CN116526665A - Data processing system based on electric power edge calculation - Google Patents
Data processing system based on electric power edge calculation Download PDFInfo
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- CN116526665A CN116526665A CN202310426752.3A CN202310426752A CN116526665A CN 116526665 A CN116526665 A CN 116526665A CN 202310426752 A CN202310426752 A CN 202310426752A CN 116526665 A CN116526665 A CN 116526665A
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- 230000007613 environmental effect Effects 0.000 claims abstract description 40
- 230000005611 electricity Effects 0.000 claims abstract description 24
- 238000012544 monitoring process Methods 0.000 claims abstract description 14
- 230000005856 abnormality Effects 0.000 claims abstract description 10
- 238000000034 method Methods 0.000 claims description 29
- 238000004458 analytical method Methods 0.000 claims description 21
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- 238000010223 real-time analysis Methods 0.000 claims description 3
- 238000007405 data analysis Methods 0.000 abstract description 3
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Classifications
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00002—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by monitoring
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00001—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by the display of information or by user interaction, e.g. supervisory control and data acquisition systems [SCADA] or graphical user interfaces [GUI]
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00032—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
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Abstract
The invention relates to the technical field of power data analysis, and particularly discloses a power edge-based computing data processing system, which comprises the following components: the power data acquisition module is used for acquiring the whole power data of the platform area; the user meter is used for collecting user electricity data of a single user; the environment state monitoring module is used for monitoring environment state parameters of the station area; the edge computing equipment is used for analyzing the line loss condition of the platform area in real time according to the whole power data of the platform area, the power consumption data of the user and the environmental state parameters, and judging the power consumption abnormality of the user according to the power consumption data of the user and the environmental state parameters. The system analyzes the line loss condition of the platform area in real time based on the whole power data of the platform area, the power consumption data of the user and the environmental state parameters through the edge computing equipment, judges the power consumption abnormality of the user, and accurately judges the power consumption safety condition of the user and the out-of-tolerance condition of the line loss rate.
Description
Technical Field
The invention relates to the technical field of power data analysis, in particular to a power edge-based computing data processing system.
Background
Along with the continuous expansion of the electric power scale, the load condition of the power grid is continuously increased, and the electric power system is an important support for guaranteeing the stable development of national economy, so that the abnormal electricity utilization condition of a user and the line loss of the power grid are required to be timely judged for guaranteeing the safe and stable operation of the electric power system, the operation safety of the electric power system can be effectively guaranteed, and the economic loss caused by the line loss to the power grid is reduced.
The conventional power consumption monitoring and line loss judging system is mainly realized through a power monitoring center of a power grid management department, however, the analysis processing process in a huge amount of power grid data sets causes increased pressure on power grid management, so that the safety of power operation is ensured by setting an edge on a user side of a platform area, performing corresponding peripheral power data record monitoring through edge equipment and timely record early warning when power risks occur.
However, the existing line loss analysis method is mostly performed periodically, that is, the line loss is calculated once according to one charging period, and with the application of the edge equipment, the line loss condition can be analyzed in real time, however, the existing line loss judgment process mainly compares the line loss rate calculated in real time with a standard value, and judges through a difference value, and under different power conditions and environment conditions, the line loss rate is different, so that the same standard can only judge whether the line loss rate meets the requirement, but cannot judge the condition that the line loss rate is out of tolerance, and further is unfavorable for subsequent analysis and judgment; meanwhile, in the safety monitoring process of the safety electricity consumption of the user, the existing monitoring mode is mainly used for monitoring the electricity consumption value of the user and comparing the electricity consumption value with the standard value, and the mode cannot judge the electricity consumption state of the user adaptively, so that the judgment is inaccurate.
Disclosure of Invention
The invention aims to provide a power edge-based computing data processing system, which solves the following technical problems:
how to accurately judge the electricity safety condition of a user and accurately judge the out-of-tolerance condition of the line loss rate through the electric power edge equipment.
The aim of the invention can be achieved by the following technical scheme:
a power edge-based computing data processing system, the system comprising:
the power data acquisition module is used for acquiring the whole power data of the platform area;
the user meter is used for collecting user electricity data of a single user;
the environment state monitoring module is used for monitoring environment state parameters of the station area;
the edge computing equipment is used for analyzing the line loss condition of the platform area in real time according to the whole power data of the platform area, the power consumption data of the user and the environmental state parameters, and judging the power consumption abnormality of the user according to the power consumption data of the user and the environmental state parameters.
