CN114720764B - Harmonic analysis method and system based on real-time monitoring data of electric meter - Google Patents
Harmonic analysis method and system based on real-time monitoring data of electric meter Download PDFInfo
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Abstract
The application discloses a harmonic analysis method and system based on real-time monitoring data of an electric meter, wherein the real-time monitoring data is acquired through an intelligent electric meter and is sent to a harmonic analysis system; preprocessing the real-time monitoring data, and filtering interference signals in the real-time monitoring data acquisition process to obtain processing monitoring data; classifying the processed monitoring data based on a preset classification requirement to obtain a monitoring data classification set; respectively carrying out Fourier transform operation on all the monitoring data sets to obtain a harmonic voltage set and a harmonic current set; and respectively carrying out trend analysis on the monitoring data set according to the harmonic voltage set and the harmonic current set to obtain a monitoring and predicting information set, carrying out power utilization evaluation according to the monitoring and predicting information set, and determining a circuit control scheme. The technical problems that in the prior art, accuracy of harmonic analysis is not high in the process of guiding a circuit to be used, and the actual power utilization condition of a user is influenced are solved.
Description
Technical Field
The application relates to the technical field of data analysis, in particular to a harmonic wave analysis method and system based on real-time monitoring data of an electric meter.
Background
Harmonic waves refer to components which are obtained by performing Fourier series decomposition on periodic non-sinusoidal alternating current and are greater than integral multiple of fundamental wave frequency, and the problem of harmonic pollution in the power system is increasingly serious along with the continuous improvement of new energy permeability and the great increase of non-linear load in the power system. A large amount of harmonic injection causes the waveforms of voltage and current in the power grid to be seriously distorted, thereby not only influencing the normal use of electrical equipment, but also threatening the safe and stable operation of the power grid. How to effectively control the harmonic waves and maintain the normal use of the circuit is a problem which needs to be solved consistently.
The technology at least has the following technical problems:
the accuracy of harmonic analysis in the prior art is not high in the process of guiding the circuit to use, and the actual power utilization condition of a user is influenced.
Disclosure of Invention
The application aims to provide a harmonic analysis method and a harmonic analysis system based on real-time monitoring data of an electric meter, and the method and the system are used for solving the technical problems that in the prior art, the accuracy of harmonic analysis is not high in the process of guiding a circuit to be used, and the actual power utilization condition of a user is influenced. The method has the advantages that targeted harmonic analysis is carried out according to a classified monitoring data set, corresponding control is carried out by combining the sizes of harmonic voltage and current and the prediction trend, so that the use safety of electrical equipment of each user is ensured, the circuit harmonic analysis is applied to the power utilization control of the user, a reliable circuit is provided for each user more accurately, the use safety of user electrical appliances is ensured, and the stability of voltage and current in the circuit is maintained.
In view of the above problems, the embodiments of the present application provide a harmonic analysis method and system based on real-time monitoring data of an electricity meter.
In a first aspect, the application provides a harmonic analysis method based on real-time monitoring data of an electric meter, wherein the method is applied to a harmonic analysis system, and the harmonic analysis system comprises an intelligent electric meter; the method comprises the following steps: acquiring real-time monitoring data through an intelligent ammeter, and sending the real-time monitoring data to a harmonic analysis system; the harmonic analysis system is used for preprocessing the real-time monitoring data, filtering interference signals in the real-time monitoring data acquisition process and obtaining processing monitoring data; obtaining a preset classification requirement; classifying the processing monitoring data based on the preset classification requirement to obtain a monitoring data classification set, wherein the monitoring data classification set comprises a plurality of monitoring data sets; respectively carrying out Fourier transform operation on all the monitoring data sets to obtain a harmonic voltage set and a harmonic current set; performing trend analysis on the monitoring data set according to the harmonic voltage set and the harmonic current set respectively to obtain a monitoring prediction information set, wherein the monitoring prediction information set corresponds to the monitoring data set; and carrying out power utilization evaluation according to the monitoring and predicting information set, and determining a circuit control scheme.
In another aspect, the present application further provides a harmonic analysis system based on real-time monitoring data of an electric meter, for executing a harmonic analysis method based on real-time monitoring data of an electric meter according to the first aspect, the system includes:
the system comprises a first obtaining unit, a harmonic analysis system and a second obtaining unit, wherein the first obtaining unit is used for acquiring real-time monitoring data through an intelligent electric meter and sending the real-time monitoring data to the harmonic analysis system;
the second acquisition unit is used for preprocessing the real-time monitoring data by the harmonic analysis system, filtering interference signals in the real-time monitoring data acquisition process and acquiring processing monitoring data;
a third obtaining unit, configured to obtain a preset classification requirement;
a fourth obtaining unit, configured to classify the processed monitoring data based on the preset classification requirement to obtain a monitoring data classification set, where the monitoring data classification set includes multiple monitoring data sets;
a fifth obtaining unit, configured to obtain a harmonic voltage set and a harmonic current set by performing fourier transform operation on all monitoring data sets, respectively;
a sixth obtaining unit, configured to perform trend analysis on the monitoring data set according to the harmonic voltage set and the harmonic current set, respectively, to obtain a monitoring prediction information set, where the monitoring prediction information set corresponds to the monitoring data set;
a first determination unit for performing a power usage assessment based on the monitored predictive information set, determining a circuit control scheme.
