CN116247819A - System and method for monitoring line loss of transformer area based on big data - Google Patents
System and method for monitoring line loss of transformer area based on big data Download PDFInfo
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- CN116247819A CN116247819A CN202310157959.5A CN202310157959A CN116247819A CN 116247819 A CN116247819 A CN 116247819A CN 202310157959 A CN202310157959 A CN 202310157959A CN 116247819 A CN116247819 A CN 116247819A
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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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- 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
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
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Abstract
The invention discloses a system and a method for monitoring line loss of a transformer area based on big data, which relate to the technical field of electric power safety and comprise a data acquisition module, an electricity stealing evaluation module and an operation and maintenance management module; the data acquisition module is used for acquiring electric energy data and line loss data of each station area; the electricity stealing assessment module is used for carrying out electricity stealing assessment according to the electric energy data and the line loss data of each area, judging whether the electricity stealing phenomenon exists in each area or not, and reminding an administrator of overhauling and maintaining the areas; when receiving the electricity larceny early warning signal, the cloud server is also used for generating an electricity larceny maintenance task to the operation and maintenance management module; the operation and maintenance management module is used for analyzing the overhaul coefficient of the electricity stealing overhaul task to obtain a priority processing table of the electricity stealing overhaul task, and distributing corresponding power maintenance personnel for the electricity stealing overhaul task according to the priority processing table; resources are reasonably allocated, a basis is provided for scheduling the power grid mode, and the maintenance efficiency of the transformer area is improved.
Description
Technical Field
The invention relates to the technical field of electric power safety, in particular to a system and a method for monitoring line loss of a transformer area based on big data.
Background
Line loss is an abbreviation for active power loss generated in the power network transmission process. The electric energy is transmitted from the power generation enterprise to the power client through each power transmission and transformation element, and in the transmission process, the electric energy loss caused by factors such as electric quantity leakage of the power equipment, metering error of the metering equipment and management is conventionally called as line loss. The line loss abnormality handling management relates to the aspects of marketing metering collection, anti-electricity stealing, business management, power distribution network planning design, operation management and the like, and comprehensively embodies the management level of power grid enterprises on the platform region equipment and users.
For a long time, aiming at a 'transformer area' with abnormal line loss, electric power staff often need to analyze the reasons of the abnormality in time, formulate loss reduction measures and arrange on-site disposal. The existing transformer area line loss monitoring system cannot intelligently identify the transformer area with high monitoring grade, reasonably arrange monitoring resources and improve monitoring efficiency; and the corresponding maintenance loss reduction strategy cannot be formulated according to the maintenance coefficient, so that a basis is provided for scheduling the power grid mode, the maintenance efficiency is improved, and the potential electric hazards are eliminated; based on the defects, the invention provides a system and a method for monitoring the line loss of a platform area based on big data.
Disclosure of Invention
The present invention aims to solve at least one of the technical problems existing in the prior art. Therefore, the invention provides a system and a method for monitoring the line loss of a platform area based on big data.
In order to achieve the above objective, an embodiment according to a first aspect of the present invention provides a system for monitoring line loss of a transformer area based on big data, which includes a data acquisition module, an electricity larceny evaluation module, an operation and maintenance management module, an operation and maintenance tracking module, and a level evaluation module;
the data acquisition module is used for acquiring the electric energy data and the line loss data of each area and transmitting the acquired electric energy data and line loss data to the cloud server for caching;
the electricity stealing assessment module is used for acquiring the electric energy data and the line loss data of each platform area cached in the cloud server to carry out electricity stealing assessment, and calculating to obtain an electricity stealing assessment index Cs; judging whether each station area has electricity stealing phenomenon or not so as to remind an administrator to overhaul and maintain the station area;
when receiving the electricity larceny early warning signal, the cloud server is also used for generating an electricity larceny maintenance task to the operation and maintenance management module; the operation and maintenance management module is used for carrying out maintenance coefficient WX analysis on the electricity stealing maintenance task to obtain a priority processing table of the electricity stealing maintenance task; sequentially distributing electricity stealing maintenance tasks to corresponding power maintenance personnel according to the priority processing table;
the operation and maintenance tracking module is used for carrying out electricity stealing operation and maintenance tracking on each platform area; when the fact that each platform area is overhauled due to electricity stealing is monitored, electricity stealing overhauling information is recorded, and the electricity stealing overhauling information is transmitted to a cloud platform for storage by stamping a time stamp; the grade evaluation module is used for performing monitoring grade evaluation according to electricity stealing overhaul information with a time stamp stored in the cloud platform, and obtaining the monitoring grade of each platform region.
