CN115115282B - Data analysis method for high-voltage transformer area power system - Google Patents

Data analysis method for high-voltage transformer area power system Download PDF

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CN115115282B
CN115115282B CN202211026874.5A CN202211026874A CN115115282B CN 115115282 B CN115115282 B CN 115115282B CN 202211026874 A CN202211026874 A CN 202211026874A CN 115115282 B CN115115282 B CN 115115282B
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voltage transformer
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preset time
transformer area
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程鹏
汪文豪
范荣琴
严流进
张悦
王子瑜
张海涛
李怀龙
郁照云
赵刚
邵佩佩
陈敏
罗晓梅
苏紫雪
张婷婷
姚祺
刘美
方天翼
张荣宸
李博逊
王馨
蔡晓青
李攀峰
邓道福
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Chaou Power Supply Co of State Grid Anhui Electric Power Co Ltd
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Abstract

The invention relates to the technical field of data analysis of power systems, and particularly discloses a data analysis method for a power system of a high-voltage transformer area.

Description

Data analysis method for high-voltage transformer area power system
Technical Field
The invention relates to the technical field of data analysis of power systems, in particular to a data analysis method for a power system of a high-voltage transformer area.
Background
The transformer area refers to a high-voltage power grid power supply range or power supply area corresponding to one distribution transformer. At present, a power system comprehensively manages a distribution area on a user demand side, and the power operation data of a high-voltage distribution area can directly influence the informatization, automation and intellectualization level of the power system. Therefore, how to systematically analyze the power operation data of the high-voltage transformer area is an important problem worthy of research.
At present high voltage platform district is in the power supply working process, need monitor and the analysis to the line network loss rate in high voltage platform district, but current high voltage platform district line network loss rate monitoring mode is the power consumption that the high voltage platform district corresponds the user demand side of regular statistics basically, the line network loss rate in analysis high voltage platform district, there is the hysteresis quality of monitoring electric power data in this kind of mode, can't realize carrying out real-time supervision and analysis to the line network loss rate in high voltage platform district, thereby there is some illegal users to take the action that improper means stolen the electric quantity, this kind of electricity stealing action has not only harmd the economic benefits of country and electric power enterprise, disturb normal power supply order, and high voltage platform district equipment can be damaged, cause the casualties, brought serious threat for the safe power consumption.
Meanwhile, in the power supply working process of the high-voltage transformer area, the power operation data is basically acquired and analyzed within a preset time period, but in the power operation data analysis process of the existing high-voltage transformer area, only the influence of voltage fluctuation on the power supply quality of the high-voltage transformer area is considered, so that a certain deviation exists in an analysis result, the accuracy and the reliability of the power supply quality analysis result of the high-voltage transformer area are reduced, further, the safety power supply guarantee of the high-voltage transformer area is influenced, meanwhile, the power supply quality requirements of the user demand side in each power consumption time period are not considered in the existing analysis mode, further, whether the corresponding electric equipment of the user demand side can normally operate or not cannot be determined, and potential hazards are caused to the safety power consumption of the user demand side.
Disclosure of Invention
In view of the above, in order to solve the problems in the background art, a data analysis method for a high voltage power system is proposed.
In order to achieve the above object, the present invention provides a data analysis method for a power system of a high voltage transformer area, comprising the following steps: s1, acquiring real-time electricity consumption of a user demand side: and acquiring the real-time power consumption of each high-voltage transformer area on each user demand side in a preset time period, and acquiring the power consumption of each high-voltage transformer area in the preset time period.
S2, analyzing the loss rate of the line network of the high-voltage transformer area: and monitoring meteorological parameter data of each high-voltage transformer area in a preset time period, and analyzing the line network loss rate of each high-voltage transformer area in the preset time period.
S3, evaluating the abnormal index of the high-voltage transformer area circuit: and evaluating the line abnormal index corresponding to each high-voltage transformer area, comparing the line abnormal index with a preset line abnormal index threshold value, and performing corresponding processing according to the comparison result.
S4, monitoring voltage parameters of a user demand side: and monitoring instantaneous voltage and voltage waves of each high-voltage transformer area corresponding to each acquisition time point at each user demand side in a preset time period to form voltage parameters of each high-voltage transformer area corresponding to each acquisition time point at each user demand side in the preset time period.
S5, analyzing voltage parameters of a user demand side: and analyzing the voltage parameters of each high-voltage transformer area corresponding to each acquisition time point at each user demand side in a preset time period to obtain a voltage fluctuation influence weight index and a voltage wave coincidence influence weight index of each high-voltage transformer area in the preset time period.
S6, analyzing and processing a power supply quality evaluation coefficient: and analyzing the power supply quality evaluation coefficient of each high-voltage transformer area in a preset time period, and performing early warning treatment according to the power utilization time period corresponding to each high-voltage transformer area.
As above, the specific steps corresponding to step S1 are as follows: s11, counting all high-voltage transformer areas in the target high-voltage power grid management area, and numbering all high-voltage transformer areas in the target high-voltage power grid management area as
Figure 281079DEST_PATH_IMAGE001
。
S12, acquiring real-time electricity consumption of each user demand side of each high-voltage transformer area in a preset time period through the corresponding intelligent electric meters of each user demand side in each high-voltage transformer area, and marking the real-time electricity consumption of each user demand side of each high-voltage transformer area in the preset time period as electricity consumption
Figure 932640DEST_PATH_IMAGE002
，
Figure 181218DEST_PATH_IMAGE003
I is the number of the ith high voltage station area,
Figure 310848DEST_PATH_IMAGE004
and j is the number of the j-th user demand side.
S13, obtaining real-time power supply quantity of each high-voltage transformer area in a preset time period, and analyzing to obtain the power consumption quantity of each high-voltage transformer area in the preset time period
Figure 859641DEST_PATH_IMAGE005
In which
Figure 416525DEST_PATH_IMAGE006
Expressed as the power loss of the ith high-voltage station zone in a preset time period,
Figure 152400DEST_PATH_IMAGE007
the power supply amount of the ith high-voltage station zone is expressed in real time within a preset time period.