In a third aspect, the present application further provides a harmonic analysis system based on real-time monitoring data of an electric meter, including a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method according to the first aspect when executing the computer program.
In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method according to the first aspect.
One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:
1. classifying the processed monitoring data based on a preset classification requirement to obtain a monitoring data classification set; respectively carrying out Fourier transform operation on all the monitoring data sets to obtain a harmonic voltage set and a harmonic current set; the trend analysis is carried out on the monitoring data set according to the harmonic voltage set and the harmonic current set, the aim of carrying out targeted harmonic analysis according to the classified monitoring data set is achieved, the corresponding control is carried out by combining the magnitude of the harmonic voltage and the current and the prediction trend, so that the use safety of the electrical equipment of each user is ensured, the circuit harmonic analysis is applied to the user electricity control system, a reliable circuit is more accurately provided for each user, the use safety of the electrical equipment of the user is ensured, and the technical effects of maintaining the stability of the voltage and the current in the circuit are achieved.
2. By preprocessing the real-time monitoring data and filtering interference signals in the real-time monitoring data acquisition process, the processed monitoring data is obtained, the data of sampling burrs or transmission errors caused by interference is corrected, and a basic technical effect is provided for accurate harmonic analysis.
3. Constructing a classification tree level relation based on the classification characteristic information; performing feature comparison extraction on the processing monitoring data according to the classification feature information to obtain a feature classification cluster; and performing tree-level division on the feature classification clusters according to the classification tree-level relation to obtain the monitoring data classification set. The method achieves the technical effects that the monitoring data are classified according to different classification characteristics, the tree level relation is constructed to determine the relation of each level, the guarantee is provided for classification harmonic analysis and prediction, and the accuracy of classification prediction analysis results of each level is further improved based on the construction of the classification tree level relation.
The foregoing description is only an overview of the technical solutions of the present application, and the present application can be implemented according to the content of the description in order to make the technical means of the present application more clearly understood, and the following detailed description of the present application is given in order to make the above and other objects, features, and advantages of the present application more clearly understandable.
Drawings
In order to more clearly illustrate the embodiments or technical solutions in the prior art of the present application, the drawings used in the description of the embodiments or prior art will be briefly described below, it is obvious that the drawings in the description below are only exemplary, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
Fig. 1 is a schematic flowchart of a harmonic analysis method based on real-time monitoring data of an electricity meter according to an embodiment of the present application;
FIG. 2 is a schematic structural diagram of a harmonic analysis system based on real-time monitoring data of an electric meter according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of an exemplary electronic device according to an embodiment of the present application.
Description of reference numerals: a first obtaining unit 11, a second obtaining unit 12, a third obtaining unit 13, a fourth obtaining unit 14, a fifth obtaining unit 15, a sixth obtaining unit 16, a first determining unit 17, a bus 300, a receiver 301, a processor 302, a transmitter 303, a memory 304, and a bus interface 305.
Detailed Description
The embodiment of the application provides a harmonic analysis method and system based on real-time monitoring data of an ammeter, and solves the technical problems that in the prior art, accuracy of harmonic analysis is not high in a circuit use guiding process, and actual electricity utilization conditions of users are affected.
In the following, the technical solutions in the embodiments of the present application will be clearly and completely described with reference to the accompanying drawings, and it is to be understood that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments of the present application, and it should be understood that the present application is not limited by the example embodiments described herein. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments of the present application without making any creative effort belong to the protection scope of the present application. It should be further noted that, for the convenience of description, only some but not all of the relevant portions of the present application are shown in the drawings.
The technical scheme provided by the application has the following general idea:
acquiring real-time monitoring data through an intelligent ammeter, and sending the real-time monitoring data to a harmonic analysis system; the harmonic analysis system is used for preprocessing the real-time monitoring data, filtering interference signals in the real-time monitoring data acquisition process and obtaining processing monitoring data; obtaining a preset classification requirement; classifying the processing monitoring data based on the preset classification requirement to obtain a monitoring data classification set, wherein the monitoring data classification set comprises a plurality of monitoring data sets; respectively carrying out Fourier transform operation on all the monitoring data sets to obtain a harmonic voltage set and a harmonic current set; respectively carrying out trend analysis on the monitoring data set according to the harmonic voltage set and the harmonic current set to obtain a monitoring prediction information set, wherein the monitoring prediction information set corresponds to the monitoring data set; and carrying out power utilization evaluation according to the monitoring and predicting information set, and determining a circuit control scheme.
Having described the principles of the present application, various non-limiting embodiments thereof will now be described in detail with reference to the accompanying drawings.
