to the time interval from t0 to tn. With 15 minutes as an interval, accumulate the power values ​​of n 15 minutes. Calculate according to the following formula:

[0139]

[0140] In the formula, U is the collected voltage value, I is the collected current value, P is the active power of the energy meter, W is the electricity value calculated within the specified time period, and Δt=tk-tk-1 represents the time interval, which is the minimum interval of 15 minutes collected by the metering system and the minimum time interval of 15 minutes for the energy meter to save data.

[0141] In summary, the present embodiment provides a method for calculating the corrected electricity quantity of an electric energy meter, including: obtaining the historical metering data of the target electric energy meter, such as the current, voltage, power, and meter code; using the phase angle feature portrait algorithm to analyze the historical metering data, and identifying the type of wiring error corresponding to the target electric energy meter; based on the type of wiring error, determining the corresponding correction transformation matrix; and calculating the corrected electricity quantity of the target electric energy meter based on the correction transformation matrix. It can be seen that the present embodiment provides a method for calculating the corrected electricity quantity of an electric energy meter, by using advanced algorithms and mathematical models, which can more accurately calculate the corrected electricity quantity of the electric energy meter and reduce the interference of human factors, thereby improving the accuracy and reliability of the calculation of the corrected electricity quantity of the electric energy meter in the power system, and can be applied to various complex wiring error situations, effectively improving the applicability of the method for calculating the corrected electricity quantity of the electric energy meter in the power system.

[0142] In order to better implement the method for calculating the corrected electricity quantity of the electric energy meter of the embodiment of the present application, the embodiment of the present application also provides a device for calculating the corrected electricity quantity of the electric energy meter. The meanings of the terms are the same as those in the method for calculating the corrected electricity quantity of the electric energy meter, and the specific implementation details can refer to the description in the method embodiment.

[0143] See also Fig. 9 , Fig. 9 The schematic diagram of the structure of the electric energy meter corrected electric energy calculation device provided in the embodiment of the present application, wherein the electric energy meter corrected electric energy calculation device may specifically include an acquisition module 201, an analysis module 202, a determination module 203 and a calculation module 204, which may be specifically as follows:

[0144] The acquisition module 201 is used to acquire the measurement history data of the target electric energy meter;

[0145] An analysis module 202 is used to analyze the metering history data using a phase angle feature profiling algorithm to identify the wiring error type corresponding to the target electric energy meter;

[0146] A determination module 203, configured to determine a corresponding correction transformation matrix based on the wiring error type;

[0147] The calculation module 204 is used to calculate the corrected electric quantity of the target electric energy meter based on the corrected transformation matrix.

[0148] Furthermore, in some embodiments, the construction method of the phase angle feature portrait algorithm includes:

[0149] Obtaining operating data of multiple different types of electric energy meters;

[0150] Performing data preprocessing on the operation data to obtain preprocessed operation data;

[0151] Extracting corresponding phase angle features and power features from the preprocessed operating data;

[0152] The phase angle features and power features are classified according to different wiring types, and a typical phase angle feature learning set is constructed;

[0153] The preset machine learning algorithm is trained based on the typical phase angle feature learning set to obtain the phase angle feature portrait algorithm.

[0154] Furthermore, in some embodiments, the analysis module 202 is specifically used to:

[0155] The phase angle feature profiling algorithm is used to extract features from the historical metering data to obtain the phase angle features and power features of the target electric energy meter.

[0156] The phase angle feature and the power feature are integrated to obtain a comprehensive feature vector;

[0157] Matching the comprehensive feature vector with the typical phase angle features in the typical phase angle feature learning set to obtain several matching combinations with the highest matching degree;

[0158] Calculate the Euclidean distances corresponding to several matching results respectively, take the matching combination with the smallest Euclidean distance as the voltage connection combination corresponding to the target electric energy meter, and generate a matching result;

[0159] The wiring error type of the target electric energy meter is determined through the matching results.

[0160] Further, in some embodiments, the determination module 203 is specifically configured to:

[0161] Based on the wiring error type, a correction model corresponding to the target electric energy meter is constructed;

[0162] A corresponding correction transformation matrix is ​​determined based on the correction model.

[0163] Further, in some embodiments, the determination module 203 is specifically configured to:

[0164] Determine the standard phase angle of the target electric energy meter under the correct wiring condition;

[0165] determining an actual phase angle of a target electric energy meter based on the type of wiring error;

[0166] Calculate the phase difference between the standard phase angle and the actual phase angle;

[0167] A corresponding correction transformation matrix is ​​constructed based on the phase difference as a correction model corresponding to the target electric energy meter.

[0168] Further, in some embodiments, the determination module 203 is specifically configured to:

[0169] Calculate the theoretical power of the target electric energy meter under the correct wiring conditions;

[0170] Based on the wiring error type and the voltage and current values ​​measured by the target electric energy meter, the actual power is corrected using a correction transformation matrix to obtain the actual power of the target electric energy meter;

[0171] Furthermore, in some embodiments, the calculation module 204 is specifically configured to:

[0172] Determining the time interval for recording the target electric energy meter data;

[0173] Collecting current, voltage and data of the target electric energy meter in each time interval;

[0174] Based on the current, voltage and data collected from the target electric energy meter in each time interval, the metering power data of each time interval is corrected by correcting the transformation matrix to obtain the corrected actual measured power;

[0175] Based on the corrected actual measured power data, the power of the target electric energy meter in each time interval is calculated to obtain the corrected power of each time interval;

[0176] All corrected electricity quantities for each time interval are accumulated to obtain the total corrected electricity quantity for the entire billing period.

