CN117405971A - Power acquisition digitization method based on flow automation - Google Patents
Power acquisition digitization method based on flow automation Download PDFInfo
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Abstract
The invention provides a method and a system for digitizing electric power collection based on flow automation, which belong to the technical field of data processing and specifically comprise the following steps: determining the temperature abnormality probability based on the frequency and the accumulated duration of the operation temperature of the electric power metering equipment which are not in the preset interval; determining the harmonic aberration probability of the electric power metering equipment based on the frequency and the accumulated duration of the abnormal harmonic content of the running current of the electric power metering equipment; determining transmission abnormality probability and metering abnormality probability of the electric power metering equipment according to the model and the historical operation data, and determining comprehensive abnormality probability and check priority of the electric power metering equipment by combining the harmonic abnormality probability and the temperature abnormality probability; and the metering data of the electric power metering equipment is verified through the verification priority, and the metering charging result is output by utilizing the flow automatic processing system based on the metering data, so that the reliable collection of the metering data of the electric power metering equipment is realized.
Description
Technical Field
The invention belongs to the technical field of data processing, and particularly relates to a method for power acquisition digitization based on flow automation.
Background
Along with the digitization and the intellectualization of the electric power metering equipment, the electricity consumption data acquisition of the electric power user is also changed into automatic meter reading from the traditional manual meter reading mode, and meanwhile, the self-service settlement can be realized by using a flow self-service robot or a self-service metering charging system according to meter reading results, but the problem metering data identification and processing in the settlement processing process are also realized, so that the technical problem to be solved urgently.
In order to realize the recognition of the problem metering data, the recognition of the abnormal data through a preset rule is given in the prior art, specifically, in the invention patent CN201611083723.8, "electric power charging distributed parallel abnormality detection method", the electric power charging data is screened by using the technical characteristics of the electric power network service data, especially the sparsity of the electric power charging data, to a certain extent, and a parallel coordinate descent calculation method is adopted, so that the abnormal problem is found more accurately, but the following technical problems exist in the prior art means:
the problem metering data are often related to the electric power metering equipment, and in particular, the data transmission and metering accuracy of the metering data of the electric power metering equipment with different models are different to a certain extent, so that if the differentiated electric power metering data cannot be verified according to the model of the electric power metering equipment of a specific user, the reliability of the metering data of the electric power metering equipment cannot be ensured.
The metering accuracy of metering data and the reliability of data transmission of the electric power metering equipment are influenced by the operation environment of the electric power metering equipment, for example, the metering chip generates temperature drift or is halted to cause inaccurate metering result and even cannot meter due to the fact that the operation temperature is too high, and therefore if differentiated electric power metering data verification can not be carried out by combining the operation environment data of the electric power equipment, the reliability of the metering data of the electric power metering equipment cannot be guaranteed.
Aiming at the technical problems, the invention provides a method for digitizing power collection based on flow automation.
Disclosure of Invention
In order to achieve the purpose of the invention, the invention adopts the following technical scheme:
according to one aspect of the invention, a method for flow automation-based power harvesting digitization is provided.
The method for digitizing the power collection based on the process automation is characterized by comprising the following steps:
s1, determining the operation temperature of the electric power metering equipment based on historical operation data, determining the temperature abnormality probability of the electric power metering equipment by combining the frequency and the accumulated time length of the operation temperature which are not in a preset interval, and setting the verification priority of the electric power metering equipment with abnormal temperature abnormality probability as a first level;
S2, determining harmonic content of the running current of the electric power metering equipment based on historical running data, determining harmonic abnormality probability of the electric power metering equipment by combining frequency and accumulated duration of abnormality of the harmonic content, and setting verification priority of the electric power metering equipment with abnormality of the harmonic abnormality probability as a second level;
s3, determining transmission abnormality probability and metering abnormality probability of the electric power metering equipment according to the model and the historical operation data, and determining comprehensive abnormality probability and check priority of the electric power metering equipment by combining harmonic abnormality probability and temperature abnormality probability of the electric power metering equipment;
and S4, checking the metering data of the electric power metering equipment according to the checking priority, and outputting metering charging results by using a flow automatic processing system based on the metering data when the metering data is not abnormal.
The invention has the beneficial effects that:
1. by determining the temperature abnormality probability of the electric power metering equipment, the judgment of the metering reliability of the electric power metering equipment from the actual condition of the operation temperature of the electric power metering equipment is realized, and not only the difference of single operation temperature is considered, but also the difference of the abnormal frequency and the abnormal time length of the operation temperature is considered.