Example one
Referring to fig. 1, an embodiment of the present application provides a harmonic analysis method based on real-time monitoring data of an electric meter, where the method is applied to a harmonic analysis system, and the harmonic analysis system includes a smart electric meter; the method comprises the following steps:
step S100: acquiring real-time monitoring data through an intelligent ammeter, and sending the real-time monitoring data to a harmonic analysis system;
specifically, the intelligent electric meter monitors data in a current circuit in real time, collects the monitoring data, transmits the collected monitoring data to the server through a high-speed network, and performs harmonic analysis processing on the received monitoring data through the harmonic analysis system, so that the intelligent electric meter realizes the effect of the front-end monitoring sensor on collecting the data in real time and transmitting the collected real-time monitoring data.
Step S200: the harmonic analysis system is used for preprocessing the real-time monitoring data, filtering interference signals in the real-time monitoring data acquisition process and obtaining processing monitoring data;
further, the preprocessing the real-time monitoring data, filtering the interference signal in the real-time monitoring data acquisition process, and obtaining the processing monitoring data includes: acquiring a first continuous queue according to the real-time monitoring data; acquiring a second continuous queue, arranging the second continuous queue at the tail of the first continuous queue, and forming a first calculation queue; carrying out average operation on the first calculation queue to obtain a first average value; obtaining a third continuous queue, arranging the third continuous queue at the tail part of the first calculation queue, removing the first continuous queue and forming a second calculation queue; carrying out average operation on the second calculation queue to obtain a second average value; and determining a filtering requirement value according to the first average value and the second average value, and filtering the real-time monitoring data based on the filtering requirement value to obtain the processing monitoring data.
Specifically, the collected data is corrected and filtered by using a high-speed smoothing filtering algorithm, sampling burrs or data which are mistakenly transmitted due to interference are removed, the interference and deviation data are filtered by using the filtering algorithm, the obtained processing monitoring data is the data from which the sampling burrs or the transmission errors are removed, and the harmonic analysis system is used for carrying out harmonic analysis on the processing monitoring data, so that a foundation is provided for accurate analysis. The high-speed smoothing filtering algorithm can be correspondingly set and processed according to needs, and the embodiment of the application adopts a sliding smoothing filtering method for processing. The method includes the steps that a plurality of continuous sampling samples are used as a queue from real-time monitoring data, the first continuous queue is selected according to a preset continuous length, and the obtained first continuous queue is formed by the plurality of continuous sampling samples, wherein each continuous queue is a set fixed length, such as 10 sampling values and 30 sampling values, and the like, and is not limited specifically. The second continuous queue is formed by continuously extracting sampling data with continuous fixed length from the sampling value behind the first continuous queue, the second continuous queue is placed at the tail of the first continuous queue, the average operation is carried out on the first calculation queue formed by the first continuous queue and the second continuous queue to obtain an average value, the average value is used for carrying out filtering processing, the data in the average value range is reserved, and the data exceeding the range is removed. And then continuously selecting sampling data with fixed length from the acquired real-time monitoring data to form a third continuous queue, placing the third continuous queue behind the second continuous queue, removing the first contact queue at the head to form a second calculation queue, thereby obtaining a new filtering result, and repeating the steps to process and filter all data in the real-time monitoring data, thereby obtaining the final processed monitoring data.
Step S300: obtaining a preset classification requirement;
step S400: classifying the processing monitoring data based on the preset classification requirement to obtain a monitoring data classification set, wherein the monitoring data classification set comprises a plurality of monitoring data sets;
further, the classifying the processing monitoring data based on the preset classification requirement to obtain a monitoring data classification set, where the monitoring data classification set includes multiple monitoring data sets, including: obtaining classification characteristic information according to the preset classification requirement; constructing a classification tree level relation based on the classification characteristic information; performing feature comparison extraction on the processing monitoring data according to the classification feature information to obtain a feature classification cluster; and performing tree-level division on the feature classification clusters according to the classification tree-level relation to obtain the monitoring data classification set.
Specifically, different classification requirements are set according to the characteristics of the analyzed electricity utilization place, and if the electricity utilization condition in a cell is analyzed, the preset classification requirements can be building classification according to the cell, electricity utilization type classification for each building, and finally type classification for high-power generation and electricity utilization appliances for each household in the building. Effective circuit management in each building in the cell can be realized. Different analysis requirements correspond to classified data characteristics of all levels, real-time measured data comprise the classified identification characteristics, the intelligent electric meter corresponds to different acquisition path identification information, acquisition positions, line labels and the like, and specific classification can be guaranteed. And constructing a classification tree level relation according to the hierarchical front-back and subordinate relations, if the classification tree level relation is classified as a first level according to building analysis, the classification tree level relation is used as a root node, the building is classified according to the electricity utilization type, the data characteristic of the electricity utilization type is a second classification and is used as a child node, finally, the electricity utilization characteristics of each household are classified as a third classification and is used as a leaf node, thus the tree level relation is constructed, the analysis processing is carried out by utilizing the monitoring data corresponding to each level, the corresponding harmonic wave analysis can be carried out on each classification, and the electricity utilization processing and control can be carried out in a targeted manner.