In one embodiment, the process of determining the abnormal electricity consumption of the user includes:
acquiring a historical load curve F (t) of each user in a platform region and an average historical load curve of the platform region
By the formulaObtaining a load difference curve delta F (t) of a user;
obtaining a key value set { t for a user load difference curve Δf (t) by Δf' (t) =0 1 ，t 2 ，…，t n }；
Acquiring a period and environmental parameters corresponding to the key values, and forming a feature set { t } for each key value i ，ΔF(t i )，P i ，T i }；
Analyzing the characteristic value of each user to form an analysis model;
inputting the real-time characteristic set of the user into an analysis model, and judging the electricity utilization abnormality of the user;
wherein P is i At t i Time period T of i At t i Temperature value at the moment.
In one embodiment, the process of obtaining the analytical model is:
according to period P in the feature set i Fitting a reference load difference interval and a corresponding temperature interval to each preset time period;
combining the load difference intervals and the corresponding temperature intervals of all the time periods to generate an analysis model;
the process for judging the abnormal electricity consumption of the user according to the analysis model comprises the following steps:
t in real-time feature set according to user i Judging the period P i P in feature set i ，T i Respectively with period P i And comparing the corresponding reference load difference interval with the corresponding temperature interval, and judging whether the electricity consumption of the user is abnormal or not according to the comparison result.
In one embodiment, the process of real-time analysis of line loss condition is:
calculating the real-time standard line loss rate of the transformer area according to the real-time overall power data of the transformer area and the environmental state parameters to obtain the standard line loss rate;
performing line loss calculation according to real-time overall power data of the transformer area and real-time user power data to obtain an actual line loss rate;
and judging the power running condition of the station area according to the comparison of the actual line loss rate and the standard line loss rate.
In one embodiment, the standard line loss rate is calculated by:
acquiring voltage fluctuation data and load fluctuation data in the whole power data of the transformer area, and determining the power influence coefficient C of the voltage magnitude data, the fluctuation data, the load magnitude data and the fluctuation data on the line loss of the transformer area P ；
Acquiring temperature data and humidity data in environmental state parameters, and determining an environmental influence coefficient C of temperature and humidity on line loss of a platform area E ；
By the formula X P ＝X 0 *C P *C E Obtaining standard line loss rate X P ；
Wherein X is 0 The line loss rate under the standard environment and standard power data is preset.
In an embodiment, the power influence coefficient C P The acquisition process of (1) is as follows:
by the formulaCalculating to obtain electric power influence coefficient C P ；
Wherein v is L Is the current load value; v L0 Is a preset load standard value; f (F) L The load influence function is the line loss; v Li Load values acquired at specific intervals for a specific period of time before a current point in time; n is the obtained load value v Li Is the number of (3); f (F) w Is a line loss load stability function; alpha 1 、α 1 Is a preset coefficient.
In one embodiment, the environmental impact coefficient C E The acquisition process of (1) is as follows:
through formula C E ＝β 1 *F T (T)+β 2 *F H (H) Calculating to obtain environmental impact coefficient C E ；
Wherein T is an ambient temperature value; f (F) T Is a line loss temperature influence function; h is an environmental humidity value; f (F) H Is a line loss humidity influence function; beta 1 、β 2 Is a preset coefficient.
The invention has the beneficial effects that:
(1) According to the invention, the line loss condition of the platform area is analyzed in real time based on the whole power data of the platform area, the power consumption data of the user and the environmental state parameters through the edge computing equipment, and the power consumption abnormality of the user is judged according to the power consumption data of the user and the environmental state parameters, so that the power consumption safety condition of the user is accurately judged, and the out-of-tolerance condition of the line loss rate is accurately judged.
(2) The invention can correspondingly judge the standard line loss rate according to the actual condition of the electric power and the actual condition of the environment, and then the difference value condition of the actual line loss rate and the standard line loss rate can be adaptively judged by comparison, so that the line loss condition can be more accurately judged by comparison results, and the subsequent investigation and maintenance of the line loss problem are facilitated.
Drawings
The invention is further described below with reference to the accompanying drawings.