As above, the monitoring of the meteorological parameter data of each high voltage transformer area in the preset time period in step S2 specifically includes: monitoring meteorological parameter data of each high-voltage transformer area in a preset time period, wherein the meteorological parameter data comprise wind speed, temperature, rainfall and fog concentration, and respectively marking the wind speed, the temperature, the rainfall and the fog concentration of each high-voltage transformer area in the preset time period as
Figure 820141DEST_PATH_IMAGE008
。
Analyzing meteorological parameter influence indexes of high-voltage transformer areas in preset time period
Figure 223441DEST_PATH_IMAGE009
Wherein
Figure 685646DEST_PATH_IMAGE010
Expressed as a meteorological parameter influence index of the ith high-voltage transformer area in a preset time period, e is expressed as a natural constant,
Figure 174396DEST_PATH_IMAGE011
respectively expressed as influence weight factors corresponding to preset wind speed, temperature, rainfall and fog concentration,
Figure 878785DEST_PATH_IMAGE012
，
Figure 136591DEST_PATH_IMAGE013
respectively expressed as the proper wind speed, the proper temperature, the proper rainfall and the proper fog concentration of the preset high-voltage line corresponding to the proper meteorological environment under the condition of normal grid loss rate,
Figure 35277DEST_PATH_IMAGE014
respectively expressed as a preset allowable wind speed deviation value, an allowable temperature deviation value, an allowable rainfall deviation value and an allowable fog concentration deviation value.
As described above, the line network loss rate of each high voltage transformer area in the step S2 is analyzed in a specific analysis manner: the power consumption of each high-voltage transformer area in a preset time period
Figure 11323DEST_PATH_IMAGE015
Real-time power supply
Figure 20867DEST_PATH_IMAGE016
And weather parameter influence index
Figure 133180DEST_PATH_IMAGE017
Substituting into line network loss rate analysis formula
Figure 202767DEST_PATH_IMAGE018
Obtaining the line network loss rate of each high-voltage transformer area in a preset time period
Figure 666109DEST_PATH_IMAGE019
Wherein
Figure 479345DEST_PATH_IMAGE020
Expressed as a preset line network loss rate impact compensation factor.
As above, the specific steps corresponding to step S3 are as follows: s31, extracting the standard grid loss rate of the power line corresponding to each high-voltage transformer area stored in the data storage library of the power system in the suitable meteorological environment, and analyzing the line abnormal index corresponding to each high-voltage transformer area
Figure 711743DEST_PATH_IMAGE021
In which
Figure 217811DEST_PATH_IMAGE022
Expressed as the line anomaly index corresponding to the ith high-voltage station area,
Figure 902870DEST_PATH_IMAGE023
expressed as a preset line anomaly index bias factor,
Figure 752752DEST_PATH_IMAGE024
and the standard grid loss rate of the power line corresponding to the ith high-voltage transformer area in the suitable meteorological environment is expressed.
And S32, comparing the abnormal line index corresponding to each high-voltage transformer area with a preset abnormal high-voltage transformer area line index threshold, if the abnormal line index corresponding to a certain high-voltage transformer area is smaller than the preset abnormal high-voltage transformer area line index threshold, indicating that the line corresponding to the high-voltage transformer area is in a normal transmission state, and if the abnormal line index corresponding to a certain high-voltage transformer area is larger than or equal to the preset abnormal high-voltage transformer area line index threshold, indicating that the line corresponding to the high-voltage transformer area is in an abnormal transmission state, and informing a manager of the high-voltage transformer area to perform routing inspection processing on the corresponding line.
As above, the specific steps corresponding to step S4 include: monitoring instantaneous voltage of each high-voltage transformer area corresponding to each acquisition time point at each user demand side in a preset time period through a voltage sensor to obtain the instantaneous voltage of each high-voltage transformer area corresponding to each acquisition time point at each user demand side in the preset time period, and marking the instantaneous voltage as the instantaneous voltage
Figure 839657DEST_PATH_IMAGE025
，
Figure 516626DEST_PATH_IMAGE026
And r is the number of the r-th acquisition time point in the preset time period.
The voltage oscillograph is used for monitoring the voltage waves of each high-voltage platform area corresponding to each acquisition time point at each user demand side in the preset time period to obtain the voltage waves of each high-voltage platform area corresponding to each acquisition time point at each user demand side in the preset time period, and extracting the frequency of the voltage waves of each acquisition time point corresponding to each user demand side in the preset time period, the peak top value of each period in the voltage waves of each acquisition time point and the peak bottom value of each period in the voltage waves of each acquisition time point.
As above, in step S5, the voltage fluctuation influence weight index analysis manner of each high voltage station in the preset time period is as follows: and obtaining the power utilization time periods corresponding to the high-voltage transformer areas according to the preset time periods corresponding to the high-voltage transformer areas, and comparing and screening the rated voltages of the high-voltage transformer areas corresponding to the power utilization time periods.
Extracting the instantaneous voltage of each high-voltage transformer area corresponding to each acquisition time point at each user demand side in a preset time period, and analyzing to obtain the voltage fluctuation influence weight index of each high-voltage transformer area in the preset time period
Figure 423402DEST_PATH_IMAGE027
Wherein
Figure 578439DEST_PATH_IMAGE028
Expressed as the voltage fluctuation influence weight index of the ith high-voltage station area in a preset time period,
Figure 519851DEST_PATH_IMAGE029
respectively expressed as a preset voltage stability correction factor and a voltage conformance correction factor, u is expressed as the number of acquisition time points within a preset time period,
Figure 367721DEST_PATH_IMAGE030
the instantaneous voltage of the jth user demand side corresponding to the (r + 1) th collection time point in the preset time period of the ith high-voltage platform area is expressed,
Figure 27372DEST_PATH_IMAGE031
expressed as the rated voltage of the ith high-voltage station zone for the application power period,
Figure 986101DEST_PATH_IMAGE032
represented as a preset allowed voltage discrete floating value.