Step S500: respectively carrying out Fourier transform operation on all the monitoring data sets to obtain a harmonic voltage set and a harmonic current set;
further, the method further comprises: based on the monitoring current and the monitoring voltage in all the monitoring data sets, obtaining corresponding harmonic voltage and harmonic current through fast Fourier change; fitting and constructing a regression function; performing coefficient calculation on the regression function, determining a regression function coefficient, and optimizing the regression function by using the regression function coefficient; carrying out harmonic impedance calculation on the harmonic voltage set and the harmonic current set by utilizing the regression function to obtain a harmonic impedance estimation value; and determining the harmonic voltage set and the harmonic current set based on the harmonic impedance estimated value, the harmonic voltage and the harmonic current.
Specifically, the harmonic is an electric quantity contained in the current and having a frequency that is an integral multiple of the fundamental wave, and generally, the harmonic voltage and the harmonic current corresponding to data in each monitoring data set are obtained by performing fourier series decomposition on a periodic non-sinusoidal electric quantity and performing fourier transform operation. Simultaneously harmonic voltage = harmonic current × harmonic impedance, where harmonic impedance = system impedance × h, h being the h-th harmonic. The embodiment of the application utilizes the calculation processing of the harmonic impedance to further improve the reliability of the harmonic calculation processing. And (3) constructing a functional relation between harmonic voltage and harmonic current through the time point of sample collection, constructing a regression function, wherein the coefficient of the regression function is the key for optimizing the regression function, calculating the loss function by replacing different coefficients until the loss function reaches the preset requirement, wherein the smaller the preset requirement is, the better the preset requirement is, and when the preset requirement is met, the coefficient is taken as the coefficient of the regression function. And solving a harmonic impedance estimation value at the current moment based on a regression function, carrying out mutual verification by utilizing the harmonic impedance estimation value, harmonic voltage and harmonic current, and determining the current harmonic voltage and harmonic current when the calculation relationship between the harmonic impedance estimation value and the harmonic voltage and the harmonic current meets the formula so as to determine a harmonic voltage set and a harmonic current set.
Step S600: performing trend analysis on the monitoring data set according to the harmonic voltage set and the harmonic current set respectively to obtain a monitoring prediction information set, wherein the monitoring prediction information set corresponds to the monitoring data set;
further, the performing trend analysis on the monitoring data set according to the harmonic voltage set and the harmonic current set respectively to obtain a monitoring prediction information set, where the monitoring prediction information set corresponds to the monitoring data set, includes: obtaining a first classification data set according to the classification tree level relation of the monitoring data set; obtaining harmonic voltage and harmonic current of the first classified data set according to the first classified data set; obtaining a first classification requirement characteristic according to the first classification data set; obtaining first prediction influence information according to the first classification requirement characteristics, the harmonic voltage and the harmonic current of the first classification data set; repeatedly obtaining a second classified data set and a third classified data set until an Nth classified data set, and determining respective predicted influence information based on the second classified data set and the third classified data set until the Nth classified data set, wherein the second predicted influence information and the Nth predicted influence information are respectively the second predicted influence information and the Nth predicted influence information; and obtaining the monitoring prediction information set based on the first prediction influence information, the second prediction influence information, the Nth prediction influence information and the classification tree level relation of the monitoring data set.
Specifically, the trend of each classified monitoring data set is analyzed to obtain the variation trend of the harmonic voltage and the harmonic current corresponding to each classified data, the corresponding prediction is performed, during the trend analysis prediction, a mode of constructing a mathematical model, such as a neural network model and a markov model, can be used, the monitoring data sets, the harmonic voltage and the harmonic current are learned through a machine learning model, the logical relationship of the trends among the monitoring data sets, the harmonic voltage and the harmonic current is constructed, and the trend prediction of the harmonic voltage and the harmonic current is performed. In order to provide management and control of each bit of bonding circuit for each user, the embodiment of the application respectively analyzes and predicts the classification data sets, namely, a first classification data set which is classification of a root node is obtained from classification tree level relation of the monitoring data sets, harmonic voltage and current trend prediction is carried out on corresponding monitoring data in the first classification data set, trend prediction is carried out on a second classification data set of a sub-node, correlation of the trends between the two classifications is carried out according to characteristic relation between the first classification and the second classification, if the first classification is the power utilization condition of one building and the second classification is the power utilization characteristic of a user in the building, the power utilization prediction of the second classification has an influence on the trend of the first classification, the analysis and prediction are carried out according to the trend relation between the first classification and the second classification, the prediction range is gradually reduced, when the relation processing of the classifications is carried out, the analysis and prediction range is determined according to the requirement of the analysis and prediction, if the current circuit analysis is used for carrying out on the balance of the circuit control between the cells, the power utilization data of the first classification is used as effective high-load prediction of the building, and the effective user control is taken as the requirement of the current high-load prediction of the user, and the user control, and the high-oriented load of the high-oriented load prediction of the user is taken as the requirement of the effective user. Corresponding analysis and prediction are carried out through different classification groups, and different circuit control requirements can be met.
Step S700: and carrying out power utilization evaluation according to the monitoring and predicting information set, and determining a circuit control scheme.