2. By determining the harmonic aberration probability of the electric power metering equipment, the problem of low metering accuracy caused by harmonic aberration of metered current data is fully considered, the harmonic content of single electric power metering equipment is considered, and meanwhile, the data such as the occurrence frequency of the harmonic content of the electric power metering equipment is comprehensively evaluated, so that the screening of the electric power metering equipment with low electric energy quality is realized.
3. By determining the comprehensive abnormality probability and the verification priority of the electric power metering equipment, the influence of own abnormality factors of single electric power metering equipment is considered, meanwhile, the difference of abnormality factors of different electric power metering equipment models is comprehensively considered, and a foundation is laid for further performing differentiated verification of metering data.
Further technical solutions include, but are not limited to, operating temperature, operating current, number of metering data anomalies, and number of data transmission anomalies.
The further technical scheme is that whether the operation temperature of the electric power metering equipment is reliable or not is determined through the accumulated metering time length of the electric power metering equipment and the accumulated time length that the operation temperature is not in a preset interval, and the method specifically comprises the following steps:
Obtaining a temperature abnormal time length proportion according to the ratio of the accumulated time length of the electric power metering equipment, in which the operating temperature is not in the preset interval, to the accumulated metering time length of the electric power metering equipment, judging whether the temperature abnormal time length proportion is larger than a preset time length proportion threshold value, if so, determining that the operating temperature of the electric power metering equipment is unreliable, and if not, determining that the operating temperature of the electric power metering equipment is reliable.
The further technical scheme is that when the harmonic aberration probability of the electric power metering equipment is larger than a second probability threshold value, the verification priority of the electric power metering equipment is determined to be a second level.
The further technical scheme is that the method for determining the check priority comprises the following steps:
when the comprehensive abnormality probability of the electric power metering equipment is larger than a second probability threshold value, setting the verification priority of the electric power metering equipment to be a first level;
when the comprehensive abnormality probability of the electric power metering equipment is larger than a first probability threshold and is not larger than a second probability threshold, judging whether the harmonic abnormality probability and the temperature abnormality probability of the electric power metering equipment are both larger than the first probability threshold, if so, setting the verification priority of the electric power metering equipment to be a first level, and if not, setting the verification priority of the electric power metering equipment to be a second level;
When the comprehensive abnormality probability of the electric power metering equipment is smaller than a first probability threshold, judging whether the harmonic abnormality probability and the temperature abnormality probability of the electric power metering equipment are both larger than the first probability threshold, if so, setting the verification priority of the electric power metering equipment to be a second level, and if not, setting the verification priority of the electric power metering equipment to be a third level.
The further technical scheme is that the first level is larger than the second level, the second level is larger than the third level, and the verification period of the metering data of the electric power metering equipment is determined according to the verification priority of the electric power metering equipment.
In another aspect, the present invention provides a computer system comprising: a communicatively coupled memory and processor, and a computer program stored on the memory and capable of running on the processor, characterized by: the processor executes the method for digitizing the power collection based on process automation when running the computer program.
Additional features and advantages will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and drawings.
In order to make the above objects, features and advantages of the present invention more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings.
FIG. 1 is a flow chart of a method of power harvesting digitization based on process automation;
FIG. 2 is a flow chart of a method of determining a temperature aberration probability of an electric power metering device;
FIG. 3 is a block diagram of a computer system.
Detailed Description
In order to make the technical solutions in the present specification better understood by those skilled in the art, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is obvious that the described embodiments are only some embodiments of the present specification, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, shall fall within the scope of the present disclosure.
The applicant finds that when the measurement data of the electric power measurement equipment are collected and automatically calculated, the accuracy and the reliability of data transmission of the electric power measurement equipment of different models are different to a certain extent, meanwhile, the harmonic content of the running current and the running temperature of the electric power measurement equipment are also influenced by the influence of the working environment factors to a certain extent, so that the accuracy of the measurement data of the electric power measurement equipment cannot be ensured if the verification of the differentiated measurement data is carried out without considering the factors.
For ease of understanding, the following description of the scheme will be made by way of example 1 and example 2.
Example 1
To solve the above problems, according to one aspect of the present invention, as shown in fig. 1, there is provided a method for digitizing power collection based on process automation, which is characterized by specifically comprising:
s1, determining the operation temperature of the electric power metering equipment based on historical operation data, determining the temperature abnormality probability of the electric power metering equipment by combining the frequency and the accumulated time length of the operation temperature which are not in a preset interval, and setting the verification priority of the electric power metering equipment with abnormal temperature abnormality probability as a first level;
further, the historical operating data includes, but is not limited to, operating temperature, operating current, number of meter data anomalies, and number of data transmission anomalies.