[0177] In summary, the device for calculating the corrected electric quantity of an electric energy meter provided in this embodiment obtains the metering history data of the target electric energy meter through the acquisition module 201; analyzes the metering history data using the phase angle feature portrait algorithm through the analysis module 202 to identify the type of wiring error corresponding to the target electric energy meter; determines the corresponding correction transformation matrix based on the wiring error type through the determination module 203; and calculates the corrected electric quantity of the target electric energy meter based on the correction transformation matrix through the calculation module 204. It can be seen that this embodiment can more accurately calculate the corrected electric quantity of the electric energy meter and reduce the interference of human factors by adopting advanced algorithms and mathematical models, thereby improving the accuracy and reliability of the electric power system calculating the corrected electric quantity, and can be applied to various complex wiring error situations, effectively improving the applicability of the method for calculating the corrected electric quantity of the electric energy meter in the electric power system.

[0178] In addition, the present application also provides an electronic device, such as Fig.10 , which shows a schematic diagram of the structure of an electronic device involved in an embodiment of the present application. Specifically, the electronic device may include a processor 301 with one or more processing cores, a memory 302 with one or more computer-readable storage media, a power supply 303, an input unit 304 and other components. Those skilled in the art can understand that Fig.10 The electronic device structure shown in the figure does not constitute a limitation on the electronic device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0179] The processor 301 is the control center of the electronic device. It uses various interfaces and lines to connect various parts of the entire electronic device. By running or executing software programs and / or modules stored in the memory 302, and calling data stored in the memory 302, it executes various functions of the electronic device and processes data, thereby monitoring the electronic device as a whole. Optionally, the processor 301 may include one or more processing cores; preferably, the processor 301 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface, and application programs, and the modem processor mainly processes wireless communications. It is understandable that the above-mentioned modem processor may not be integrated into the processor 301.

[0180] The memory 302 can be used to store software programs and modules. The processor 301 executes various functional applications and the electric energy meter corrected power calculation method by running the software programs and modules stored in the memory 302. The memory 302 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the electronic device, etc. In addition, the memory 302 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices. Accordingly, the memory 302 may also include a memory controller to provide the processor 301 with access to the memory 302.

[0181] The electronic device also includes a power supply 303 for supplying power to each component. Preferably, the power supply 303 can be logically connected to the processor 301 through a power management system, so that the power management system can manage charging, discharging, power consumption and other functions. The power supply 303 can also include one or more DC or AC power supplies, recharging systems, power failure detection circuits, power converters or inverters, power status indicators and other arbitrary components.

[0182] The electronic device may further include an input unit 304, which may be used to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal input related to user settings and function control.

[0183] Although not shown, the electronic device may further include a display unit, etc., which will not be described in detail herein. Specifically in this embodiment, the processor 301 in the electronic device will load the executable files corresponding to the processes of one or more application programs into the memory 302 according to the following instructions, and the processor 301 will run the application programs stored in the memory 302, thereby realizing various functions, as follows:

[0184] Obtain the metering history data of the target electric energy meter; use the phase angle feature profiling algorithm to analyze the metering history data and identify the wiring error type corresponding to the target electric energy meter; based on the wiring error type, determine the corresponding correction transformation matrix; based on the correction transformation matrix, calculate the corrected electric quantity of the target electric energy meter.

[0185] The specific implementation of the above operations can be found in the previous embodiments, which will not be described in detail here.

[0186] The embodiments of the present application adopt advanced algorithms and mathematical models to more accurately calculate the corrected electricity quantity of the electricity meter and reduce the interference of human factors, thereby improving the accuracy and reliability of the power system's calculation of the corrected electricity quantity of the electricity meter, and can be applied to various complex wiring error situations, effectively improving the applicability of the method for calculating the corrected electricity quantity of the electricity meter in the power system.

[0187] A person of ordinary skill in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be completed by instructions, or by controlling related hardware through instructions. The instructions may be stored in a computer-readable storage medium and loaded and executed by a processor.

[0188] To this end, an embodiment of the present application provides a storage medium in which a plurality of instructions are stored, and the instructions can be loaded by a processor to execute the steps in any one of the methods for calculating the corrected electric quantity of an electric energy meter provided in the embodiment of the present application. For example, the instructions can execute the following steps:

[0189] Obtain the metering history data of the target electric energy meter; use the phase angle feature profiling algorithm to analyze the metering history data and identify the wiring error type corresponding to the target electric energy meter; based on the wiring error type, determine the corresponding correction transformation matrix; based on the correction transformation matrix, calculate the corrected electric quantity of the target electric energy meter.

[0190] The specific implementation of the above operations can be found in the previous embodiments, which will not be described in detail here.