As above, the analysis manner of the voltage wave of each high voltage platform in the preset time period in step S5 according with the influence weight index is as follows: according to the voltage waves of each high-voltage platform area corresponding to each acquisition time point at each user demand side in the preset time period, screening the standard voltage waves of each high-voltage platform area corresponding to each acquisition time point at each user demand side in the preset time period, and extracting the frequency of the standard voltage waves of each acquisition time point at each user demand side in the preset time period, the peak top value of each period in the standard voltage waves of each acquisition time point and the peak bottom value of each period in the standard voltage waves of each acquisition time point.
Analyzing the voltage wave of each high-voltage transformer area in a preset time period to accord with an influence weight index
Figure 782019DEST_PATH_IMAGE033
Wherein
Figure 800790DEST_PATH_IMAGE034
The voltage wave of the ith high-voltage platform region in a preset time period is expressed to be in accordance with the influence weight index,
Figure 947738DEST_PATH_IMAGE035
respectively expressed as coincidence influence factors corresponding to preset voltage wave frequency and coincidence influence factors corresponding to voltage wave peak value,
Figure 444578DEST_PATH_IMAGE036
respectively representing the frequency of a voltage wave at the r-th collection time point corresponding to the j-th user demand side in the ith high-voltage platform area in a preset time period, the peak top value of the s-th period in the voltage wave at the r-th collection time point and the peak bottom value of the s-th period in the voltage wave at the r-th collection time point,
Figure 859117DEST_PATH_IMAGE037
，
Figure 783211DEST_PATH_IMAGE038
respectively representing the frequency of the standard voltage wave of the r collecting time point corresponding to the j user demand side of the ith high-voltage platform area in the preset time period, the peak top value of the s-th period in the standard voltage wave of the r collecting time point and the peak bottom value of the s-th period in the standard voltage wave of the r collecting time point,
Figure 151875DEST_PATH_IMAGE039
expressed as a preset deviation value of the frequency of the allowed voltage wave and a deviation value of the peak value of the allowed voltage wave, and d is expressed as the number of cycles.
As described above, in step S6, the power supply quality evaluation coefficient of each high-voltage platform area in the preset time period is analyzed, and the specific analysis manner is.
Influence weight index of voltage fluctuation of each high-voltage transformer area in preset time period
Figure 452406DEST_PATH_IMAGE040
Coincidence of sum voltage wave with influence weight index
Figure 222916DEST_PATH_IMAGE041
Substituting power supply quality evaluation coefficient analysis formula
Figure 317911DEST_PATH_IMAGE042
Obtaining the power supply quality evaluation coefficient of each high-voltage transformer area in a preset time period
Figure 173872DEST_PATH_IMAGE043
In which
Figure 278094DEST_PATH_IMAGE044
Respectively expressed as a preset voltage fluctuation influence compensation factor and a voltage wave coincidence influence compensation factor, and e is expressed as a natural constant.
Compared with the prior art, the data analysis method for the high-voltage transformer area power system has the following beneficial effects: the real-time power consumption of each user demand side of each high-voltage transformer area in the preset time period is obtained, the line network loss rate of each high-voltage transformer area in the preset time period is analyzed by combining the meteorological parameter data of each high-voltage transformer area in the preset time period, the problem of electric power data monitoring hysteresis is avoided, the line network loss rate of the high-voltage transformer area is monitored and analyzed in real time, the line abnormity index corresponding to each high-voltage transformer area is evaluated, and corresponding processing is carried out according to the comparison result, so that the behavior that partial illegal users steal electric quantity by adopting illegal means is effectively avoided, the economic benefits of the country and the electric power enterprise are further maintained, the normal power supply order is maintained, the operation safety of equipment in the high-voltage transformer area is guaranteed, and the occurrence rate of casualty accidents is reduced.
According to the method, the voltage parameters of each high-voltage transformer area corresponding to each acquisition time point at each user demand side in the preset time period are monitored, the voltage fluctuation influence weight index and the voltage wave coincidence influence weight index of each high-voltage transformer area in the preset time period are obtained through analysis, so that the multi-dimensional analysis of the power operation data of the high-voltage transformer areas is realized, the specified reference data is provided for the later analysis of the power supply quality of the high-voltage transformer areas, the accuracy and the reliability of the analysis result of the power supply quality of the high-voltage transformer areas in the later period are improved, the power supply quality evaluation coefficient of each high-voltage transformer area in the preset time period is analyzed, and the early warning treatment is performed according to the power consumption time period corresponding to each high-voltage transformer area, so that the safe power supply of the high-voltage transformer areas is guaranteed, the power supply quality demand of the user demand sides in the power consumption time periods is met, the normal operation of the power consumption equipment corresponding to the user demand sides is further ensured, and the potential safety power consumption of the user demand sides is avoided.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments 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 the drawings without creative efforts.
FIG. 1 is a schematic flow chart of the method of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the present invention provides a data analysis method for a power system of a high voltage transformer area, including the following steps: s1, acquiring real-time electricity consumption of a user demand side: and acquiring the real-time power consumption of each high-voltage transformer area on each user demand side in a preset time period, and acquiring the power consumption of each high-voltage transformer area in the preset time period.