Further, the specific evaluation steps of the electricity larceny evaluation module are as follows:
acquiring electric energy data and line loss data of each station area, and marking the electric energy data and the line loss data as DSi and XSi respectively; the electric energy data is the difference value of the power supply quantity and the sales quantity; calculating to obtain a power loss value QPI by using a formula QPI=A1× (DS-XS), wherein alpha 1 is a preset proportionality coefficient, and i represents an ith station area;
establishing a graph of the change of the electric loss value QPI along with time; comparing the electrical loss value QPI with a preset loss threshold value; if the QPI is more than or equal to a preset loss threshold value, intercepting and marking a corresponding curve segment in a corresponding curve graph, and marking the curve segment as a loss curve segment;
in a preset time period, counting the number of loss curve segments to be C1; integrating all loss curve segments with time to obtain a loss reference area M1; calculating to obtain a power theft evaluation index Cs of the platform area by using a formula Cs=C1×a1+M1×a2, wherein a1 and a2 are coefficient factors;
comparing the electricity larceny evaluation index Cs with a preset evaluation threshold; if Cs is larger than a preset evaluation threshold, judging that the electricity larceny phenomenon exists in the station area, and generating an electricity larceny early warning signal.
Further, the specific analysis steps of the operation and maintenance management module are as follows:
acquiring the release time of an electricity stealing maintenance task, and calculating the time difference between the release time and the current time of the system to obtain release time FT1; acquiring a platform area corresponding to an electricity stealing maintenance task, and automatically calling a monitoring grade DT of the platform area from the cloud platform;
acquiring potential power supply related data of the station area, and calculating to obtain a power supply coefficient GD of the station area; calculating an overhaul coefficient WX of the electricity stealing overhaul task by using a formula WX=F1×b1+DT×b2+GDXb3, wherein b1, b2 and b3 are coefficient factors; and sequencing the electricity stealing overhaul tasks according to the size of the overhaul coefficient WX to obtain a priority processing table of the electricity stealing overhaul tasks.
Further, the specific evaluation steps of the grade evaluation module are as follows:
acquiring all electricity stealing overhaul information of a platform region within a preset time period according to the platform region identification;
counting the total times of electricity stealing and maintenance of the station area as Z1; marking the overhaul duration of each piece of electricity stealing overhaul information as GTi and the overhaul grade as GDi; the maintenance value JXi is calculated by using a formula JXi =GTi×g1+GDi×g2, wherein g1 and g2 are coefficient factors;
comparing the service value JXi with a preset service threshold; counting the times of JXi which are larger than a preset overhaul threshold value as Zb1; when JXi is greater than the preset maintenance, obtaining a difference value between JXi and a preset maintenance threshold value and summing to obtain a total superpositioning value CH; the super-detection attraction coefficient CX is calculated by using a formula CX=Zb1×g3+CH×g4, wherein g3 and g4 are coefficient factors;
calculating to obtain a power theft protection coefficient LF of the platform area by using a formula LF=C1×g5+CXXg6, wherein g5 and g6 are coefficient factors;
determining that the monitoring grade of the platform area is DT according to the electricity larceny protection coefficient LF, specifically: a mapping relation table of the electricity larceny protection coefficient range and the monitoring level is stored in the database; the grade evaluation module is used for stamping the monitoring grade DT of the platform area with a time stamp and storing the time stamp to the cloud platform.
Further, the specific calculation method of the power supply coefficient GD is as follows:
the potential power supply related data comprise the length of a power transmission line, the number of power supplies in a power supply area and the average power consumption of a user; marking the length of a corresponding power transmission line as Ls, and sequentially marking the number of power supplies and the average power consumption of a user in a corresponding power supply area as Hs and Ds; and calculating the power supply coefficient GD of the station region by using a formula GD=ls×b6+Hs×b4+Ds×b5, wherein b4, b5 and b6 are coefficient factors.