[0191] The storage medium may include: a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, etc. Since the instructions stored in the storage medium can execute the steps in any of the methods for calculating the corrected electric quantity of an electric energy meter provided in the embodiments of the present application, the beneficial effects that can be achieved by any of the methods for calculating the corrected electric quantity of an electric energy meter provided in the embodiments of the present application can be achieved. For details, please refer to the previous embodiments, which will not be repeated here.

[0192] The above is a detailed introduction to an electric energy meter correction power calculation method, device, electronic device and storage medium provided in an embodiment of the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for calculating the corrected electric quantity of an electric energy meter, characterized in that: The steps include: Obtain the historical measurement data of the target electric energy meter; The phase angle feature profiling algorithm is used to analyze the metering historical data to identify the wiring error type corresponding to the target electric energy meter; Based on the wiring error type, determining a corresponding correction transformation matrix; Based on the correction transformation matrix, a corrected electric quantity of the target electric energy meter is calculated.

2. The method for calculating the corrected electric quantity of an electric energy meter according to claim 1, characterized in that: The construction method of the phase angle feature portrait algorithm includes: Obtaining operating data of multiple different types of electric energy meters; Performing data preprocessing on the operation data to obtain preprocessed operation data; Extracting corresponding phase angle features and power features from the preprocessed operating data; Classifying the phase angle features and the power features according to different wiring types, and constructing a typical phase angle feature learning set; A preset machine learning algorithm is trained based on the typical phase angle feature learning set to obtain a phase angle feature portrait algorithm.

3. The method for calculating the corrected electric quantity of an electric energy meter according to claim 2, characterized in that: The adopting of the phase angle feature profiling algorithm to analyze the historical metering data and identify the wiring error type corresponding to the target electric energy meter includes: The phase angle feature profiling algorithm is used to extract features from the historical metering data to obtain the phase angle features and power features of the target electric energy meter; Integrate the phase angle feature and the power feature to obtain a comprehensive feature vector; Matching the comprehensive feature vector with the typical phase angle features in the typical phase angle feature learning set to obtain a plurality of matching combinations with the highest matching degree; Calculating the Euclidean distances corresponding to the plurality of matching results respectively, taking the matching combination with the smallest Euclidean distance as the voltage connection combination corresponding to the target electric energy meter, and generating a matching result; The wiring error type of the target electric energy meter is determined according to the matching result.

4. The method for calculating the corrected electric quantity of an electric energy meter according to claim 1, characterized in that: The determining a corresponding correction transformation matrix based on the wiring error type includes: Based on the wiring error type, constructing a correction model corresponding to the target electric energy meter; A corresponding correction transformation matrix is ​​determined based on the correction model.

5. The method for calculating the corrected electric quantity of an electric energy meter according to claim 4, characterized in that: The constructing a correction model corresponding to the target electric energy meter based on the wiring error type includes: Determine the standard phase angle of the target electric energy meter under the correct wiring condition; determining an actual phase angle of the target electric energy meter based on the wiring error type; Calculating a phase difference between the standard phase angle and the actual phase angle; A corresponding correction transformation matrix is ​​constructed based on the phase difference as a correction model corresponding to the target electric energy meter.

6. The method for calculating the corrected electric quantity of an electric energy meter according to claim 5, characterized in that: The determining a corresponding correction transformation matrix based on the correction model comprises: Calculating the theoretical power of the target electric energy meter under the correct wiring condition; determining a correction transformation matrix of the target electric energy meter based on the wiring error type; The actual power is corrected based on the correction transformation matrix to obtain a corrected actual measured power.

7. The method for calculating corrected electric quantity of electric energy meter according to claim 1, characterized in that: The calculating the corrected electric quantity of the target electric energy meter based on the corrected transformation matrix includes: Determining the time interval for recording the target electric energy meter data; Collecting current data and voltage data of the target electric energy meter in each time interval; Based on the current data and the voltage data collected from the target electric energy meter in each time interval, the metering power data of each time interval is corrected by a correction transformation matrix to obtain the corrected actual measured power; Based on the actual measured power, the power of the target electric energy meter in each time interval is calculated to obtain the corrected power of each time interval; All corrected electricity quantities for each time interval are accumulated to obtain the total corrected electricity quantity for the entire billing period.

8. A device for calculating the corrected electric quantity of an electric energy meter, characterized in that: include: An acquisition module is used to acquire the historical measurement data of the target electric energy meter; An analysis module, configured to analyze the metering history data using a phase angle feature profiling algorithm to identify a wiring error type corresponding to the target electric energy meter; A determination module, configured to determine a corresponding correction transformation matrix based on the wiring error type; A calculation module is used to calculate the corrected electric quantity of the target electric energy meter based on the corrected transformation matrix.

9. An electronic device, characterized in that: include: A memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the program according to the steps of the method for correcting the electric quantity calculation of an electric energy meter as described in any one of claims 1 to 7.

10. A storage medium, characterized in that: A computer program is stored which can be loaded by a processor and execute the method for calculating corrected electric quantity of an electric energy meter as described in any one of claims 1 to 7.

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