FIG. 1 is a schematic block diagram of a power edge based computing data processing system of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring now to FIG. 1, in one embodiment, a power edge based computing data processing system is provided, the system comprising:
the power data acquisition module is used for acquiring the whole power data of the platform area;
the user meter is used for collecting user electricity data of a single user;
the environment state monitoring module is used for monitoring environment state parameters of the station area;
the edge computing equipment is used for analyzing the line loss condition of the platform area in real time according to the whole power data of the platform area, the power consumption data of the user and the environmental state parameters, and judging the power consumption abnormality of the user according to the power consumption data of the user and the environmental state parameters.
Through the technical scheme, the whole power data of the platform area is acquired through the power data acquisition module, the user power consumption data of a single user is acquired through the user meter, meanwhile, the environment state monitoring module monitors the environment state parameters of the platform area, and further, the line loss condition of the platform area is analyzed in real time based on the whole power data of the platform area, the user power consumption data and the environment state parameters through the edge computing equipment, and the abnormal user power consumption is judged according to the user power consumption data and the environment state parameters, so that the power consumption safety condition of the user is accurately judged, and the out-of-tolerance condition of the line loss rate is accurately judged.
As one embodiment of the present invention, the process of determining the abnormal electricity consumption of the user includes:
acquiring a historical load curve F (t) of each user in a platform region and an average historical load curve of the platform region
By the formulaObtaining a load difference curve delta F (t) of a user;
obtaining a key value set { t for a user load difference curve Δf (t) by Δf' (t) =0 1 ，t 2 ，…，t n }；
Acquiring a period and environmental parameters corresponding to the key values, and forming a feature set { t } for each key value i ，ΔF(t i )，P i ，T i }；
Analyzing the characteristic value of each user to form an analysis model;
inputting the real-time characteristic set of the user into an analysis model, and judging the electricity utilization abnormality of the user;
wherein P is i At t i Time period T of i At t i Temperature value at the moment.
Through the above technical solution, this embodiment provides a process for determining abnormal electricity consumption of users, which includes first obtaining a historical load curve F (t) of each user in a platform and an average historical load curve of the platformThen through the formulaObtaining a load difference curve delta F (t) of a user; obtaining a key value set { t for a user load difference curve Δf (t) by Δf' (t) =0 1 ，t 2 ，…，t n -a }; acquiring a period and environmental parameters corresponding to the key values, and forming a feature set { t } for each key value i ，ΔF(t i )，P i ，T i -a }; obviously, the feature set corresponding to each key value can reflect the condition of the user load at the critical value, so that an analysis model is formed based on the feature sets, real-time feature set input of the user is judged according to the analysis model, and further the abnormality of the user can be accurately judged.
It should be noted that, the process of obtaining the analysis model in the above scheme may be completed based on machine training, or may be implemented through a data analysis modeling process, which is not limited herein.
As one embodiment of the present invention, the process of obtaining the analytical model is:
according to period P in the feature set i Fitting a reference load difference interval and a corresponding temperature interval to each preset time period;
combining the load difference intervals and the corresponding temperature intervals of all the time periods to generate an analysis model;
the process for judging the abnormal electricity consumption of the user according to the analysis model comprises the following steps:
t in real-time feature set according to user i Judging the period P i P in feature set i ，T i Respectively with period P i And comparing the corresponding reference load difference interval with the corresponding temperature interval, and judging whether the electricity consumption of the user is abnormal or not according to the comparison result.
With the foregoing technical solution, the present embodiment provides a method for acquiring an analysis model, specifically, according to a period P of feature concentration i Fitting a reference load difference interval and a corresponding temperature interval to each preset time period, wherein obviously, the reference load difference interval and the corresponding temperature interval can reflect the distribution condition of the level average level difference value of the users in the corresponding temperature interval and different time periods relative to the platform region, so that all the load difference intervals and the corresponding temperature intervals areThe load difference interval and the corresponding temperature interval of the time period are combined to generate an analysis model, judgment is carried out according to the analysis model, and then, t in the real-time characteristic set of the user is calculated i Judging the period P i P in feature set i ，T i Respectively with period P i The corresponding reference load difference value interval and the corresponding temperature interval are compared, and whether the electricity consumption of the user is abnormal or not is judged according to the comparison result, so that the abnormal electricity consumption condition of the user can be accurately judged.