In one possible embodiment, the method for determining the temperature aberration probability of the electric power metering device is as follows:
s21, determining the accumulated metering duration of the electric power metering equipment and the accumulated duration of the electric power metering equipment with the operation temperature not in a preset interval according to the historical operation data of the electric power metering equipment, determining whether the operation temperature of the electric power metering equipment is reliable or not according to the accumulated metering duration of the electric power metering equipment and the accumulated duration of the electric power metering equipment with the operation temperature not in the preset interval, if so, entering the next step, and if not, entering the step S23;
S22, determining the frequency that the operation temperature of the electric power metering equipment is not in a preset interval based on the average value of the times that the operation temperature of the electric power metering equipment is not in the preset interval in unit time, determining whether the operation temperature of the electric power metering equipment is reliable or not according to the average value of the accumulated time length that the operation temperature of the electric power metering equipment is not in the preset interval in unit time, if yes, determining the temperature abnormality probability of the electric power metering equipment according to the accumulated metering time length of the electric power metering equipment and the accumulated time length that the operation temperature is not in the preset interval, and if no, entering step S23;
s23, determining the probability of the recent temperature abnormality of the electric power metering equipment through the average value and the maximum value of the accumulated time length, in which the operation temperature of the electric power metering equipment is not in the preset interval, of the preset time, and judging whether the probability of the recent temperature abnormality of the electric power metering equipment is smaller than a first probability threshold, if so, determining the probability of the temperature abnormality of the electric power metering equipment through the probability of the recent temperature abnormality of the electric power metering equipment, and if not, entering the next step;
S24, determining the long-term temperature abnormality probability of the electric power metering equipment through the average value and the maximum value of the accumulated time length, in which the operation temperature of the electric power metering equipment is not in the preset interval, the frequency, in which the operation temperature is not in the preset interval, of the accumulated time length, in which the operation temperature of the electric power metering equipment is not in the preset interval, in unit time;
s25, acquiring accumulated metering duration of the electric power metering equipment, and determining the temperature abnormality probability of the electric power metering equipment by combining the long-term abnormality probability and the short-term temperature abnormality probability of the electric power metering equipment.
Further, determining whether the operation temperature of the electric power metering device is reliable according to the accumulated metering duration of the electric power metering device and the accumulated duration that the operation temperature is not in the preset interval specifically includes:
obtaining a temperature abnormal time length proportion according to the ratio of the accumulated time length of the electric power metering equipment, in which the operating temperature is not in the preset interval, to the accumulated metering time length of the electric power metering equipment, judging whether the temperature abnormal time length proportion is larger than a preset time length proportion threshold value, if so, determining that the operating temperature of the electric power metering equipment is unreliable, and if not, determining that the operating temperature of the electric power metering equipment is reliable.
In a further possible embodiment, the method for determining the probability of temperature aberration of the power metering device is:
determining the accumulated metering duration of the electric power metering equipment and the accumulated duration of the electric power metering equipment with the operation temperature not in a preset interval according to the historical operation data of the electric power metering equipment, and determining the comprehensive temperature reliability of the electric power metering equipment by combining the accumulated duration of the electric power metering equipment with the operation temperature not in the preset interval in the preset time;
determining that the operating temperature of the electric power metering device is unreliable based on the integrated reliable amount of temperature of the electric power metering device:
determining a frequency that the operation temperature of the electric power metering equipment is not in a preset interval based on the average value of times that the operation temperature of the electric power metering equipment is not in the preset interval in unit time;
determining the probability of the recent temperature aberration of the electric power metering equipment according to the average value and the maximum value of the accumulated time length of the electric power metering equipment in which the operation temperature in the preset time is not in the preset interval, the frequency of the electric power metering equipment in which the operation temperature in the preset time is not in the preset interval and the accumulated time length of the electric power metering equipment in the unit time;
And determining the long-term temperature abnormality probability of the electric power metering equipment according to the accumulated duration of the electric power metering equipment, the frequency of which the operation temperature is not in the preset interval, the average value and the maximum value of the accumulated duration of the electric power metering equipment which is not in the preset interval, and the accumulated metering duration of the electric power metering equipment, and determining the temperature abnormality probability of the electric power metering equipment according to the long-term abnormality probability and the short-term temperature abnormality probability of the electric power metering equipment.
Determining that the operating temperature of the electric power metering device is reliable based on the integrated reliability amount of the temperature of the electric power metering device:
determining the long period abnormality probability of the electric power metering equipment through the accumulated metering duration of the electric power metering equipment and the accumulated duration of the operation temperature which is not in a preset interval; determining the short period abnormality probability of the electric power metering equipment through the accumulated time length of the electric power metering equipment when the operation temperature is not in a preset interval;
and determining the temperature abnormality probability of the electric power metering equipment according to the accumulated metering duration of the electric power metering equipment, the preset time, the long period abnormality probability and the short period abnormality probability.
