CN114219102A - Operation and maintenance method and device for electric power metering equipment, terminal and storage medium - Google Patents
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Abstract
The invention relates to the technical field of power metering, in particular to a method, a device, a terminal and a storage medium for operation and maintenance of power metering equipment. According to the embodiment of the invention, the abnormal state of the second metering equipment is found through line loss, the rotation from 'due rotation' to 'state rotation' is realized, the replacement of unnecessary objects is reduced, the maintenance workload is reduced, and the unnecessary labor consumption is reduced.
Description
Technical Field
The invention relates to the technical field of electric power metering, in particular to an operation and maintenance method, device, terminal and storage medium for electric power metering equipment.
Background
In order to avoid waste of materials and manpower caused by 'due rotation' on the premise of ensuring normal operation of the electric power metering equipment, the selection of the operation and maintenance method of the electric power metering equipment is very important. The good operation and maintenance strategy can reduce the waste of resources and promote the sustainable development of energy.
Meanwhile, with the development of the power market and big data, the analysis and utilization of data related to electric energy become more and more important. If the rotation mechanism of the electric power metering equipment is rotated from 'due rotation' to 'state rotation', the service life of the electric power metering equipment is greatly prolonged, and meanwhile, unnecessary operation and maintenance manpower consumption is reduced.
Based on this, it is necessary to develop and design an operation and maintenance method for the electric power metering equipment.
Disclosure of Invention
The embodiment of the invention provides an operation and maintenance method, device, terminal and storage medium of electric power metering equipment, which are used for solving the problem that due rotation is adopted in the prior art, so that resource waste is easily caused.
In a first aspect, an embodiment of the present invention provides an operation and maintenance method for an electric power metering device, including: acquiring the state of first metering equipment, wherein the first metering equipment is power metering equipment of a bus;
if the first metering equipment is in a good state, acquiring the current line loss, wherein the line loss is the deviation between the sum of the metering data of each feeder line and the metering data of the bus, and the feeder line is a feeder line connected with the bus;
determining a state of a second metering device set according to the current line loss, wherein the second metering device set comprises second metering devices of the feeder lines connected with the bus;
if the state of the second metering equipment set is abnormal, determining second metering equipment which generates the abnormality;
and sending the maintenance information of the second metering equipment with the abnormality to the terminal equipment of the maintenance personnel.
In some embodiments, the obtaining the state of the first metrology device comprises:
acquiring operating environment data of the first metering equipment, wherein the operating environment data is used for representing the operating environment of the first metering equipment;
inputting the operating environment data into the neural network model to obtain the expected life of the first metering equipment, wherein the neural network is an LSTM neural network which is subjected to predictive training;
if the expected life is greater than a first threshold, determining that the status of the first metering device is good.
In some embodiments, the determining a state of a second set of metrology devices from the current line loss comprises:
acquiring a line loss curve and current metering data of the bus, wherein the line loss curve is a curve representing the relation between the bus metering data and the line loss;
determining target line loss according to the current metering data and the line loss curve;
and if the deviation between the current line loss and the target line loss is larger than a second threshold value, determining that the state of the second metering equipment set is abnormal.
In some embodiments, the obtaining a line loss curve includes:
acquiring historical metering data and historical line loss of the bus in multiple periods;
and fitting the historical metering data of the multiple periods and the historical line loss to generate the line loss curve.
In some embodiments, the determining a second metrology device generating an anomaly comprises:
for each second metrology device, performing the steps of:
acquiring a current metering data set and a plurality of historical metering data sets, wherein the metering data sets are sets of metering data of the second metering device in a preset metering time;
selecting one historical metering data set which is closest to the current metering data set from the plurality of historical metering data sets as a comparison metering data set;
calculating the deviation between a first average value and a second average value, wherein the first average value is the average value of all metering data in the current metering data set, and the second average value is the average value of all metering data in the comparison metering data set;
and if the deviation of the first average value and the second average value is larger than a third threshold value, determining that the second metering device generates an abnormality.