On the basis of the above embodiment, the specific steps corresponding to the step S1 are as follows: s11, counting all high-voltage transformer areas in the target high-voltage power grid management area, and presetting all high-voltage transformer areas in the target high-voltage power grid management areaAre sequentially numbered as
Figure 903110DEST_PATH_IMAGE045
。
S12, acquiring real-time electricity consumption of each user demand side of each high-voltage transformer area in a preset time period through the corresponding intelligent electric meters of each user demand side in each high-voltage transformer area, and marking the real-time electricity consumption of each user demand side of each high-voltage transformer area in the preset time period as electricity consumption
Figure 434586DEST_PATH_IMAGE046
，
Figure 777843DEST_PATH_IMAGE047
I is the number of the ith high voltage station area,
Figure 685756DEST_PATH_IMAGE048
and j is the number of the j-th user demand side.
S13, acquiring real-time power supply quantity of each high-voltage transformer area in a preset time period, and analyzing to obtain the power consumption quantity of each high-voltage transformer area in the preset time period
Figure 663814DEST_PATH_IMAGE049
Wherein
Figure 366191DEST_PATH_IMAGE050
Expressed as the power loss of the ith high-voltage station zone in a preset time period,
Figure 196743DEST_PATH_IMAGE051
the power supply amount of the ith high-voltage station zone is expressed in real time within a preset time period.
S2, analyzing the loss rate of the high-voltage transformer area line network: and monitoring meteorological parameter data of each high-voltage transformer area in a preset time period, and analyzing the line network loss rate of each high-voltage transformer area in the preset time period.
On the basis of the above embodiment, the monitoring meteorological parameter data of each high voltage transformer area in the step S2 in a preset time period specifically includes: monitoringThe method comprises the steps that meteorological parameter data of each high-voltage transformer area in a preset time period comprise wind speed, temperature, rainfall and fog concentration, and the wind speed, the temperature, the rainfall and the fog concentration of each high-voltage transformer area in the preset time period are respectively marked as
Figure 377189DEST_PATH_IMAGE052
。
Analyzing meteorological parameter influence indexes of high-voltage transformer areas in preset time periods
Figure 976798DEST_PATH_IMAGE053
Wherein
Figure 850076DEST_PATH_IMAGE054
Expressed as a meteorological parameter influence index of the ith high-voltage transformer area in a preset time period, e is expressed as a natural constant,
Figure 902345DEST_PATH_IMAGE055
respectively expressed as influence weight factors corresponding to preset wind speed, temperature, rainfall and fog concentration,
Figure 886482DEST_PATH_IMAGE056
，
Figure 606176DEST_PATH_IMAGE057
respectively expressed as the proper wind speed, the proper temperature, the proper rainfall and the proper fog concentration of the preset high-voltage line corresponding to the proper meteorological environment under the condition of normal grid loss,
Figure 384776DEST_PATH_IMAGE058
respectively expressed as a preset allowable wind speed deviation value, an allowable temperature deviation value, an allowable rainfall deviation value and an allowable fog concentration deviation value.
As a specific embodiment of the present invention, in the above, the wind speed of each high voltage platform area in a preset time period is detected by a wind speed sensor, wherein the wind speed sensor is respectively installed in each high voltage platform area; detecting the temperature of each high-voltage transformer area within a preset time period through a temperature sensor, wherein the temperature sensors are respectively installed in the high-voltage transformer areas; detecting rainfall of each high-voltage platform area in a preset time period through a rainfall monitor, wherein the rainfall monitors are respectively installed in the high-voltage platform areas; and detecting the fog concentration of each high-voltage transformer area in a preset time period through a fog concentration detector, wherein the fog concentration detectors are respectively installed in the high-voltage transformer areas.
On the basis of the above embodiment, the analyzing step S2 analyzes the line network loss rate of each high-voltage transformer area in a preset time period, and the specific analyzing method is as follows: the power loss of each high-voltage transformer area in a preset time period
Figure 189921DEST_PATH_IMAGE059
Real-time power supply amount
Figure 712169DEST_PATH_IMAGE060
And weather parameter influence index
Figure 784905DEST_PATH_IMAGE061
Substituted into line network loss rate analysis formula
Figure 999986DEST_PATH_IMAGE062
Obtaining the line network loss rate of each high-voltage transformer area in a preset time period
Figure 761269DEST_PATH_IMAGE063
In which
Figure 87208DEST_PATH_IMAGE064
Expressed as a preset line network loss rate impact compensation factor.
S3, evaluating the abnormal indexes of the lines in the high-voltage transformer area: and evaluating the line abnormal index corresponding to each high-voltage transformer area, comparing the line abnormal index with a preset line abnormal index threshold value, and performing corresponding processing according to the comparison result.
On the basis of the above embodiment, the specific steps corresponding to step S3 are as follows: s31, extracting power lines corresponding to high-voltage transformer areas stored in a power system data storage libraryAnalyzing the line abnormal index corresponding to each high-voltage transformer area in the standard network loss rate suitable for the meteorological environment
Figure 515915DEST_PATH_IMAGE065
In which
Figure 636318DEST_PATH_IMAGE066
Expressed as the line anomaly index corresponding to the ith high-voltage station area,
Figure 681634DEST_PATH_IMAGE067
expressed as a preset line anomaly index bias factor,
Figure 545685DEST_PATH_IMAGE068
the standard grid loss rate of the power line corresponding to the ith high-voltage transformer area in the suitable meteorological environment is expressed.
And S32, comparing the abnormal line index corresponding to each high-voltage transformer area with a preset abnormal high-voltage transformer area line index threshold, if the abnormal line index corresponding to a certain high-voltage transformer area is smaller than the preset abnormal high-voltage transformer area line index threshold, indicating that the line corresponding to the high-voltage transformer area is in a normal transmission state, and if the abnormal line index corresponding to a certain high-voltage transformer area is larger than or equal to the preset abnormal high-voltage transformer area line index threshold, indicating that the line corresponding to the high-voltage transformer area is in an abnormal transmission state, and informing a manager of the high-voltage transformer area to perform routing inspection processing on the corresponding line.