In another possible embodiment, as shown in fig. 2, the method for determining the probability of temperature aberration of the power metering device is as follows:
determining the accumulated metering duration of the electric power metering equipment and the accumulated duration of the electric power metering equipment with the operation temperature not in a preset interval according to the historical operation data of the electric power metering equipment, determining whether the operation temperature of the electric power metering equipment is reliable or not according to the accumulated metering duration of the electric power metering equipment and the accumulated duration of the operation temperature not in the preset interval, if so, determining the temperature abnormality probability of the electric power metering equipment according to the accumulated metering duration of the electric power metering equipment and the accumulated duration of the operation temperature not in the preset interval, and if not, entering the next step;
determining a frequency that the operation temperature of the electric power metering equipment is not in a preset interval based on the average value of times that the operation temperature of the electric power metering equipment is not in the preset interval in unit time;
determining the probability of the recent temperature aberration of the electric power metering equipment according to the average value and the maximum value of the accumulated time length of the electric power metering equipment in which the operation temperature in the preset time is not in the preset interval, the frequency of the electric power metering equipment in which the operation temperature in the preset time is not in the preset interval and the accumulated time length of the electric power metering equipment in the unit time;
Determining the long-term temperature abnormality probability of the electric power metering equipment according to the accumulated duration of the electric power metering equipment, the frequency of which the operation temperature is not in a preset interval, the average value of the accumulated duration of which the operation temperature is not in the preset interval in unit time and the maximum value, judging whether the recent temperature abnormality probability and the long-term temperature abnormality probability of the electric power metering equipment are smaller than a first probability threshold, if so, determining the temperature abnormality probability of the electric power metering equipment according to the recent temperature abnormality probability of the electric power metering equipment, and if not, entering the next step;
and acquiring the accumulated metering duration of the electric power metering equipment, and determining the temperature abnormality probability of the electric power metering equipment by combining the long-term abnormality probability and the short-term temperature abnormality probability of the electric power metering equipment.
S2, determining harmonic content of the running current of the electric power metering equipment based on historical running data, determining harmonic abnormality probability of the electric power metering equipment by combining frequency and accumulated duration of abnormality of the harmonic content, and setting verification priority of the electric power metering equipment with abnormality of the harmonic abnormality probability as a second level;
In one possible embodiment, the method for determining the harmonic aberration probability is as follows:
s31, determining a period of abnormality of the harmonic content of the electric power metering equipment based on the harmonic content of the running current of the electric power metering equipment, determining whether the metering electric energy quality of the electric power metering equipment meets the requirement or not according to the harmonic content and the duration ratio of the period of abnormality of the harmonic content of the electric power metering equipment, if so, entering the next step, and if not, entering the step S33;
s32, extracting distortion characteristic quantities based on current waveforms of the time periods with abnormal harmonic content of the electric power metering equipment to obtain the deviation degree, kurtosis and waveform factors of the current waveforms, determining the waveform variation quantity of the current waveforms of the time periods with abnormal harmonic content of the electric power metering equipment according to the deviation degree, kurtosis, waveform factors and harmonic content of the current waveforms, determining whether the metered electric energy quality of the electric power metering equipment meets the requirements or not according to the duration ratio of the time periods with abnormal harmonic content, which does not meet the requirements, of the waveform variation quantity, if yes, determining the harmonic aberration probability of the electric power metering equipment according to the duration ratio of the time periods with abnormal harmonic content of the electric power metering equipment and the duration ratio of the time periods with abnormal harmonic content, which does not meet the requirements, if no, entering the next step;
S33, based on the current waveform of the electric power metering equipment in the period with abnormal harmonic content in the preset time, extracting the time domain feature and the frequency domain feature of the current waveform by adopting an image feature extraction model based on a CNN algorithm, and carrying out attention mechanism transformation on the time domain feature, the frequency domain feature and the waveform variance of the current waveform by utilizing an abnormal waveform evaluation model containing an attention mechanism in combination with the waveform variance of the current waveform to obtain the corrected waveform variance of the current metering equipment in the period with abnormal harmonic content in the preset time;
s34, determining harmonic aberration probability of the electric power metering equipment in preset time through the harmonic content of the electric power metering equipment in the time period with abnormal harmonic content and the corrected waveform variation of the time period with abnormal harmonic content, wherein the time period is a ratio of the corrected waveform variation and the waveform variation does not meet requirements;
s35, determining harmonic aberration probability of a long period of the electric power metering equipment according to the harmonic content of the period of abnormal harmonic content of the electric power metering equipment, the time length ratio and the waveform variation of the period of abnormal harmonic content, wherein the time length ratio and the waveform variation do not meet requirements, and determining the harmonic aberration probability of the electric power metering equipment according to the harmonic aberration probability of the electric power metering equipment in preset time, the preset time and the accumulated metering duration of the electric power metering equipment.