Further, the electricity stealing overhaul information comprises a platform area identifier, overhaul duration and corresponding overhaul grades, and the overhaul grades are uploaded to the cloud platform after being overhauled by power maintenance personnel.
Further, the electricity larceny assessment module is used for sending an electricity larceny early warning signal to a cloud server; and the cloud server drives the control alarm module to send out an alarm after receiving the electricity stealing early warning signal.
Further, the method for monitoring the line loss of the platform area based on big data comprises the following steps:
step one: the data acquisition module acquires the electric energy data and the line loss data of each area and transmits the acquired electric energy data and line loss data to the cloud server for caching;
step two: the power stealing evaluation module is used for acquiring power data and line loss data of each platform area cached in the cloud server to perform power stealing evaluation, and a power loss value QPI is obtained through calculation;
evaluating the electricity stealing evaluation index Cs according to the space-time variation condition of the electricity loss value QPI; if Cs is greater than a preset evaluation threshold, judging that the electricity larceny phenomenon exists in the station area, and generating an electricity larceny early warning signal;
step three: when receiving the electricity larceny early warning signal, the cloud server is used for generating an electricity larceny maintenance task to the operation and maintenance management module; the operation and maintenance management module is used for carrying out maintenance coefficient WX analysis on the electricity stealing maintenance task to obtain a priority processing table of the electricity stealing maintenance task;
step four: the operation and maintenance management module is used for distributing corresponding power maintenance personnel for the electricity stealing maintenance tasks in sequence according to the priority processing table; after the overhaul is completed, the electricity stealing overhaul information is recorded to the cloud platform through the operation and maintenance tracking module;
step five: monitoring and grading evaluation is carried out on electricity stealing overhaul information with a time stamp stored in the cloud platform by using a grading evaluation module; and calculating to obtain the electricity stealing protection coefficient LF of the platform area, and determining the monitoring grade of the platform area according to the electricity stealing protection coefficient LF.
Compared with the prior art, the invention has the beneficial effects that:
1. the data acquisition module is used for acquiring the electric energy data and the line loss data of each station area; the electricity stealing evaluation module is used for carrying out electricity stealing evaluation on the electric energy data and the line loss data of each area and establishing a graph of the change of the electric loss value QPI along with time; calculating to obtain a power stealing evaluation index Cs of the platform region according to the space-time transformation condition of the power loss value QPI, if Cs is larger than a preset evaluation threshold, judging that the platform region has a power stealing phenomenon, and generating a power stealing early warning signal to remind an administrator to overhaul and maintain the platform region; the electric power safety is improved;
2. when receiving the electricity larceny early warning signal, the cloud server is also used for generating an electricity larceny maintenance task to the operation and maintenance management module; the operation and maintenance management module is used for analyzing the overhaul coefficients of the electricity stealing overhaul tasks, sequencing the electricity stealing overhaul tasks according to the overhaul coefficients WX, and obtaining a priority processing table of the electricity stealing overhaul tasks; resources are reasonably allocated, and the maintenance efficiency of the platform area is improved; after the overhaul is completed, the electricity stealing overhaul information is recorded to the cloud platform through the operation and maintenance tracking module; the grade evaluation module is used for performing monitoring grade evaluation on electricity stealing maintenance information with a time stamp stored in the cloud platform, calculating an electricity stealing protection coefficient LF of the platform region, determining the monitoring grade of the platform region according to the electricity stealing protection coefficient LF, and providing a basis for scheduling a power grid mode, so that maintenance efficiency is improved, and potential electric hazards are eliminated.
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In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a system block diagram of a system for monitoring line loss of a platform area based on big data.
Fig. 2 is a schematic block diagram of a method for monitoring line loss of a station area based on big data in the present invention.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present invention, 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.