In some embodiments, said selecting one of said historical metrology data sets that is closest to said current metrology data set as a comparison metrology data set comprises:
respectively carrying out normalization processing on the current measurement data set and each historical measurement data set;
generating a probability curve according to the current measurement data set to serve as a first curve;
generating a probability curve according to the historical measurement data set to serve as a second curve;
selecting the second curve most similar to the first curve as a closest curve;
and taking the historical measurement data set corresponding to the closest curve as the comparison measurement data set.
In some embodiments, the sending the maintenance information of the second metering device generating the abnormality to the maintenance personnel includes:
obtaining an identification of the second metering device that generated the anomaly, the identification including at least one of: the name, model and installation location of the second metering device;
and sending the identification to the terminal equipment of the maintainer.
In a second aspect, an embodiment of the present invention provides an operation and maintenance device for an electric power metering device, including:
the system comprises a first state acquisition module, a second state acquisition module and a control module, wherein the first state acquisition module is used for acquiring the state of first metering equipment, and the first metering equipment is electric power metering equipment of a bus;
the line loss acquisition module is used for acquiring the current line loss when the first metering equipment is in a good state, wherein the line loss is the deviation between the sum of the metering data of each feeder line and the metering data of the bus, and the feeder line is a feeder line connected with the bus;
a second state obtaining module, configured to determine a state of a second metering device set according to the current line loss, where the second metering device set includes second metering devices of feeder lines connected to the bus;
the abnormality determining module is used for determining second metering equipment which generates abnormality when the state of the second metering equipment set is abnormal; and the number of the first and second groups,
and the output module is used for sending the maintenance information of the second metering equipment with the abnormity to a terminal of a maintenance worker.
In a third aspect, an embodiment of the present invention provides a terminal, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the steps of the method according to the first aspect or any one of the possible implementation manners of the first aspect when executing the computer program.
In a fourth aspect, the present invention provides a computer-readable storage medium, which stores a computer program that, when executed by a processor, implements the steps of the method as described in the first aspect or any one of the possible implementations of the first aspect.
Compared with the prior art, the implementation mode of the invention has the following beneficial effects:
the embodiment of the invention discloses an operation and maintenance method of electric power metering equipment, which comprises the steps of firstly obtaining the state of bus electric power metering equipment, obtaining line loss when the state is good, wherein the line loss is the deviation of metering data of a bus and each feeder line, when the deviation is large, determining that one metering equipment of the feeder line is abnormal, and after determining abnormal equipment, maintaining the abnormal equipment. According to the embodiment of the invention, the abnormal state of the second metering equipment is found through line loss, the rotation from 'due rotation' to 'state rotation' is realized, the replacement of unnecessary objects is reduced, the maintenance workload is reduced, and the unnecessary labor consumption is reduced.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments or the prior art description will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without inventive labor.
FIG. 1 is a flow chart of an operation and maintenance method of an electric power metering device according to an embodiment of the present invention;
FIG. 2 is a diagram of a recurrent neural network structure and its development in the time domain, provided by an embodiment of the present invention;
FIG. 3 is a diagram of a basic structure of an LSTM network model provided by an embodiment of the present invention;
FIG. 4 is a schematic diagram of a sampling method comparing similarity of two curves according to an embodiment of the present invention;
fig. 5 is a functional block diagram of an operation and maintenance device of an electric power metering apparatus according to an embodiment of the present invention;
fig. 6 is a functional block diagram of a terminal according to an embodiment of the present invention.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.
In order to make the objects, technical solutions and advantages of the present invention more apparent, the following description is made with reference to the accompanying drawings.
The following is a detailed description of the embodiments of the present invention, which is implemented on the premise of the technical solution of the present invention, and a detailed implementation manner and a specific operation process are given, but the scope of the present invention is not limited to the following embodiments.
Fig. 1 is a flowchart of an operation and maintenance method of an electric power metering device according to an embodiment of the present invention.