In another possible embodiment, the method for determining the harmonic aberration probability is as follows:
determining a period of abnormality of the harmonic content of the electric power metering equipment based on the harmonic content of the running current of the electric power metering equipment, determining whether the metering electric energy quality of the electric power metering equipment meets the requirement according to the harmonic content and the duration ratio of the period of abnormality of the harmonic content of the electric power metering equipment, if so, determining the harmonic abnormality probability of the electric power metering equipment according to the duration ratio of the period of abnormality of the harmonic content of the electric power metering equipment, and if not, entering the next step;
extracting distortion characteristic quantities based on the current waveforms of the time periods with abnormal harmonic content of the electric power metering equipment to obtain the deviation degree, kurtosis and waveform factors of the current waveforms, and determining the waveform variation quantities of the current waveforms of the time periods with abnormal harmonic content of the electric power metering equipment according to the deviation degree, kurtosis, waveform factors and harmonic content of the current waveforms;
based on the current waveform of the electric power metering equipment in the period with abnormal harmonic content in the preset time, extracting the time domain characteristic and the frequency domain characteristic of the current waveform by adopting an image characteristic extraction model based on a CNN algorithm, and carrying out attention mechanism transformation on the time domain characteristic, the frequency domain characteristic and the waveform variation of the current waveform by adopting an abnormal waveform evaluation model containing an attention mechanism in combination with the waveform variation of the current waveform to obtain the corrected waveform variation of the period with abnormal harmonic content in the preset time;
Determining harmonic aberration probability of the electric power metering equipment in preset time according to the harmonic content of the electric power metering equipment in the abnormal time period, the time length ratio and the corrected waveform variation of the abnormal time period of the harmonic content, wherein the time length ratio is not satisfied, determining whether the metering electric energy quality of the electric power metering equipment satisfies the requirement or not according to the harmonic aberration probability of the electric power metering equipment in the preset time, if yes, determining the harmonic aberration probability of the electric power metering equipment according to the time length ratio of the abnormal time period of the electric power metering equipment in the preset time and the time length ratio of the corrected waveform variation not satisfied; the method comprises the steps of carrying out a first treatment on the surface of the
And determining the harmonic aberration probability of the electric power metering equipment according to the harmonic aberration probability of the electric power metering equipment in a preset time, the preset time and the accumulated metering duration of the electric power metering equipment.
Further, when the harmonic aberration probability of the electric power metering equipment is larger than a second probability threshold value, determining that the verification priority of the electric power metering equipment is a second level.
S3, determining transmission abnormality probability and metering abnormality probability of the electric power metering equipment according to the model and the historical operation data, and determining comprehensive abnormality probability and check priority of the electric power metering equipment by combining harmonic abnormality probability and temperature abnormality probability of the electric power metering equipment;
specifically, the method for determining the transmission anomaly probability includes:
determining the number of the power metering devices with abnormal transmission of metering data in the power metering devices of the model according to the model of the power metering devices, and determining the probability of abnormal transmission of the power metering devices of the model according to the ratio of the number of the power metering devices with abnormal transmission of the metering data in the power metering devices of the model;
determining the number of times of metering data transmission failure of the electric power metering equipment according to the historical operation data of the electric power metering equipment, and determining the basic transmission abnormality probability of the electric power metering equipment according to the number of times of metering data transmission failure of the electric power metering equipment and the number of times of metering data transmission failure in preset time;
And determining the transmission abnormality probability of the electric power metering equipment according to the basic transmission abnormality probability of the electric power metering equipment and the transmission abnormality probability of the electric power metering equipment of the model.
It can be appreciated that the method for determining the comprehensive abnormality probability comprises the following steps:
determining transmission abnormality probability and metering abnormality probability of the electric power metering equipment according to model and historical operation data, and determining comprehensive abnormality probability and check priority of the electric power metering equipment by combining harmonic abnormality probability and temperature abnormality probability of the electric power metering equipment
When either the transmission abnormality probability or the metering abnormality probability of the electric power metering device is greater than a second probability threshold value:
the transmission abnormality probability of the electric power metering equipment is set as the basic abnormality probability of the electric power metering equipment;
determining the supplementary probability of the basic abnormality probability of the electric power metering equipment according to the harmonic abnormality probability and the temperature abnormality probability of the electric power metering equipment, and determining the comprehensive abnormality probability of the electric power metering equipment according to the basic abnormality probability;
when the transmission abnormality probability or the metering abnormality probability of the electric power metering equipment is not larger than a second probability threshold value:
Determining corrected metering abnormality probability of the electric power metering equipment according to harmonic abnormality probability, temperature abnormality probability and metering abnormality probability of the electric power metering equipment;
determining corrected transmission abnormality probability of the electric power metering equipment according to the temperature abnormality probability of the electric power metering equipment and the transmission abnormality probability;
and determining the comprehensive abnormal probability of the electric power metering equipment through the corrected transmission abnormal probability and the corrected metering abnormal probability of the electric power metering equipment.