As shown in fig. 1 to 2, a system for monitoring line loss of a platform area based on big data comprises a data acquisition module, a cloud server, an electricity larceny evaluation module, an alarm module, an operation and maintenance management module, an operation and maintenance tracking module, a cloud platform and a grade evaluation module;
the data acquisition module is used for acquiring the electric energy data and the line loss data of each area and transmitting the acquired electric energy data and line loss data to the cloud server for caching; the electric energy data is the difference value of the power supply quantity and the sales quantity;
the electricity stealing assessment module is used for acquiring the electric energy data and the line loss data of each platform area cached in the cloud server to carry out electricity stealing assessment and judging whether the electricity stealing phenomenon exists in each platform area; the specific evaluation steps are as follows:
acquiring electric energy data and line loss data of each station area, and marking the electric energy data and the line loss data as DSi and XSi respectively;
calculating to obtain a power loss value QPI by using a formula QPI=A1× (DS-XS), wherein alpha 1 is a preset proportionality coefficient, and i represents an ith station area; establishing a graph of the change of the electric loss value QPI along with time;
comparing the electrical loss value QPI with a preset loss threshold value; if the QPI is more than or equal to a preset loss threshold value, intercepting and marking a corresponding curve segment in a corresponding curve graph, and marking the curve segment as a loss curve segment;
in a preset time period, counting the number of loss curve segments to be C1; integrating all loss curve segments with time to obtain a loss reference area M1; calculating to obtain a power theft evaluation index Cs of the platform area by using a formula Cs=C1×a1+M1×a2, wherein a1 and a2 are coefficient factors;
comparing the electricity larceny evaluation index Cs with a preset evaluation threshold; if Cs is greater than a preset evaluation threshold, judging that the electricity larceny phenomenon exists in the station area, and generating an electricity larceny early warning signal;
the electricity larceny evaluation module is used for sending an electricity larceny early warning signal to the cloud server; the cloud server drives the control alarm module to send out an alarm after receiving the electricity stealing early warning signal so as to remind an administrator of overhauling and maintaining the platform area;
when receiving the electricity larceny early warning signal, the cloud server is also used for generating an electricity larceny maintenance task to the operation and maintenance management module; the operation and maintenance management module is used for analyzing the overhaul coefficients of the electricity stealing overhaul task to obtain a priority processing table of the electricity stealing overhaul task; the maintenance efficiency of the platform area is improved;
the specific analysis steps of the operation and maintenance management module are as follows:
acquiring the release time of an electricity stealing maintenance task, and calculating the time difference between the release time and the current time of the system to obtain release time FT1; acquiring a platform area corresponding to an electricity stealing maintenance task, and automatically calling a monitoring grade DT of the platform area from the cloud platform;
acquiring potential power supply related data of the station area, wherein the potential power supply related data comprises the length of a power transmission line, the number of power supplies in a power supply area and the average power consumption of users;
marking the length of a corresponding power transmission line as Ls, and sequentially marking the number of power supplies and the average power consumption of a user in a corresponding power supply area as Hs and Ds; calculating to obtain a power supply coefficient GD of the station area by using a formula GD=ls×b6+Hs×b4+Ds×b5, wherein b4, b5 and b6 are coefficient factors;
normalizing the release time length, the monitoring grade and the power supply coefficient and taking the numerical value; calculating an overhaul coefficient WX of the electricity stealing overhaul task by using a formula WX=F1×b1+DT×b2+GDXb3, wherein b1, b2 and b3 are coefficient factors;
sequencing the electricity stealing overhaul tasks according to the size of the overhaul coefficient WX to obtain a priority processing table of the electricity stealing overhaul tasks; the operation and maintenance management module is used for distributing corresponding power maintenance personnel for the electricity stealing maintenance tasks in sequence according to the priority processing table, reasonably distributing resources and improving the maintenance efficiency of the transformer area;
the operation and maintenance tracking module is used for tracking electricity stealing operation and maintenance of each platform region, recording electricity stealing overhaul information when the fact that each platform region is overhauled due to electricity stealing is monitored, and transmitting the electricity stealing overhaul information to the cloud platform for real-time storage by stamping a time stamp; the power stealing overhaul information comprises a platform area identifier, overhaul duration and corresponding overhaul grades, wherein the overhaul grades are uploaded to the cloud platform after being overhauled by power maintainers, and the higher the overhaul grade is, the more serious the power stealing problem is indicated;
the grade evaluation module is connected with the cloud platform and is used for performing monitoring grade evaluation according to electricity stealing overhaul information with a time stamp stored in the cloud platform, and the specific evaluation steps are as follows:
acquiring all electricity stealing overhaul information of a platform region within a preset time period according to the platform region identification;