Further, the determining a circuit control scheme according to the power utilization assessment performed by the monitoring prediction information set includes: acquiring the first prediction influence information, the second prediction influence information and the classification tree level relation of the monitoring data set based on the monitoring prediction information set; obtaining a first classification second classification influence relation according to the classification tree level relation of the monitoring data set; determining a multi-stage influence result according to the first prediction influence information, the second prediction influence information and the first classification and second classification influence relation; determining a hierarchical circuit control requirement according to the multi-level influence result and the classification tree level relation of the monitoring data set; determining the circuit control scheme according to the hierarchical circuit control requirements based on the classification tree level relationship of the monitoring data set.
Further, the method further comprises: obtaining a first electric characteristic according to the first classification requirement characteristic; and determining the control requirement of the grading circuit according to the first electric characteristic and the multi-grade influence result.
Specifically, the analysis and prediction results of various categories in the monitoring and prediction information set directly correspond to how the circuit control is performed, so that different circuit control schemes are customized. Because hierarchical tree-level relations are adopted in classification, trends among all levels can be influenced, in order to analyze and process lower-level more accurately, the tree-level relations need to be referred to, and cooperation processing is carried out through relevance among all levels to ensure the power utilization control requirements of all levels. In the determination process of performing control of each classification circuit, the embodiment of the application considers the main electricity utilization characteristics of each hierarchy and performs specific analysis by combining with specific electricity utilization characteristics, for example, the current circuit control scheme is customized by considering the electricity utilization of each user of the whole building, the electricity utilization characteristics of the users are analyzed, some users use more electric appliances with high-load electric quantity, the electricity utilization characteristics of the users need synchronous high-load electricity utilization, some users have small electricity utilization load, the electricity utilization condition of each user needs to be ensured, the electricity utilization requirements of the whole building and the whole cell need to be ensured, comprehensive analysis processing needs to be performed according to the electricity utilization characteristics of different users and the electricity utilization condition of the whole building, corresponding control is performed by combining the harmonic voltage, the current and the prediction trend, so as to ensure the use safety of the electric equipment of each user, the circuit harmonic analysis is applied to the electricity utilization control of the users, more accurate circuits are provided for each user, the safety of the electric appliances used by the users is ensured, the stability of the voltage and the current in the circuit use guidance process in the prior art is not influenced by the actual high electricity utilization condition of the users.
In summary, the embodiment of the present application has the following technical effects:
1. classifying the processed monitoring data based on a preset classification requirement to obtain a monitoring data classification set; respectively carrying out Fourier transform operation on all the monitoring data sets to obtain a harmonic voltage set and a harmonic current set; the trend analysis is carried out on the monitoring data set according to the harmonic voltage set and the harmonic current set, the aim of carrying out targeted harmonic analysis according to the classified monitoring data set is achieved, the corresponding control is carried out by combining the magnitude of the harmonic voltage and the current and the prediction trend, so that the use safety of the electrical equipment of each user is ensured, the circuit harmonic analysis is applied to the user electricity control system, a reliable circuit is more accurately provided for each user, the use safety of the electrical equipment of the user is ensured, and the technical effects of maintaining the stability of the voltage and the current in the circuit are achieved.
2. The real-time monitoring data are preprocessed, interference signals in the real-time monitoring data acquisition process are filtered, processing monitoring data are obtained, data with sampling burrs removed or data with transmission errors caused by interference are corrected, and a basic technical effect is provided for accurate harmonic analysis.
3. Constructing a classification tree level relation based on the classification characteristic information; performing feature comparison extraction on the processing monitoring data according to the classification feature information to obtain a feature classification cluster; and performing tree-level division on the feature classification clusters according to the classification tree-level relation to obtain the monitoring data classification set. The method achieves the technical effects that the monitoring data are classified according to different classification characteristics, the tree level relation is constructed to determine the relation of each level, the guarantee is provided for classification harmonic analysis and prediction, and the accuracy of classification prediction analysis results of each level is further improved based on the construction of the classification tree level relation.
Example two
Based on the same inventive concept as the harmonic analysis method based on the real-time monitoring data of the electric meter in the foregoing embodiment, the present invention further provides a harmonic analysis system based on the real-time monitoring data of the electric meter, please refer to fig. 2, where the system includes:
the first obtaining unit 11 is used for acquiring real-time monitoring data through an intelligent electric meter and sending the real-time monitoring data to a harmonic analysis system;
the second obtaining unit 12 is configured to, by the harmonic analysis system, pre-process the real-time monitoring data, and filter an interference signal in a real-time monitoring data acquisition process to obtain processed monitoring data;
a third obtaining unit 13, where the third obtaining unit 13 is configured to obtain a preset classification requirement;
a fourth obtaining unit 14, where the fourth obtaining unit 14 is configured to classify the processed monitoring data based on the preset classification requirement to obtain a monitoring data classification set, where the monitoring data classification set includes multiple monitoring data sets;
a fifth obtaining unit 15, where the fifth obtaining unit 15 is configured to obtain a harmonic voltage set and a harmonic current set by performing fourier transform operation on all monitoring data sets, respectively;
a sixth obtaining unit 16, where the sixth obtaining unit 16 is configured to perform trend analysis on the monitoring data sets according to the harmonic voltage set and the harmonic current set, respectively, to obtain monitoring prediction information sets, where the monitoring prediction information sets correspond to the monitoring data sets;
a first determining unit 17, wherein the first determining unit 17 is used for carrying out power utilization evaluation according to the monitoring prediction information set and determining a circuit control scheme.