Further, the method for determining the check priority comprises the following steps:
when the comprehensive abnormality probability of the electric power metering equipment is larger than a second probability threshold value, setting the verification priority of the electric power metering equipment to be a first level;
when the comprehensive abnormality probability of the electric power metering equipment is larger than a first probability threshold and is not larger than a second probability threshold, judging whether the harmonic abnormality probability and the temperature abnormality probability of the electric power metering equipment are both larger than the first probability threshold, if so, setting the verification priority of the electric power metering equipment to be a first level, and if not, setting the verification priority of the electric power metering equipment to be a second level;
When the comprehensive abnormality probability of the electric power metering equipment is smaller than a first probability threshold, judging whether the harmonic abnormality probability and the temperature abnormality probability of the electric power metering equipment are both larger than the first probability threshold, if so, setting the verification priority of the electric power metering equipment to be a second level, and if not, setting the verification priority of the electric power metering equipment to be a third level.
Further, the first level is greater than the second level, the second level is greater than the third level, and a verification period of the metering data of the electric power metering device is determined according to the verification priority of the electric power metering device.
And S4, checking the metering data of the electric power metering equipment according to the checking priority, and outputting metering charging results by using a flow automatic processing system based on the metering data when the metering data is not abnormal.
The invention achieves the following technical effects:
1. by determining the temperature abnormality probability of the electric power metering equipment, the judgment of the metering reliability of the electric power metering equipment from the actual condition of the operation temperature of the electric power metering equipment is realized, and not only the difference of single operation temperature is considered, but also the difference of the abnormal frequency and the abnormal time length of the operation temperature is considered.
2. By determining the harmonic aberration probability of the electric power metering equipment, the problem of low metering accuracy caused by harmonic aberration of metered current data is fully considered, the harmonic content of single electric power metering equipment is considered, and meanwhile, the data such as the occurrence frequency of the harmonic content of the electric power metering equipment is comprehensively evaluated, so that the screening of the electric power metering equipment with low electric energy quality is realized.
3. By determining the comprehensive abnormality probability and the verification priority of the electric power metering equipment, the influence of own abnormality factors of single electric power metering equipment is considered, meanwhile, the difference of abnormality factors of different electric power metering equipment models is comprehensively considered, and a foundation is laid for further performing differentiated verification of metering data.
Example 2
In another aspect, as shown in FIG. 3, the present invention provides a computer system comprising: a communicatively coupled memory and processor, and a computer program stored on the memory and capable of running on the processor, characterized by: the processor executes the method for digitizing the power collection based on process automation when running the computer program.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for apparatus, devices, non-volatile computer storage medium embodiments, the description is relatively simple, as it is substantially similar to method embodiments, with reference to the section of the method embodiments being relevant.
The foregoing describes specific embodiments of the present disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
The foregoing is merely one or more embodiments of the present description and is not intended to limit the present description. Various modifications and alterations to one or more embodiments of this description will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, or the like, which is within the spirit and principles of one or more embodiments of the present description, is intended to be included within the scope of the claims of the present description.
Claims (10)
1. The method for digitizing the power collection based on the process automation is characterized by comprising the following steps:
determining the operation temperature of the electric power metering equipment based on historical operation data, determining the temperature abnormality probability of the electric power metering equipment by combining the frequency and the accumulated time length of which the operation temperature is not in a preset interval, and setting the verification priority of the electric power metering equipment with abnormal temperature abnormality probability as a first level;
determining harmonic content of the running current of the electric power metering equipment based on historical running data, determining harmonic abnormality probability of the electric power metering equipment by combining frequency and accumulated duration of abnormality of the harmonic content, and setting verification priority of the electric power metering equipment with abnormality of the harmonic abnormality probability as a second level;
determining transmission abnormality probability and metering abnormality probability of the electric power metering equipment according to the model and the historical operation data, and determining comprehensive abnormality probability and check priority of the electric power metering equipment by combining harmonic abnormality probability and temperature abnormality probability of the electric power metering equipment;
and checking the metering data of the electric power metering equipment according to the checking priority, and outputting metering charging results by using a flow automatic processing system based on the metering data when the metering data is not abnormal.
2. A process automation based power harvesting digitization method as claimed in claim 1, wherein the historical operating data includes, but is not limited to, operating temperature, operating current, metering data anomaly count, and data transmission anomaly count.