In the embodiment, the real-time power consumption of each user demand side of each high-voltage transformer area in the preset time period is obtained, the line network loss rate of each high-voltage transformer area in the preset time period is analyzed by combining the meteorological parameter data of each high-voltage transformer area in the preset time period, so that the problem of electric power data hysteresis monitoring is avoided, the line network loss rate of the high-voltage transformer area is monitored and analyzed in real time, the line abnormal index corresponding to each high-voltage transformer area is evaluated, and corresponding processing is performed according to the comparison result, so that the action that part of illegal users steal electric quantity by adopting an illegal means is effectively avoided, the economic benefits of countries and power enterprises are further maintained, the normal power supply order is maintained, the operation safety of equipment in the high-voltage transformer areas is guaranteed, and the occurrence rate of casualty accidents is reduced.
S4, monitoring voltage parameters of a user demand side: and monitoring instantaneous voltage and voltage waves of each high-voltage transformer area corresponding to each acquisition time point at each user demand side in a preset time period to form voltage parameters of each high-voltage transformer area corresponding to each acquisition time point at each user demand side in the preset time period.
On the basis of the above embodiment, the specific steps corresponding to the step S4 include: monitoring the instantaneous voltage of each high-voltage transformer area corresponding to each acquisition time point at each user demand side in a preset time period through a voltage sensor to obtain the instantaneous voltage of each high-voltage transformer area corresponding to each acquisition time point at each user demand side in the preset time period, and marking the instantaneous voltage as the instantaneous voltage
Figure 94478DEST_PATH_IMAGE069
，
Figure 651361DEST_PATH_IMAGE070
And r is the number of the r-th acquisition time point in the preset time period.
The voltage oscillograph is used for monitoring the voltage waves of each high-voltage platform area corresponding to each acquisition time point at each user demand side in the preset time period to obtain the voltage waves of each high-voltage platform area corresponding to each acquisition time point at each user demand side in the preset time period, and extracting the frequency of the voltage waves of each acquisition time point corresponding to each user demand side in the preset time period, the peak top value of each period in the voltage waves of each acquisition time point and the peak bottom value of each period in the voltage waves of each acquisition time point.
S5, analyzing voltage parameters of a user demand side: and analyzing the voltage parameters of each high-voltage transformer area corresponding to each acquisition time point at each user demand side in a preset time period to obtain a voltage fluctuation influence weight index and a voltage wave coincidence influence weight index of each high-voltage transformer area in the preset time period.
On the basis of the above embodiment, in the step S5, the voltage fluctuation influence weight index analysis manner of each high-voltage platform area in the preset time period is as follows: and obtaining the power utilization time periods corresponding to the high-voltage transformer areas according to the preset time periods corresponding to the high-voltage transformer areas, and comparing and screening the rated voltages of the high-voltage transformer areas corresponding to the power utilization time periods.
Extracting the instantaneous voltage of each high-voltage transformer area corresponding to each acquisition time point at each user demand side in a preset time period, and analyzing to obtain the voltage fluctuation influence weight index of each high-voltage transformer area in the preset time period
Figure 652815DEST_PATH_IMAGE071
Wherein
Figure 320557DEST_PATH_IMAGE072
Expressed as the voltage fluctuation influence weight index of the ith high-voltage station area in a preset time period,
Figure 956813DEST_PATH_IMAGE073
respectively expressed as a preset voltage stability correction factor and a voltage conformance correction factor, u is expressed as the number of acquisition time points within a preset time period,
Figure 950176DEST_PATH_IMAGE074
the instantaneous voltage of the jth user demand side corresponding to the (r + 1) th collection time point in the preset time period of the ith high-voltage platform area is expressed,
Figure 438927DEST_PATH_IMAGE075
expressed as the rated voltage of the ith high-voltage station zone for the application power period,
Figure 910359DEST_PATH_IMAGE076
represented as a preset allowed voltage discrete floating value.
As a specific embodiment of the present invention, the comparing and screening the rated voltages of the high-voltage transformer areas for the application power periods specifically includes: comparing the preset time periods corresponding to the high-voltage transformer areas with the standard time periods corresponding to the preset power utilization periods according to the preset time periods corresponding to the high-voltage transformer areas, if the preset time periods corresponding to the high-voltage transformer areas are completely in the standard time periods corresponding to the set power utilization periods, the power utilization periods corresponding to the high-voltage transformer areas are the set power utilization periods, otherwise, counting the set power utilization periods corresponding to the preset time periods of the high-voltage transformer areas, obtaining the corresponding weights of the set power utilization periods corresponding to the preset time periods of the high-voltage transformer areas according to the corresponding weights of the preset power utilization periods, screening the set power utilization period with the highest weight, recording the set power utilization period as the power utilization period corresponding to the high-voltage transformer areas, and further counting the power utilization periods corresponding to the high-voltage transformer areas.
And extracting rated voltages which need to be provided by each high-voltage station area in each set power utilization period and are stored in the power system data storage library, screening to obtain the rated voltages which need to be provided by each high-voltage station area in the corresponding power utilization period, and recording the rated voltages as the rated voltages of each high-voltage station area in the corresponding power utilization period.
Further, each set electricity utilization period comprises a peak electricity utilization period, a peak power utilization period and a valley electricity utilization period, wherein the corresponding weight of the peak electricity utilization period is greater than that of the peak electricity utilization period, and the corresponding weight of the peak electricity utilization period is greater than that of the valley electricity utilization period.
On the basis of the above embodiment, the voltage wave of each high voltage platform in the step S5 in the preset time period conforms to the analysis manner of the influence weight index: according to the voltage waves of each high-voltage platform area corresponding to each acquisition time point at each user demand side in the preset time period, screening the standard voltage waves of each high-voltage platform area corresponding to each acquisition time point at each user demand side in the preset time period, and extracting the frequency of the standard voltage waves of each acquisition time point at each user demand side in the preset time period, the peak top value of each period in the standard voltage waves of each acquisition time point and the peak bottom value of each period in the standard voltage waves of each acquisition time point.