As shown in fig. 1, it shows a flowchart of an implementation of an operation and maintenance method of an electric power metering device provided by an embodiment of the present invention, which is detailed as follows:
in step 101, a state of a first metering device is obtained, where the first metering device is a power metering device of a bus.
In some embodiments, the step 101 comprises:
acquiring operating environment data of the first metering equipment, wherein the operating environment data is used for representing the operating environment of the first metering equipment;
inputting the operating environment data into the neural network model to obtain the expected life of the first metering equipment, wherein the neural network is an LSTM neural network which is subjected to predictive training;
if the expected life is greater than a first threshold, determining that the status of the first metering device is good.
For example, a typical power grid structure is that a bus connects a plurality of feeder lines to supply power to the plurality of feeder lines, and the power data of the bus should be the sum of the power data of the feeder lines connected to the bus. Power data such as instantaneous power, power consumption for a period of time.
Based on the principle, the inventive method verifies the validity of each other by adopting the electric energy data of the bus and the electric energy data of each feeder line, and further shows whether each electric power metering device on the bus and the feeder line operates reliably and accurately. The waste of materials and manpower for periodically maintaining and updating the electric power metering equipment in the prior art is avoided.
The metering equipment for metering the bus bar is generally high in accuracy, better in reliability requirement than usual application, and generally ideal in application environment, and therefore, a metering instrument of the bus bar should be used as a reference.
Whether the power metering equipment of the bus runs reliably or not is in a close and inseparable relation with the running environment, the running environment condition is good, and detection and regulation equipment is arranged. The detection data such as temperature, humidity, etc. can be used as the condition for predicting the life expectancy of the electric power metering equipment.
The embodiment of the invention provides a method for predicting the service life of electric power metering equipment by adopting a neural network. Specifically an LSTM network.
An LSTM Network (Long Short-Term Memory Network) is a time-cycle Neural Network, and is specially designed to solve the Long-Term dependence problem of a general RNN (recurrent Neural Network), and all RNNs have a chain form of a repetitive Neural Network module.
Fig. 2 shows a Recurrent Neural Network (RNN) structure and its time domain expansion form, in which its internal recurrent neural unit forms a hidden layer in the RNN network, and the output of each network node is fed back to itself and its next node at the same time, and this multi-stage feedback mechanism makes the RNN network have a memory function. At time t, the hidden layer accepts the input x at the current timetAnd the state h of the previous moment itselft-1And a ring network structure is formed, so that the RNN has certain short-term memory capability. In addition, the parameters can be shared, so that the method has an advantage in learning the nonlinear characteristics of the processing sequence.
In FIG. 2, U is the weight matrix from the input layer to the hidden layer, V is the weight matrix from the hidden layer to the output layer, W is the last value of the hidden layer as the weight of the input of this time, stIs a hidden state at time t, otIs the output at time t, xtIs the input at time t, is the storage unit of the network, as an n-dimensional vector.
The RNN usually adopts a back propagation algorithm for model training, but due to the structural defect, when inputting long sequence data, the network parameters will be exponentially attenuated or enhanced as the network deepens, and the gradient value will be approximately equal to 0 or approach to infinity, which results in gradient extinction and gradient explosion problems. Due to the rapid development of the deep learning field in recent times, the related research and application are increasingly deep, and corresponding solutions are provided for the problems of the recurrent neural network.
The LSTM network model provides a new solution in dealing with long time dependent sequence problems, which is essentially a special RNN network. In contrast to RNN internal neurons, LSTM not only includes a short term memory state control unit h, but also adds a memory for a long term memory control unit c, which updates more frequently than a long term memory control unit c. The LSTM recurrent neural network overcomes the defects of the RNN model by simultaneously having short-term memory neurons and long-term memory neurons, so that the LSTM recurrent neural network can effectively process long-interval time sequence data.