3. A process automation based power harvesting digitization method as claimed in claim 1, wherein the method of determining the probability of temperature aberration of the power metering device is:
s21, determining the accumulated metering duration of the electric power metering equipment and the accumulated duration of the electric power metering equipment with the operation temperature not in a preset interval according to the historical operation data of the electric power metering equipment, determining whether the operation temperature of the electric power metering equipment is reliable or not according to the accumulated metering duration of the electric power metering equipment and the accumulated duration of the electric power metering equipment with the operation temperature not in the preset interval, if so, entering the next step, and if not, entering the step S23;
s22, determining the frequency that the operation temperature of the electric power metering equipment is not in a preset interval based on the average value of the times that the operation temperature of the electric power metering equipment is not in the preset interval in unit time, determining whether the operation temperature of the electric power metering equipment is reliable or not according to the average value of the accumulated time length that the operation temperature of the electric power metering equipment is not in the preset interval in unit time, if yes, determining the temperature abnormality probability of the electric power metering equipment according to the accumulated metering time length of the electric power metering equipment and the accumulated time length that the operation temperature is not in the preset interval, and if no, entering step S23;
S23, determining the probability of the recent temperature abnormality of the electric power metering equipment through the average value and the maximum value of the accumulated time length, in which the operation temperature of the electric power metering equipment is not in the preset interval, of the preset time, and judging whether the probability of the recent temperature abnormality of the electric power metering equipment is smaller than a first probability threshold, if so, determining the probability of the temperature abnormality of the electric power metering equipment through the probability of the recent temperature abnormality of the electric power metering equipment, and if not, entering the next step;
s24, determining the long-term temperature abnormality probability of the electric power metering equipment through the average value and the maximum value of the accumulated time length, in which the operation temperature of the electric power metering equipment is not in the preset interval, the frequency, in which the operation temperature is not in the preset interval, of the accumulated time length, in which the operation temperature of the electric power metering equipment is not in the preset interval, in unit time;
s25, acquiring accumulated metering duration of the electric power metering equipment, and determining the temperature abnormality probability of the electric power metering equipment by combining the long-term abnormality probability and the short-term temperature abnormality probability of the electric power metering equipment.
4. The process automation-based power acquisition digitization method of claim 3, wherein determining whether the operating temperature of the power metering device is reliable by the accumulated metering duration of the power metering device and the accumulated duration that the operating temperature is not within a preset interval specifically comprises:
obtaining a temperature abnormal time length proportion according to the ratio of the accumulated time length of the electric power metering equipment, in which the operating temperature is not in the preset interval, to the accumulated metering time length of the electric power metering equipment, judging whether the temperature abnormal time length proportion is larger than a preset time length proportion threshold value, if so, determining that the operating temperature of the electric power metering equipment is unreliable, and if not, determining that the operating temperature of the electric power metering equipment is reliable.
5. The method for digitizing power collection based on process automation of claim 1, wherein the method for determining the harmonic aberration probability is as follows:
s31, determining a period of abnormality of the harmonic content of the electric power metering equipment based on the harmonic content of the running current of the electric power metering equipment, determining whether the metering electric energy quality of the electric power metering equipment meets the requirement or not according to the harmonic content and the duration ratio of the period of abnormality of the harmonic content of the electric power metering equipment, if so, entering the next step, and if not, entering the step S33;
S32, extracting distortion characteristic quantities based on current waveforms of the time periods with abnormal harmonic content of the electric power metering equipment to obtain the deviation degree, kurtosis and waveform factors of the current waveforms, determining the waveform variation quantity of the current waveforms of the time periods with abnormal harmonic content of the electric power metering equipment according to the deviation degree, kurtosis, waveform factors and harmonic content of the current waveforms, determining whether the metered electric energy quality of the electric power metering equipment meets the requirements or not according to the duration ratio of the time periods with abnormal harmonic content, which does not meet the requirements, of the waveform variation quantity, if yes, determining the harmonic aberration probability of the electric power metering equipment according to the duration ratio of the time periods with abnormal harmonic content of the electric power metering equipment and the duration ratio of the time periods with abnormal harmonic content, which does not meet the requirements, if no, entering the next step;
s33, based on the current waveform of the electric power metering equipment in the period with abnormal harmonic content in the preset time, extracting the time domain feature and the frequency domain feature of the current waveform by adopting an image feature extraction model based on a CNN algorithm, and carrying out attention mechanism transformation on the time domain feature, the frequency domain feature and the waveform variance of the current waveform by utilizing an abnormal waveform evaluation model containing an attention mechanism in combination with the waveform variance of the current waveform to obtain the corrected waveform variance of the current metering equipment in the period with abnormal harmonic content in the preset time;
S34, determining harmonic aberration probability of the electric power metering equipment in preset time through the harmonic content of the electric power metering equipment in the time period with abnormal harmonic content and the corrected waveform variation of the time period with abnormal harmonic content, wherein the time period is a ratio of the corrected waveform variation and the waveform variation does not meet requirements;
s35, determining harmonic aberration probability of a long period of the electric power metering equipment according to the harmonic content of the period of abnormal harmonic content of the electric power metering equipment, the time length ratio and the waveform variation of the period of abnormal harmonic content, wherein the time length ratio and the waveform variation do not meet requirements, and determining the harmonic aberration probability of the electric power metering equipment according to the harmonic aberration probability of the electric power metering equipment in preset time, the preset time and the accumulated metering duration of the electric power metering equipment.