Analyzing the voltage wave of each high-voltage transformer area in a preset time period to accord with an influence weight index
Figure 168165DEST_PATH_IMAGE077
Wherein
Figure 66851DEST_PATH_IMAGE078
The voltage wave of the ith high-voltage platform region in a preset time period is expressed to be in accordance with the influence weight index,
Figure 511739DEST_PATH_IMAGE079
respectively expressed as coincidence influence factors corresponding to preset voltage wave frequency and coincidence influence factors corresponding to voltage wave peak value,
Figure 786862DEST_PATH_IMAGE080
respectively representing the frequency of a voltage wave at the r collecting time point corresponding to the j user demand side of the ith high-voltage platform area in a preset time period, the peak top value of the s-th period in the voltage wave at the r collecting time point and the peak bottom value of the s-th period in the voltage wave at the r collecting time point,
Figure 164754DEST_PATH_IMAGE081
，
Figure 968762DEST_PATH_IMAGE082
respectively representing the frequency of a reference voltage wave of an r-th collection time point, the peak top value of the s-th period in the reference voltage wave of the r-th collection time point and the peak bottom value of the s-th period in the reference voltage wave of the r-th collection time point at the j-th user demand side of the ith high-voltage platform area in a preset time period,
Figure 432104DEST_PATH_IMAGE083
expressed as a preset deviation value of the frequency of the allowed voltage wave and a deviation value of the peak value of the allowed voltage wave, and d is expressed as the number of cycles.
As a specific embodiment of the present invention, the standard voltage wave screening manner of each high voltage platform area corresponding to each acquisition time point at each user demand side in a preset time period is as follows: extracting voltage waves of each high-voltage transformer area corresponding to each acquisition time point at each user demand side in a preset time period to obtain voltage waveforms of each high-voltage transformer area corresponding to each acquisition time point at each user demand side in the preset time period; and extracting standard voltage waves of voltage waveforms corresponding to the set power consumption periods of the high-voltage transformer areas stored in the power system data storage library, and screening the standard voltage waves of the high-voltage transformer areas corresponding to the acquisition time points of the user demand sides in the preset time period according to the power consumption periods corresponding to the high-voltage transformer areas.
S6, analyzing and processing a power supply quality evaluation coefficient: and analyzing the power supply quality evaluation coefficient of each high-voltage transformer area in a preset time period, and performing early warning treatment according to the power utilization time period corresponding to each high-voltage transformer area.
On the basis of the foregoing embodiment, in step S6, the power supply quality evaluation coefficient of each high-voltage platform area in a preset time period is analyzed in a specific analysis manner: influence weight index of voltage fluctuation of each high-voltage transformer area in preset time period
Figure 979760DEST_PATH_IMAGE084
Coincidence of sum voltage wave with influence weight index
Figure 710694DEST_PATH_IMAGE085
Substituting power supply quality evaluation coefficient analysis formula
Figure 951182DEST_PATH_IMAGE086
Obtaining the power supply quality evaluation coefficient of each high-voltage transformer area in a preset time period
Figure 636241DEST_PATH_IMAGE087
Wherein
Figure 253168DEST_PATH_IMAGE088
Respectively expressed as a preset voltage fluctuation influence compensation factor and a voltage wave coincidence influence compensation factor, and e is expressed as a natural constant.
It should be noted that, in the step S6, the early warning processing is performed according to the power utilization time period corresponding to each high-voltage platform area, and the method specifically includes: the method comprises the steps of extracting safe power supply quality evaluation coefficient ranges corresponding to all set power utilization periods of a user demand side stored in a power system data storage library, screening the safe power supply quality evaluation coefficient ranges corresponding to all high-voltage transformer areas according to the power utilization periods corresponding to all high-voltage transformer areas, comparing the power supply quality evaluation coefficients of all high-voltage transformer areas in a preset time period with the corresponding safe power supply quality evaluation coefficient ranges, if the power supply quality evaluation coefficients of certain high-voltage transformer areas in the preset time period are out of the corresponding safe power supply quality evaluation coefficient ranges, sending early warning prompts to the high-voltage transformer areas, and carrying out corresponding maintenance regulation measures through corresponding staff of the high-voltage transformer areas.
In this embodiment, the voltage parameters of each high-voltage platform area corresponding to each acquisition time point on each user demand side in the preset time period are monitored, the voltage fluctuation influence weight index and the voltage wave of each high-voltage platform area in the preset time period are obtained through analysis, so that the multi-dimensional analysis of the power operation data of the high-voltage platform area is realized, the instructive reference data is provided for the later analysis of the power supply quality of the high-voltage platform area, the accuracy and the reliability of the analysis result of the power supply quality of the high-voltage platform area in the later period are improved, the power supply quality evaluation coefficient of each high-voltage platform area in the preset time period is analyzed, and the early warning treatment is performed according to the power utilization period corresponding to each high-voltage platform area, so that the safe power supply of the high-voltage platform area is ensured, the power supply quality demand of the user demand side in the corresponding power utilization period is met, the normal operation of the user demand side on the power utilization equipment is further ensured, and the potential hazard caused on the safe power utilization of the user demand side is avoided.
The foregoing is merely exemplary and illustrative of the principles of the present invention and various modifications, additions and substitutions of the specific embodiments described herein may be made by those skilled in the art without departing from the principles of the present invention or exceeding the scope of the claims set forth herein.