Further, the system further comprises:
a seventh obtaining unit, configured to obtain a first continuous queue according to the real-time monitoring data;
an eighth obtaining unit, configured to obtain a second continuous queue, set the second continuous queue at the tail of the first continuous queue, and form a first calculation queue;
a ninth obtaining unit, configured to perform an average operation on the first calculation queue to obtain a first average value;
a tenth obtaining unit, configured to obtain a third continuous queue, set the third continuous queue at the tail of the first computation queue, remove the first continuous queue, and form a second computation queue;
an eleventh obtaining unit, configured to perform an average operation on the second calculation queue to obtain a second average value;
and the second determining unit is used for determining a filtering requirement value according to the first average value and the second average value, and filtering the real-time monitoring data based on the filtering requirement value to obtain the processing monitoring data.
Further, the system further comprises:
a twelfth obtaining unit, configured to obtain classification feature information according to the preset classification requirement;
a first constructing unit, configured to construct a classification tree level relationship based on the classification feature information;
a thirteenth obtaining unit, configured to perform feature comparison extraction on the processing monitoring data according to the classification feature information, so as to obtain a feature classification cluster;
a fourteenth obtaining unit, configured to perform tree level division on the feature classification clusters according to the classification tree level relationship, so as to obtain the monitoring data classification set.
Further, the system further comprises:
a fifteenth obtaining unit, configured to obtain a first classified data set according to a classification tree level relationship of the monitoring data set;
a sixteenth obtaining unit, configured to obtain a harmonic voltage and a harmonic current of the first classified data set according to the first classified data set;
a seventeenth obtaining unit, configured to obtain a first classification requirement characteristic according to the first classification dataset;
an eighteenth obtaining unit, configured to obtain first predicted influence information according to the first classification requirement characteristic, the harmonic voltage of the first classification data set, and the harmonic current;
a first execution unit, configured to repeatedly obtain a second classified data set and a third classified data set until an nth classified data set, and determine respective predicted influence information based on the second classified data set and the third classified data set until the nth classified data set, where the respective predicted influence information is second predicted influence information and until the nth predicted influence information;
a nineteenth obtaining unit, configured to obtain the monitoring prediction information set based on the first prediction influence information, the second prediction influence information, up to nth prediction influence information, and a classification tree level relationship of the monitoring data set.
Further, the system further comprises:
a second execution unit to obtain the first prediction impact information, second prediction impact information, a classification tree level relationship of the monitoring data set based on the monitoring prediction information set;
a twentieth obtaining unit, configured to obtain a first classification second classification influence relationship according to the classification tree level relationship of the monitoring data set;
a third determining unit, configured to determine a multi-level influence result according to the first predicted influence information, the second predicted influence information, and the first classification second classification influence relationship;
a fourth determining unit, configured to determine a hierarchical circuit control requirement according to the multi-level influence result and a classification tree level relationship of the monitoring data set;
a fifth determination unit to determine the circuit control scheme according to the hierarchical circuit control requirement based on a classification tree level relationship of the monitoring dataset.
Further, the system further comprises:
a twenty-first obtaining unit, configured to obtain a first electricity characteristic according to the first classification requirement characteristic;
a sixth determining unit, configured to determine a hierarchical circuit control requirement according to the first electrical characteristic and the multi-level influence result.
Further, the system further comprises:
a second constructing unit configured to construct a regression function based on the harmonic voltage set and the harmonic current set;
the third execution unit is used for performing coefficient calculation on the regression function, determining a regression function coefficient and optimizing the regression function by using the regression function coefficient;
a twentieth obtaining unit, configured to perform harmonic impedance calculation on the harmonic voltage set and the harmonic current set by using the regression function to obtain a harmonic impedance estimation value;
and the seventh determining unit is used for carrying out trend analysis according to the harmonic voltage set and the harmonic current set based on the harmonic impedance estimated value and determining monitoring and predicting information.
In the present description, each embodiment is described in a progressive manner, and the emphasis of each embodiment is to be described in anticipation of the differences of other embodiments, and the foregoing harmonic analysis method based on the electric meter real-time monitoring data in the first embodiment in fig. 1 and the specific example are also applicable to the harmonic analysis system based on the electric meter real-time monitoring data in this embodiment. The device disclosed in the embodiment corresponds to the method disclosed in the embodiment, so that the description is simple, and the relevant points can be referred to the description of the method part.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Exemplary electronic device
The electronic device of the embodiment of the present application is described below with reference to fig. 3.
Fig. 3 illustrates a schematic structural diagram of an electronic device according to an embodiment of the present application.