As one implementation mode of the invention, the process of real-time analysis of the line loss condition is as follows:
calculating the real-time standard line loss rate of the transformer area according to the real-time overall power data of the transformer area and the environmental state parameters to obtain the standard line loss rate;
performing line loss calculation according to real-time overall power data of the transformer area and real-time user power data to obtain an actual line loss rate;
and judging the power running condition of the station area according to the comparison of the actual line loss rate and the standard line loss rate.
Through the technical scheme, the real-time standard line loss rate of the transformer area is calculated according to the real-time overall power data of the transformer area and the environmental state parameters, the standard line loss rate is obtained, the obtained actual line loss rate is compared with the standard line loss rate, the power operation condition of the transformer area is judged according to the comparison result, the standard line loss rate can be judged correspondingly according to the actual condition of the power and the actual condition of the environment through the mode, the difference value condition of the actual line loss rate and the standard line loss rate can be judged adaptively through the comparison, further the line loss condition can be judged more accurately through the comparison result, and the follow-up examination and overhaul of the line loss problem are facilitated.
As an embodiment of the present invention, the calculation process of the standard line loss rate is:
acquiring voltage fluctuation data and load fluctuation data in the whole power data of the transformer area, and determining the power influence coefficient C of the voltage magnitude data, the fluctuation data, the load magnitude data and the fluctuation data on the line loss of the transformer area P ；
Acquiring temperature data and humidity data in environmental state parameters, and determining an environmental influence coefficient C of temperature and humidity on line loss of a platform area E ；
By the formula X P ＝X 0 *C P *C E Obtaining standard line loss rate X P ；
Wherein X is 0 The line loss rate under the standard environment and standard power data is preset.
Through the above technical solution, the present embodiment provides a process for predicting and calculating a standard line loss rate, first, by acquiring voltage fluctuation data and load fluctuation data in overall power data of a transformer area, determining power influence coefficients C of the voltage magnitude data and the fluctuation data and the load magnitude data and the fluctuation data on the line loss of the transformer area P Acquiring temperature data and humidity data in the environmental state parameters, and determining an environmental influence coefficient C of temperature and humidity on the line loss of the platform area E The method comprises the steps of carrying out a first treatment on the surface of the By the formula X P ＝X 0 *C P *C E Obtaining standard line loss rate X P Wherein X is 0 Measured in advance according to the specific conditions of the station area, and thus by calculating the power influence coefficient C P Coefficient of environmental influence C E Furthermore, the influence of the power condition on the line loss and the influence of the environment condition on the line loss can be synthesized, the standard line loss rate can be obtained, and the abnormal condition of the line loss can be accurately judged through comparison between the actual line loss rate and the standard line loss rate.
As one embodiment of the present invention, the electric power influence coefficient C P The acquisition process of (1) is as follows:
by the formulaCalculating to obtain electric power influence coefficient C P ；
Wherein v is L Is the current load value; v L0 Is a preset load standard value; f (F) L The load influence function is the line loss; v Li Load values acquired at specific intervals for a specific period of time before a current point in time; n is the obtained load value v Li Is the number of (3); f (F) w Is a line loss load stability function; alpha 1 、α 1 Is a preset coefficient.
Through the above technical solution, the present embodiment provides an electric power influence coefficient C P Method of acquisition, wherein |v L -v L0 The i reflects the load deviation condition and,reflecting the load stability condition, F L As a line loss load influence function, F w Is a line loss load stability function, thus by the formula +.> Further, the power influence coefficient CP can be obtained.
The line loss load influence function F L Line loss load stability function F w Determining from empirical data; preset coefficient alpha 1 、α 1 The weight condition is selectively set according to the load deviation and the load stability, and will not be described in detail herein.
As one embodiment of the present invention, the environmental impact coefficient C E The acquisition process of (1) is as follows:
through formula C E ＝β 1 *F T (T)+β 2 *F H (H) Calculating to obtain environmental impact coefficient C E ；
Wherein T is an ambient temperature value; f (F) T Is a line loss temperature influence function; h is an environmental humidity value; f (F) H Is a line loss humidity influence function; beta 1 、β 2 Is a preset coefficient.
Through the above technical solution, the present embodiment provides an environmental impact coefficient C E The acquisition method is realized by a line loss temperature influence function F T Line loss humidity influence function F H Furthermore, the influence condition of the environmental factors on the line loss can be judged.