Claims (6)

1. A data analysis method for a high-voltage transformer area power system is characterized by comprising the following steps:
s1, acquiring real-time electricity consumption of a user demand side: acquiring real-time power consumption of each high-voltage transformer area on each user demand side in a preset time period, and acquiring power loss of each high-voltage transformer area in the preset time period;
s2, analyzing the loss rate of the line network of the high-voltage transformer area: monitoring meteorological parameter data of each high-voltage transformer area in a preset time period, and analyzing the line network loss rate of each high-voltage transformer area in the preset time period;
s3, evaluating the abnormal index of the high-voltage transformer area circuit: evaluating the line abnormal index corresponding to each high-voltage transformer area, comparing the line abnormal index with a preset line abnormal index threshold value, and performing corresponding processing according to the comparison result;
s4, monitoring voltage parameters of a user demand side: monitoring instantaneous voltage and voltage waves of each high-voltage transformer area corresponding to each acquisition time point at each user demand side in a preset time period to form voltage parameters of each high-voltage transformer area corresponding to each acquisition time point at each user demand side in the preset time period;
s5, analyzing voltage parameters of a user demand side: analyzing voltage parameters of each high-voltage transformer area corresponding to each acquisition time point at each user demand side in a preset time period to obtain a voltage fluctuation influence weight index and a voltage wave coincidence influence weight index of each high-voltage transformer area in the preset time period;
s6, analyzing and processing a power supply quality evaluation coefficient: analyzing power supply quality evaluation coefficients of the high-voltage transformer areas in a preset time period, and performing early warning processing according to the power utilization time period corresponding to the high-voltage transformer areas;
the specific steps corresponding to the step S4 comprise:
monitoring instantaneous voltage of each high-voltage transformer area corresponding to each acquisition time point at each user demand side in a preset time period through a voltage sensor to obtain the instantaneous voltage of each high-voltage transformer area corresponding to each acquisition time point at each user demand side in the preset time period, and marking the instantaneous voltage as the instantaneous voltage
Figure 550678DEST_PATH_IMAGE001
，
Figure 285416DEST_PATH_IMAGE002
And r representsNumbering the r-th acquisition time point in a preset time period;
monitoring voltage waves of each high-voltage platform area corresponding to each acquisition time point at each user demand side in a preset time period through a voltage oscillograph to obtain voltage waves of each high-voltage platform area corresponding to each acquisition time point at each user demand side in the preset time period, and extracting the frequency of the voltage waves of each high-voltage platform area corresponding to each acquisition time point at each user demand side in the preset time period, the peak top value of each period in the voltage waves of each acquisition time point and the peak bottom value of each period in the voltage waves of each acquisition time point;
in the step S5, the voltage fluctuation influence weight index analysis manner of each high-voltage transformer area in the preset time period is as follows:
obtaining the power utilization time periods corresponding to the high-voltage transformer areas according to the preset time periods corresponding to the high-voltage transformer areas, and comparing and screening rated voltages of the high-voltage transformer areas corresponding to the power utilization time periods;
extracting the instantaneous voltage of each high-voltage transformer area corresponding to each acquisition time point at each user demand side in a preset time period, and analyzing to obtain the voltage fluctuation influence weight index of each high-voltage transformer area in the preset time period
Figure 829005DEST_PATH_IMAGE003
Wherein
Figure 940181DEST_PATH_IMAGE004
Expressed as the voltage fluctuation influence weight index of the ith high-voltage station area in a preset time period,
Figure 888545DEST_PATH_IMAGE005
respectively expressed as a preset voltage stability correction factor and a voltage conformance correction factor, u is expressed as the number of acquisition time points within a preset time period,
Figure 794184DEST_PATH_IMAGE006
the instantaneous voltage of the jth user demand side corresponding to the (r + 1) th collection time point in the preset time period of the ith high-voltage platform area is expressed,
Figure 827999DEST_PATH_IMAGE007
expressed as the rated voltage of the ith high-voltage station zone for the application power period,
Figure 618232DEST_PATH_IMAGE008
expressed as a preset allowed voltage discrete floating value;
in the step S5, the analysis mode that the voltage wave of each high-voltage transformer area in the preset time period conforms to the influence weight index is as follows:
according to the voltage waves of each high-voltage platform area corresponding to each acquisition time point at each user demand side in the preset time period, screening the standard voltage waves of each high-voltage platform area corresponding to each acquisition time point at each user demand side in the preset time period, and extracting the frequency of the standard voltage waves of each acquisition time point at each user demand side in the preset time period, the peak top value of each period in the standard voltage waves of each acquisition time point and the peak bottom value of each period in the standard voltage waves of each acquisition time point;
analyzing the voltage wave of each high-voltage transformer area in a preset time period to accord with an influence weight index
Figure 686682DEST_PATH_IMAGE009
Wherein
Figure 766152DEST_PATH_IMAGE010
The voltage wave of the ith high-voltage platform region in a preset time period is expressed to be in accordance with the influence weight index,
Figure 287263DEST_PATH_IMAGE011
respectively expressed as coincidence influence factors corresponding to preset voltage wave frequency and coincidence influence factors corresponding to voltage wave peak value,
Figure 474662DEST_PATH_IMAGE012
respectively expressed as that the ith high-voltage transformer area corresponds to the r-th collection on the jth user demand side in a preset time periodThe frequency of the voltage wave at the intermediate point, the peak top value of the s-th period in the voltage wave at the r-th collection time point and the peak bottom value of the s-th period in the voltage wave at the r-th collection time point,
Figure 397619DEST_PATH_IMAGE013
，
Figure 910640DEST_PATH_IMAGE014
respectively representing the frequency of the standard voltage wave of the r collecting time point corresponding to the j user demand side of the ith high-voltage platform area in the preset time period, the peak top value of the s-th period in the standard voltage wave of the r collecting time point and the peak bottom value of the s-th period in the standard voltage wave of the r collecting time point,
Figure 919047DEST_PATH_IMAGE015
expressed as a preset deviation value of the frequency of the allowed voltage wave and a deviation value of the peak value of the allowed voltage wave, and d is expressed as the number of cycles.