Fig. 3 shows a basic structure of an LSTM network model, where a forgetting gate, an input gate, and an output gate are introduced into the LSTM network, and all the units cooperate together to complete the update and forgetting of control memory, so as to implement the storage and flow of memory in a hidden layer unit, and improve the prediction accuracy of the network. Shown in fig. 3, the LSTM network passes a forgetting valve ftInput valve itOutput valve otAnd control unit state CtAnd determining which data need to be reserved and which data need to be forgotten, and further solving the long-distance dependence problem of the RNN.
For the embodiment of the invention, the invention inputs the collected environment monitoring data into the trained LSTM network, and predicts the life expectancy of the electric power metering equipment through the LSTM network.
In the training of the LSTM network, historical data of the electric power metering equipment is adopted to train the LSTM network.
Before training, a training sample set and a verification sample set should be prepared, wherein the training sample set and the verification sample set are data sets formed by historical monitoring data, and each monitoring data is marked with a life label.
After training by adopting the training sample set, verifying by the verification sample set, the prediction precision of the trained neural network is gradually improved along with the training, and when the prediction precision verified by the verification sample set is not obviously improved, the transmission parameters of the neural network can be fixed to be used as the LSTM neural network subjected to the prediction training.
When the state of the bus power metering equipment needs to be acquired, firstly, data of an operating environment, such as temperature, humidity and dust concentration, are acquired, then the data are input into a neural network model, an expected service life is obtained, and if the service life is lower than a threshold value, the power metering equipment is good in operating state, free of maintenance and reliable in precision.
In step 102, if the state of the first metering device is good, a current line loss is obtained, where the line loss is a deviation between a sum of the metering data of each feeder line and the metering data of the bus, and the feeder line is a feeder line connected to the bus.
Illustratively, as mentioned above, the power data of the bus should be the sum of the power data of the feeder lines connected to the bus lines, which is a theoretical value, and there is usually a certain deviation between the two due to manufacturing error, line transmission loss and operation environment, and the deviation is generally called line loss.
In the method of obtaining the line loss, a common method is to obtain data of the bus power metering device, and then obtain a sum of the data of the power metering devices on each feeder line, and take a difference between the two data as the line loss.
In step 103, a state of a second metering device set is determined according to the current line loss, wherein the second metering device set includes second metering devices of the feeder lines connected to the bus.
In some embodiments, step 103 comprises:
acquiring a line loss curve and current metering data of the bus, wherein the line loss curve is a curve representing the relation between the bus metering data and the line loss;
determining target line loss according to the current metering data and the line loss curve;
and if the deviation between the current line loss and the target line loss is larger than a second threshold value, determining that the state of the second metering equipment set is abnormal.
In some embodiments, the obtaining a line loss curve includes:
acquiring historical metering data and historical line loss of the bus in multiple periods;
and fitting the historical metering data of the multiple periods and the historical line loss to generate the line loss curve.
The operating state of the power metering device on each feeder line can be seen by line loss. If the operation state of each power metering device is good, the line loss should be within a certain interval range. The embodiment of the invention provides creative labor, can provide more accurate reference, and improves the sensitivity of identifying the operation state of each electric power metering device on the feeder line.
The embodiment of the invention is characterized in that under different historical conditions, bus metering data and synchronous line loss are obtained to form a coordinate point of which the metering data corresponds to the line loss, a plurality of coordinate points are connected to fit a line loss curve, and the line loss curve is formed by fitting real historical data, so that the accuracy is higher than that of a theoretical calculation or modeling mode.
And when the current line loss is determined to be abnormal, acquiring a corresponding line loss target in a line loss curve through the current metering data, wherein the line loss corresponding to the current metering data is within a reasonable range of the line loss target, and if the line loss exceeds the range, the power metering equipment of at least one feeder line is abnormal.
In step 104, if the status of the second metering device set is abnormal, a second metering device with an abnormality is determined.