It should be noted thatLine loss temperature influence function F T Line loss humidity influence function F H Determining from empirical data; preset coefficient beta 1 、β 2 The weighting conditions are selectively set according to the influence of different environmental factors, and are not described in detail herein.
The foregoing describes one embodiment of the present invention in detail, but the description is only a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention. All equivalent changes and modifications within the scope of the present invention are intended to be covered by the present invention.
Claims (7)
1. A power edge-based computing data processing system, the system comprising:
the power data acquisition module is used for acquiring the whole power data of the platform area;
the user meter is used for collecting user electricity data of a single user;
the environment state monitoring module is used for monitoring environment state parameters of the station area;
the edge computing equipment is used for analyzing the line loss condition of the platform area in real time according to the whole power data of the platform area, the power consumption data of the user and the environmental state parameters, and judging the power consumption abnormality of the user according to the power consumption data of the user and the environmental state parameters.
2. The power edge based computing data processing system of claim 1, wherein the process of determining the user power consumption anomaly is:
acquiring a historical load curve F (t) of each user in a platform region and an average historical load curve of the platform region
By the formulaObtaining a load difference curve delta F (t) of a user;
obtaining a key value set { t for a user load difference curve Δf (t) by Δf' (t) =0 1 ，t 2 ，…，t n }；
Acquiring a period and environmental parameters corresponding to the key values, and forming a feature set { t } for each key value i ，ΔF(t i )，P i ，T i }；
Analyzing the characteristic value of each user to form an analysis model;
inputting the real-time characteristic set of the user into an analysis model, and judging the electricity utilization abnormality of the user;
wherein P is i At t i Time period T of i At t i Temperature value at the moment.
3. The power edge based computing data processing system of claim 2, wherein the process of analyzing model acquisition is:
according to period P in the feature set i Fitting a reference load difference interval and a corresponding temperature interval to each preset time period;
combining the load difference intervals and the corresponding temperature intervals of all the time periods to generate an analysis model;
the process for judging the abnormal electricity consumption of the user according to the analysis model comprises the following steps:
t in real-time feature set according to user i Judging the period P i P in feature set i ，T i Respectively with period P i And comparing the corresponding reference load difference interval with the corresponding temperature interval, and judging whether the electricity consumption of the user is abnormal or not according to the comparison result.
4. The power edge calculation based data processing system of claim 1, wherein the process of real-time analysis of line loss conditions is:
calculating the real-time standard line loss rate of the transformer area according to the real-time overall power data of the transformer area and the environmental state parameters to obtain the standard line loss rate;
performing line loss calculation according to real-time overall power data of the transformer area and real-time user power data to obtain an actual line loss rate;
and judging the power running condition of the station area according to the comparison of the actual line loss rate and the standard line loss rate.
5. The power edge based computing data processing system of claim 4, wherein the standard line loss rate is calculated by:
acquiring voltage fluctuation data and load fluctuation data in the whole power data of the transformer area, and determining the power influence coefficient C of the voltage magnitude data, the fluctuation data, the load magnitude data and the fluctuation data on the line loss of the transformer area P ；
Acquiring temperature data and humidity data in environmental state parameters, and determining an environmental influence coefficient C of temperature and humidity on line loss of a platform area E ；
By the formula X P ＝X 0 *C P *C E Obtaining standard line loss rate X P ；
Wherein X is 0 The line loss rate under the standard environment and standard power data is preset.
6. A power edge based computing data processing system as defined in claim 5, wherein the power influence coefficient C P The acquisition process of (1) is as follows:
by the formulaCalculating to obtain electric power influence coefficient C P ；
Wherein v is L Is the current load value; v L0 Is a preset load standard value; f (F) L The load influence function is the line loss; v Li Load values acquired at specific intervals for a specific period of time before a current point in time; n is the obtained load value v Li Is the number of (3); f (F) w Is a line loss load stability function; alpha 1 、α 1 Is a preset coefficient.
7. A power edge based computing data processing system as defined in claim 5, wherein said environmental impact coefficient C E The acquisition process of (1) is as follows:
through formula C E ＝β 1 *F T (T)+β 2 *F H (H) Calculating to obtain environmental impact coefficient C E ；
Wherein T is an ambient temperature value; f (F) T Is a line loss temperature influence function; h is an environmental humidity value; f (F) H Is a line loss humidity influence function; beta 1 、β 2 Is a preset coefficient.
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2023
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