2. The method according to claim 1, wherein the method comprises the following steps: the specific steps corresponding to the step S1 are as follows:
s11, counting all high-voltage transformer areas in the target high-voltage power grid management area, and numbering all high-voltage transformer areas in the target high-voltage power grid management area as
Figure 910137DEST_PATH_IMAGE016
；
S12, acquiring real-time electricity consumption of each user demand side in a preset time period of each high-voltage transformer area through the corresponding intelligent electric meters of each user demand side in each high-voltage transformer area, and marking the real-time electricity consumption of each user demand side in the preset time period of each high-voltage transformer area as a real-time electricity consumption
Figure 687600DEST_PATH_IMAGE017
，
Figure 368593DEST_PATH_IMAGE018
I is the number of the ith high voltage station,
Figure 598717DEST_PATH_IMAGE019
j is the number of the jth user demand side;
s13, acquiring real-time power supply quantity of each high-voltage transformer area in a preset time period, and analyzing to obtain the power consumption quantity of each high-voltage transformer area in the preset time period
Figure 393497DEST_PATH_IMAGE020
Wherein
Figure 25467DEST_PATH_IMAGE021
Expressed as the power loss of the ith high-voltage station zone in a preset time period,
Figure 614711DEST_PATH_IMAGE022
the power supply amount of the ith high-voltage station zone is expressed in real time within a preset time period.
3. The method for analyzing the data of the power system of the high-voltage transformer area as claimed in claim 1, wherein: in step S2, monitoring meteorological parameter data of each high-voltage transformer area within a preset time period specifically includes:
monitoring meteorological parameter data of each high-voltage transformer area in a preset time period, wherein the meteorological parameter data comprise wind speed, temperature, rainfall and fog concentration, and marking the wind speed, the temperature, the rainfall and the fog concentration of each high-voltage transformer area in the preset time period as wind speed, temperature, rainfall and fog concentration respectively
Figure 597711DEST_PATH_IMAGE023
；
Analyzing meteorological parameter influence indexes of high-voltage transformer areas in preset time period
Figure 71549DEST_PATH_IMAGE024
In which
Figure 417079DEST_PATH_IMAGE025
Expressed as a meteorological parameter influence index of the ith high-voltage transformer area in a preset time period, e is expressed as a natural constant,
Figure 410898DEST_PATH_IMAGE026
respectively expressed as influence weight factors corresponding to preset wind speed, temperature, rainfall and fog concentration,
Figure 474669DEST_PATH_IMAGE027
，
Figure 611252DEST_PATH_IMAGE028
respectively expressed as the proper wind speed, the proper temperature, the proper rainfall and the proper fog concentration of the preset high-voltage line corresponding to the proper meteorological environment under the condition of normal grid loss,
Figure 952235DEST_PATH_IMAGE029
respectively expressed as a preset allowable wind speed deviation value, an allowable temperature deviation value, an allowable rainfall deviation value and an allowable fog concentration deviation value.
4. The method according to claim 3, wherein the method comprises the following steps: in step S2, the line network loss rate of each high-voltage transformer area in a preset time period is analyzed, and the specific analysis mode is as follows:
the power consumption of each high-voltage transformer area in a preset time period
Figure 148861DEST_PATH_IMAGE030
Real-time power supply amount
Figure 981819DEST_PATH_IMAGE031
And weather parameter influence index
Figure 515568DEST_PATH_IMAGE032
Substituting into line network loss rate analysis formula
Figure 114653DEST_PATH_IMAGE033
Obtaining the line network loss rate of each high-voltage transformer area in a preset time period
Figure 482180DEST_PATH_IMAGE034
In which
Figure 395909DEST_PATH_IMAGE035
Expressed as a preset line network loss rate impact compensation factor.
5. The method according to claim 4, wherein the method comprises the following steps: the specific steps corresponding to the step S3 are as follows:
s31, extracting the standard grid loss rate of the power line corresponding to each high-voltage transformer area stored in the power system data storage library in the suitable meteorological environment, and analyzing the line abnormity index corresponding to each high-voltage transformer area
Figure 874295DEST_PATH_IMAGE036
Wherein
Figure 455449DEST_PATH_IMAGE037
Expressed as the line anomaly index corresponding to the ith high-voltage station area,
Figure 728299DEST_PATH_IMAGE038
expressed as a preset line anomaly index bias factor,
Figure 660483DEST_PATH_IMAGE039
the standard grid loss rate of the power line corresponding to the ith high-voltage transformer area in the suitable meteorological environment is represented;
and S32, comparing the line abnormal index corresponding to each high-voltage transformer area with a preset high-voltage transformer area line abnormal index threshold, if the line abnormal index corresponding to a certain high-voltage transformer area is smaller than the preset high-voltage transformer area line abnormal index threshold, indicating that the line corresponding to the high-voltage transformer area is in a normal transmission state, and if the line abnormal index corresponding to the certain high-voltage transformer area is larger than or equal to the preset high-voltage transformer area line abnormal index threshold, indicating that the line corresponding to the high-voltage transformer area is in an abnormal transmission state, and informing a manager of the high-voltage transformer area to perform routing inspection processing on the corresponding line.
6. The method for analyzing the data of the power system of the high-voltage transformer area as claimed in claim 1, wherein: in the step S6, power supply quality evaluation coefficients of each high-voltage transformer area in a preset time period are analyzed, and the specific analysis mode is;
influence weight index of voltage fluctuation of each high-voltage transformer area in preset time period
Figure 676980DEST_PATH_IMAGE040
Coincidence of sum voltage wave with influence weight index
Figure 115570DEST_PATH_IMAGE041
Substituting power supply quality evaluation coefficient analysis formula
Figure 559321DEST_PATH_IMAGE042
Obtaining the power supply quality evaluation coefficient of each high-voltage transformer area in a preset time period
Figure 713222DEST_PATH_IMAGE043
Wherein
Figure 533411DEST_PATH_IMAGE044
Respectively expressed as a preset voltage fluctuation influence compensation factor and a voltage wave coincidence influence compensation factor, and e is expressed as a natural constant.
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