In some embodiments, step 104 comprises:
for each second metrology device, performing the steps of:
acquiring a current metering data set and a plurality of historical metering data sets, wherein the metering data sets are sets of metering data of the second metering device in a preset metering time;
selecting one historical metering data set which is closest to the current metering data set from the plurality of historical metering data sets as a comparison metering data set;
calculating the deviation between a first average value and a second average value, wherein the first average value is the average value of all metering data in the current metering data set, and the second average value is the average value of all metering data in the comparison metering data set;
and if the deviation of the first average value and the second average value is larger than a third threshold value, determining that the second metering device generates an abnormality.
In some embodiments, said selecting one of said historical metrology data sets that is closest to said current metrology data set as a comparison metrology data set comprises:
respectively carrying out normalization processing on the current measurement data set and each historical measurement data set;
generating a probability curve according to the current measurement data set to serve as a first curve;
generating a probability curve according to the historical measurement data set to serve as a second curve;
selecting the second curve most similar to the first curve as a closest curve;
and taking the historical measurement data set corresponding to the closest curve as the comparison measurement data set.
For example, for each feeder line's power metering device, its metering accuracy should be determined.
One way is to mine similar parts from the historical data by comparing the historical data with the current metering data, and if the deviation between the historical data and the current metering data is larger, the feeder line is considered to be maintained.
In practice, measurement data of a recent time interval is usually obtained. And acquiring a plurality of historical metering data according to the interval length.
The measurement data is normalized, and one normalization processing mode is determined according to the following formula:
in the formula: x'iFor normalized data, xiFor data in a certain historical data set, xminIs the minimum value, x, in the historical data setmaxFor the maximum value in the historical data set, 0<i is less than or equal to n, and n is the total amount of data in the historical data set.
After the data are normalized, all the data of the data set are distributed in an interval of 0-1.
The mean x' and variance σ are then calculated from each normalized data set2Finally according to the mean x' and the variance σ2The distribution function f (x') is calculated.
In the aspect of comparing the similarity of the curves, a sampling method can be adopted, and fig. 4 shows a schematic diagram of comparing the similarity of the two curves by the sampling method.
In the figure, the abscissa is a normalized numerical value, and the ordinate is a probability of occurrence. The first curve 401 and the second curve 402 respectively sample j points, the amplitude value of which means the probability value, wherein the first curve samples j points and is marked as qjWherein the first curve samples j points and is denoted as qkjThe similarity of the two curves can be shown by the euclidean distance:
further, it is possible to obtain:
for a plurality of SkAnd sorting, selecting the curve corresponding to the minimum value as the closest curve, and taking the historical measurement data set corresponding to the curve as a comparison measurement data set.
When the deviation of the two data sets exceeds a threshold value, the power metering device is indicated to generate an abnormality.
In step 105, the maintenance information of the second metering device generating the abnormality is sent to the terminal device of the maintenance person.
In some possible implementation embodiments, the sending the maintenance information of the second metering device generating the abnormality to the maintenance personnel includes:
obtaining an identification of the second metering device that generated the anomaly, the identification including at least one of: the name, model and installation location of the second metering device;
and sending the identification to the terminal equipment of the maintainer.
The invention relates to an implementation mode of an operation and maintenance method of electric power metering equipment, which comprises the steps of firstly obtaining the state of bus electric power metering equipment, obtaining line loss when the state is good, wherein the line loss is the deviation of metering data of a bus and each feeder line, when the deviation is large, determining that one metering equipment of the feeder line is abnormal, and after determining abnormal equipment, maintaining the abnormal equipment. According to the embodiment of the invention, the abnormal state of the second metering equipment is found through line loss, the rotation from 'due rotation' to 'state rotation' is realized, the replacement of unnecessary objects is reduced, the maintenance workload is reduced, and the unnecessary labor consumption is reduced.
It should be understood that the sequence numbers of the steps in the above embodiments do not mean the execution sequence, and the execution sequence of each process should be determined by the function and the inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
The following are apparatus embodiments of the invention, and for details not described in detail therein, reference may be made to the corresponding method embodiments described above.