Based on the inventive concept of the harmonic analysis method based on the real-time monitoring data of the electric meter in the foregoing embodiments, the present invention further provides a harmonic analysis system based on the real-time monitoring data of the electric meter, wherein the harmonic analysis system comprises a computer program stored thereon, and the computer program is executed by a processor to implement the steps of any one of the methods of the harmonic analysis method based on the real-time monitoring data of the electric meter.
Where in fig. 3 a bus architecture (represented by bus 300), bus 300 may include any number of interconnected buses and bridges, bus 300 linking together various circuits including one or more processors, represented by processor 302, and memory, represented by memory 304. The bus 300 may also link together various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further herein. A bus interface 305 provides an interface between the bus 300 and the receiver 301 and transmitter 303. The receiver 301 and the transmitter 303 may be the same element, i.e., a transceiver, providing a means for communicating with various other apparatus over a transmission medium.
The processor 302 is responsible for managing the bus 300 and general processing, and the memory 304 may be used for storing data used by the processor 302 in performing operations.
In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:
the application provides a harmonic analysis method and system based on real-time monitoring data of an electric meter, wherein the real-time monitoring data is acquired through an intelligent electric meter and is sent to a harmonic analysis system; the harmonic analysis system is used for preprocessing the real-time monitoring data, filtering interference signals in the real-time monitoring data acquisition process and obtaining processing monitoring data; obtaining a preset classification requirement; classifying the processing monitoring data based on the preset classification requirement to obtain a monitoring data classification set, wherein the monitoring data classification set comprises a plurality of monitoring data sets; respectively carrying out Fourier transform operation on all the monitoring data sets to obtain a harmonic voltage set and a harmonic current set; performing trend analysis on the monitoring data set according to the harmonic voltage set and the harmonic current set respectively to obtain a monitoring prediction information set, wherein the monitoring prediction information set corresponds to the monitoring data set; and carrying out power utilization evaluation according to the monitoring and predicting information set, and determining a circuit control scheme. The method has the advantages that targeted harmonic analysis is carried out according to classified data sets, corresponding control is carried out by combining the sizes of harmonic voltage and current and prediction trend, so that the use safety of electrical equipment of each user is ensured, the circuit harmonic analysis is applied to the power utilization control of the user, a reliable circuit is provided for each user more accurately, the use safety of user electrical appliances is ensured, and the technical effects of maintaining the stability of voltage and current in the circuit are achieved, so that the technical problems that the accuracy of the harmonic analysis in the process of guiding the use of the circuit is not high and the actual power utilization condition of the user is influenced in the prior art are solved.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, apparatus, or computer program product. Accordingly, the present application may take the form of an entirely software embodiment, an entirely hardware embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application is in the form of a computer program product that may be embodied on one or more computer-usable storage media having computer-usable program code embodied therewith. And such computer-usable storage media include, but are not limited to: various media capable of storing program codes, such as a usb disk, a portable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk Memory, a Compact Disc Read-Only Memory (CD-ROM), and an optical Memory.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a system for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction system which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks. While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the same technology as the present invention, it is intended that the present invention encompass such modifications and variations as well.
Claims (9)
1. A harmonic wave analysis method based on real-time monitoring data of an electric meter is characterized in that the method is applied to a harmonic wave analysis system, and the harmonic wave analysis system comprises an intelligent electric meter; the method comprises the following steps:
acquiring real-time monitoring data through an intelligent ammeter, and sending the real-time monitoring data to a harmonic analysis system;
the harmonic analysis system is used for preprocessing the real-time monitoring data, filtering interference signals in the real-time monitoring data acquisition process and obtaining processing monitoring data;
obtaining a preset classification requirement;
classifying the processing monitoring data based on the preset classification requirement to obtain a monitoring data classification set, wherein the monitoring data classification set comprises a plurality of monitoring data sets;
respectively carrying out Fourier transform operation on all the monitoring data sets to obtain a harmonic voltage set and a harmonic current set;
performing trend analysis on the monitoring data set according to the harmonic voltage set and the harmonic current set respectively to obtain a monitoring and predicting information set, wherein the monitoring and predicting information set corresponds to the monitoring data set;
carrying out power utilization evaluation according to the monitoring and predicting information set, and determining a circuit control scheme;
the method further comprises the following steps:
based on the monitoring current and the monitoring voltage in all the monitoring data sets, obtaining corresponding harmonic voltage and harmonic current through fast Fourier change;
fitting and constructing a regression function;
performing coefficient calculation on the regression function, determining a regression function coefficient, and optimizing the regression function by using the regression function coefficient;
performing harmonic impedance calculation on the harmonic voltage set and the harmonic current set by using the regression function to obtain a harmonic impedance estimation value;
and determining the harmonic voltage set and the harmonic current set based on the harmonic impedance estimated value, the harmonic voltage and the harmonic current.