6. A process automation based power harvesting digitization method as defined in claim 1, wherein when the power metering device harmonic aberration probability is greater than a second probability threshold, then determining the power metering device verification priority to be a second level.
7. The method for digitizing power collection based on process automation according to claim 1, wherein the method for determining the probability of transmission anomaly is as follows:
Determining the number of the power metering devices with abnormal transmission of metering data in the power metering devices of the model according to the model of the power metering devices, and determining the probability of abnormal transmission of the power metering devices of the model according to the ratio of the number of the power metering devices with abnormal transmission of the metering data in the power metering devices of the model;
determining the number of times of metering data transmission failure of the electric power metering equipment according to the historical operation data of the electric power metering equipment, and determining the basic transmission abnormality probability of the electric power metering equipment according to the number of times of metering data transmission failure of the electric power metering equipment and the number of times of metering data transmission failure in preset time;
and determining the transmission abnormality probability of the electric power metering equipment according to the basic transmission abnormality probability of the electric power metering equipment and the transmission abnormality probability of the electric power metering equipment of the model.
8. The method for digitizing power collection based on process automation according to claim 1, wherein the method for determining the integrated aberration probability is as follows:
determining transmission abnormality probability and metering abnormality probability of the electric power metering equipment according to model and historical operation data, and determining comprehensive abnormality probability and check priority of the electric power metering equipment by combining harmonic abnormality probability and temperature abnormality probability of the electric power metering equipment
When either the transmission abnormality probability or the metering abnormality probability of the electric power metering device is greater than a second probability threshold value:
the transmission abnormality probability of the electric power metering equipment is set as the basic abnormality probability of the electric power metering equipment;
determining the supplementary probability of the basic abnormality probability of the electric power metering equipment according to the harmonic abnormality probability and the temperature abnormality probability of the electric power metering equipment, and determining the comprehensive abnormality probability of the electric power metering equipment according to the basic abnormality probability;
when the transmission abnormality probability or the metering abnormality probability of the electric power metering equipment is not larger than a second probability threshold value:
determining corrected metering abnormality probability of the electric power metering equipment according to harmonic abnormality probability, temperature abnormality probability and metering abnormality probability of the electric power metering equipment;
determining corrected transmission abnormality probability of the electric power metering equipment according to the temperature abnormality probability of the electric power metering equipment and the transmission abnormality probability;
and determining the comprehensive abnormal probability of the electric power metering equipment through the corrected transmission abnormal probability and the corrected metering abnormal probability of the electric power metering equipment.
9. The method for digitizing power collection based on process automation of claim 1, wherein the method for determining the verification priority is as follows:
when the comprehensive abnormality probability of the electric power metering equipment is larger than a second probability threshold value, setting the verification priority of the electric power metering equipment to be a first level;
when the comprehensive abnormality probability of the electric power metering equipment is larger than a first probability threshold and is not larger than a second probability threshold, judging whether the harmonic abnormality probability and the temperature abnormality probability of the electric power metering equipment are both larger than the first probability threshold, if so, setting the verification priority of the electric power metering equipment to be a first level, and if not, setting the verification priority of the electric power metering equipment to be a second level;
when the comprehensive abnormality probability of the electric power metering equipment is smaller than a first probability threshold, judging whether the harmonic abnormality probability and the temperature abnormality probability of the electric power metering equipment are both larger than the first probability threshold, if so, setting the verification priority of the electric power metering equipment to be a second level, and if not, setting the verification priority of the electric power metering equipment to be a third level.
The further technical scheme is that the first level is larger than the second level, the second level is larger than the third level, and the verification period of the metering data of the electric power metering equipment is determined according to the verification priority of the electric power metering equipment.
10. A computer system, comprising: a communicatively coupled memory and processor, and a computer program stored on the memory and capable of running on the processor, characterized by: the processor, when executing the computer program, performs a method of flow automation based power harvesting digitization as claimed in any one of claims 1-9.
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