Fig. 5 is a functional block diagram of an operation and maintenance device for an electric power metering device according to an embodiment of the present invention, and referring to fig. 5, the operation and maintenance device for an electric power metering device 5 includes: the system comprises a first state acquisition module 501, a line loss acquisition module 502, a second state acquisition module 503, an abnormality determination module 504 and an output module 505.
A first state obtaining module 501, configured to obtain a state of a first metering device, where the first metering device is a bus power metering device;
a line loss obtaining module 502, configured to obtain a current line loss when the state of the first metering device is good, where the line loss is a deviation between a sum of metering data of each feeder line and the metering data of the bus, and the feeder line is a feeder line connected to the bus;
a second state obtaining module 503, configured to determine a state of a second metering device set according to the current line loss, where the second metering device set includes second metering devices of the feeder lines connected to the bus;
an anomaly determination module 504, configured to determine, when the state of the second metering device set is an anomaly, a second metering device that generates the anomaly; and the number of the first and second groups,
and an output module 505, configured to send maintenance information of the second metering device that generates the abnormality to a maintenance staff.
Fig. 6 is a functional block diagram of a terminal according to an embodiment of the present invention. As shown in fig. 6, the terminal 6 of this embodiment includes: a processor 600, a memory 601 and a computer program 602 stored in said memory 601 and executable on said processor 600. The processor 600 executes the computer program 602 to implement the above-mentioned operation and maintenance methods and steps of the embodiments of the power metering device, such as steps 101 to 105 shown in fig. 1.
Illustratively, the computer program 602 may be partitioned into one or more modules/units that are stored in the memory 601 and executed by the processor 600 to implement the present invention.
The terminal 6 may be a desktop computer, a notebook, a palm computer, a cloud server, or other computing devices. The terminal 6 may include, but is not limited to, a processor 600, a memory 601. It will be appreciated by those skilled in the art that fig. 6 is only an example of a terminal 6 and does not constitute a limitation of the terminal 6, and that it may comprise more or less components than those shown, or some components may be combined, or different components, for example the terminal may further comprise input output devices, network access devices, buses, etc.
The Processor 600 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 601 may be an internal storage unit of the terminal 6, such as a hard disk or a memory of the terminal 6. The memory 601 may also be an external storage device of the terminal 6, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are equipped on the terminal 6. Further, the memory 601 may also include both an internal storage unit and an external storage device of the terminal 6. The memory 601 is used for storing the computer programs and other programs and data required by the terminal. The memory 601 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit, and the integrated unit may be implemented in a form of hardware, or may be implemented in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the above embodiments, the description of each embodiment is focused on, and for parts that are not described or illustrated in detail in a certain embodiment, reference may be made to the description of other embodiments.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus/terminal and method may be implemented in other manners. For example, the above-described apparatus/terminal embodiments are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions in actual implementation, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow in the method according to the above embodiments may be implemented by a computer program, which may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the steps of the embodiments of the method and the apparatus for operating and maintaining the power metering device may be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain other components which may be suitably increased or decreased as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media which may not include electrical carrier signals and telecommunications signals in accordance with legislation and patent practice.
The above embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may be modified or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.
Claims (10)
1. An operation and maintenance method for electric power metering equipment is characterized by comprising the following steps:
acquiring the state of first metering equipment, wherein the first metering equipment is power metering equipment of a bus;
if the first metering equipment is in a good state, acquiring the current line loss, wherein the line loss is the deviation between the sum of the metering data of each feeder line and the metering data of the bus, and the feeder line is a feeder line connected with the bus;
determining a state of a second metering device set according to the current line loss, wherein the second metering device set comprises second metering devices of the feeder lines connected with the bus;
if the state of the second metering equipment set is abnormal, determining second metering equipment which generates the abnormality;
and sending the maintenance information of the second metering equipment with the abnormality to the terminal equipment of the maintenance personnel.