2. The method of claim 1, wherein the preprocessing the real-time monitoring data to filter interference signals during the real-time monitoring data acquisition process to obtain processed monitoring data comprises:
acquiring a first continuous queue according to the real-time monitoring data;
obtaining a second continuous queue, and arranging the second continuous queue at the tail of the first continuous queue to form a first calculation queue;
carrying out average operation on the first calculation queue to obtain a first average value;
obtaining a third continuous queue, arranging the third continuous queue at the tail of the first calculation queue, and removing the first continuous queue to form a second calculation queue;
carrying out average operation on the second calculation queue to obtain a second average value;
and determining a filtering requirement value according to the first average value and the second average value, and filtering the real-time monitoring data based on the filtering requirement value to obtain the processing monitoring data.
3. The method of claim 1, wherein the classifying the process monitoring data based on the preset classification requirement obtains a monitoring data classification set, the monitoring data classification set including a plurality of monitoring data sets, including:
obtaining classification characteristic information according to the preset classification requirement;
constructing a classification tree level relation based on the classification characteristic information;
performing feature comparison extraction on the processing monitoring data according to the classification feature information to obtain a feature classification cluster;
and performing tree-level division on the feature classification clusters according to the classification tree-level relation to obtain the monitoring data classification set.
4. The method of claim 3, wherein the trend analyzing the monitoring data set according to the harmonic voltage set and the harmonic current set respectively to obtain a monitoring prediction information set, wherein the monitoring prediction information set corresponds to the monitoring data set, and comprises:
obtaining a first classification data set according to the classification tree level relation of the monitoring data set;
obtaining harmonic voltage and harmonic current of the first classified data set according to the first classified data set;
obtaining a first classification requirement characteristic according to the first classification data set;
obtaining first prediction influence information according to the first classification requirement characteristics, the harmonic voltage and the harmonic current of the first classification data set;
repeatedly obtaining a second classified data set and a third classified data set until an Nth classified data set, and determining respective predicted influence information based on the second classified data set and the third classified data set until the Nth classified data set, wherein the second predicted influence information and the Nth predicted influence information are respectively the second predicted influence information and the Nth predicted influence information;
and obtaining the monitoring prediction information set based on the first prediction influence information, the second prediction influence information, the Nth prediction influence information and the classification tree level relation of the monitoring data set.
5. The method of claim 4, wherein said evaluating power usage based on said set of monitored predictive information, determining a circuit control scheme, comprises:
acquiring the first prediction influence information, the second prediction influence information and the classification tree level relation of the monitoring data set based on the monitoring prediction information set;
obtaining a first classification second classification influence relation according to the classification tree level relation of the monitoring data set;
determining a multi-stage influence result according to the first prediction influence information, the second prediction influence information and the first classification second classification influence relation;
determining a hierarchical circuit control requirement according to the multi-level influence result and the classification tree level relation of the monitoring data set;
determining the circuit control scheme according to the hierarchical circuit control requirements based on the classification tree level relationship of the monitoring data set.
6. The method of claim 5, wherein the method further comprises:
obtaining a first electric characteristic according to the first classification requirement characteristic;
and determining the control requirement of the grading circuit according to the first electric characteristic and the multi-grade influence result.
7. A harmonic analysis system based on real-time monitoring data of an electricity meter, the system comprising:
the system comprises a first obtaining unit, a harmonic analysis system and a second obtaining unit, wherein the first obtaining unit is used for acquiring real-time monitoring data through an intelligent electric meter and sending the real-time monitoring data to the harmonic analysis system;
the second obtaining unit is used for preprocessing the real-time monitoring data by the harmonic analysis system, filtering interference signals in the real-time monitoring data acquisition process and obtaining processing monitoring data;
a third obtaining unit, configured to obtain a preset classification requirement;
a fourth obtaining unit, configured to classify the processed monitoring data based on the preset classification requirement to obtain a monitoring data classification set, where the monitoring data classification set includes multiple monitoring data sets;
a fifth obtaining unit, configured to obtain a harmonic voltage set and a harmonic current set by performing fourier transform operation on all monitoring data sets, respectively;
a sixth obtaining unit, configured to perform trend analysis on the monitoring data set according to the harmonic voltage set and the harmonic current set, respectively, to obtain a monitoring prediction information set, where the monitoring prediction information set corresponds to the monitoring data set;
a first determination unit for performing power consumption evaluation according to the monitoring prediction information set, and determining a circuit control scheme;
a second construction unit, configured to construct a regression function based on the harmonic voltage set and the harmonic current set;
the third execution unit is used for performing coefficient calculation on the regression function, determining a regression function coefficient and optimizing the regression function by using the regression function coefficient;
a twentieth obtaining unit, configured to perform harmonic impedance calculation on the harmonic voltage set and the harmonic current set by using the regression function to obtain a harmonic impedance estimation value;
and the seventh determining unit is used for carrying out trend analysis according to the harmonic voltage set and the harmonic current set based on the harmonic impedance estimated value and determining monitoring and predicting information.
8. A harmonic analysis system based on real-time monitoring data of an electricity meter, comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method of any one of claims 1 to 6 when executing the program.
9. A computer-readable storage medium, characterized in that the storage medium has stored thereon a computer program which, when being executed by a processor, carries out the steps of the method according to any one of claims 1-6.
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