2. The operation and maintenance method of the electric power metering device according to claim 1, wherein the obtaining of the state of the first metering device comprises:
acquiring operating environment data of the first metering equipment, wherein the operating environment data is used for representing the operating environment of the first metering equipment;
inputting the operating environment data into the neural network model to obtain the expected life of the first metering equipment, wherein the neural network is an LSTM neural network which is subjected to predictive training;
if the expected life is greater than a first threshold, determining that the status of the first metering device is good.
3. The method for operation and maintenance of power metering equipment according to claim 1, wherein the determining the state of the second metering equipment set according to the current line loss comprises:
acquiring a line loss curve and current metering data of the bus, wherein the line loss curve is a curve representing the relation between the bus metering data and the line loss;
determining target line loss according to the current metering data and the line loss curve;
and if the deviation between the current line loss and the target line loss is larger than a second threshold value, determining that the state of the second metering equipment set is abnormal.
4. The operation and maintenance method of the power metering device according to claim 3, wherein the obtaining of the line loss curve comprises:
acquiring historical metering data and historical line loss of the bus in multiple periods;
and fitting the historical metering data of the multiple periods and the historical line loss to generate the line loss curve.
5. The operation and maintenance method of the power metering device according to claim 1, wherein the determining of the second metering device generating the abnormality comprises:
for each second metrology device, performing the steps of:
acquiring a current metering data set and a plurality of historical metering data sets, wherein the metering data sets are sets of metering data of the second metering device in a preset metering time;
selecting one historical metering data set which is closest to the current metering data set from the plurality of historical metering data sets as a comparison metering data set;
calculating the deviation between a first average value and a second average value, wherein the first average value is the average value of all metering data in the current metering data set, and the second average value is the average value of all metering data in the comparison metering data set;
and if the deviation of the first average value and the second average value is larger than a third threshold value, determining that the second metering device generates an abnormality.
6. The operation and maintenance method of the power metering device of claim 5, wherein the selecting one of the historical metering data sets that is closest to the current metering data set as a comparison metering data set comprises:
respectively carrying out normalization processing on the current measurement data set and each historical measurement data set;
generating a probability curve according to the current measurement data set to serve as a first curve;
generating a probability curve according to the historical measurement data set to serve as a second curve;
selecting the second curve most similar to the first curve as a closest curve;
and taking the historical measurement data set corresponding to the closest curve as the comparison measurement data set.
7. The operation and maintenance method of the power metering device according to any one of claims 1 to 6, wherein the maintenance information includes an identifier, and the sending the maintenance information of the second metering device generating the abnormality to the maintenance personnel includes:
obtaining an identification of the second metering device that generated the anomaly, the identification including at least one of: the name, model and installation location of the second metering device;
and sending the identification to the terminal equipment of the maintainer.
8. An electric power metering equipment operation and maintenance device, characterized by comprising:
the system comprises a first state acquisition module, a second state acquisition module and a control module, wherein the first state acquisition module is used for acquiring the state of first metering equipment, and the first metering equipment is electric power metering equipment of a bus;
the line loss acquisition module is used for acquiring the current line loss when the first metering equipment is in a good state, wherein the line loss is the deviation between the sum of the metering data of each feeder line and the metering data of the bus, and the feeder line is a feeder line connected with the bus;
a second state obtaining module, configured to determine a state of a second metering device set according to the current line loss, where the second metering device set includes second metering devices of feeder lines connected to the bus;
the abnormality determining module is used for determining second metering equipment which generates abnormality when the state of the second metering equipment set is abnormal; and the number of the first and second groups,
and the output module is used for sending the maintenance information of the second metering equipment with the abnormity to a terminal of a maintenance worker.
9. A terminal comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any of the preceding claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.
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| CN113391256A (en) * | 2021-05-28 | 2021-09-14 | 国网河北省电力有限公司营销服务中心 | Electric energy meter metering fault analysis method and system of field operation terminal |
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| CN113391256A (en) * | 2021-05-28 | 2021-09-14 | 国网河北省电力有限公司营销服务中心 | Electric energy meter metering fault analysis method and system of field operation terminal |
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