counting the total times of electricity stealing and maintenance of the station area as Z1; marking the overhaul duration of each piece of electricity stealing overhaul information as GTi and the overhaul grade as GDi; the maintenance value JXi is calculated by using a formula JXi =GTi×g1+GDi×g2, wherein g1 and g2 are coefficient factors;
comparing the service value JXi with a preset service threshold; counting the times of JXi which are larger than a preset overhaul threshold value as Zb1; when JXi is greater than the preset maintenance, obtaining a difference value between JXi and a preset maintenance threshold value and summing to obtain a total superpositioning value CH; the super-detection attraction coefficient CX is calculated by using a formula CX=Zb1×g3+CH×g4, wherein g3 and g4 are coefficient factors;
normalizing the total times of electricity stealing and maintenance and the over-detection attraction coefficient and taking the numerical value; calculating to obtain a power theft protection coefficient LF of the platform area by using a formula LF=C1×g5+CXXg6, wherein g5 and g6 are coefficient factors;
determining a monitoring grade of a platform area according to the electricity larceny protection coefficient LF, wherein the monitoring grade is specifically as follows:
a mapping relation table of the electricity larceny protection coefficient range and the monitoring level is stored in the database;
determining a corresponding electricity stealing protection coefficient range according to the electricity stealing protection coefficient LF, and determining a corresponding monitoring grade as DT according to the electricity stealing protection coefficient range; the grade evaluation module is used for stamping the monitoring grade DT of the platform area with a time stamp and storing the time stamp to the cloud platform.
A method for monitoring the line loss of a station area based on big data comprises the following steps:
step one: the data acquisition module acquires the electric energy data and the line loss data of each area and transmits the acquired electric energy data and line loss data to the cloud server for caching;
step two: the power stealing evaluation module is used for acquiring power data and line loss data of each platform area cached in the cloud server to perform power stealing evaluation, and a power loss value QPI is obtained through calculation;
evaluating the electricity stealing evaluation index Cs according to the space-time variation condition of the electricity loss value QPI; if Cs is greater than a preset evaluation threshold, judging that the electricity larceny phenomenon exists in the station area, and generating an electricity larceny early warning signal;
step three: when receiving the electricity larceny early warning signal, the cloud server is used for generating an electricity larceny maintenance task to the operation and maintenance management module; the operation and maintenance management module is used for carrying out maintenance coefficient WX analysis on the electricity stealing maintenance task to obtain a priority processing table of the electricity stealing maintenance task;
step four: the operation and maintenance management module is used for distributing corresponding power maintenance personnel for the electricity stealing maintenance tasks in sequence according to the priority processing table; after the overhaul is completed, the electricity stealing overhaul information is recorded to the cloud platform through the operation and maintenance tracking module;
step five: monitoring and grading evaluation is carried out on electricity larceny maintenance information with a time stamp stored in a cloud platform by using a grade evaluation module, and an electricity larceny protection coefficient LF of the platform area is obtained through calculation; and determining and obtaining the monitoring grade of the platform area according to the electricity larceny protection coefficient LF.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas which are obtained by acquiring a large amount of data and performing software simulation to obtain the closest actual situation, and preset parameters and preset thresholds in the formulas are set by a person skilled in the art according to the actual situation or are obtained by simulating a large amount of data.
The working principle of the invention is as follows:
the system and the method for monitoring the line loss of the transformer areas based on big data are characterized in that a data acquisition module is used for acquiring electric energy data and line loss data of each transformer area when the system and the method are in operation; the electricity stealing evaluation module is used for carrying out electricity stealing evaluation on the electric energy data and the line loss data of each area and establishing a graph of the change of the electric loss value QPI along with time; calculating to obtain a power stealing evaluation index Cs of the platform region according to the space-time transformation condition of the power loss value QPI, if Cs is larger than a preset evaluation threshold, judging that the platform region has a power stealing phenomenon, and generating a power stealing early warning signal to remind an administrator to overhaul and maintain the platform region; the electric power safety is improved;
when receiving the electricity larceny early warning signal, the cloud server is also used for generating an electricity larceny maintenance task to the operation and maintenance management module; the operation and maintenance management module is used for analyzing the overhaul coefficients of the electricity stealing overhaul tasks, sequencing the electricity stealing overhaul tasks according to the overhaul coefficients WX, and obtaining a priority processing table of the electricity stealing overhaul tasks; resources are reasonably allocated, and the maintenance efficiency of the platform area is improved; after the overhaul is completed, the electricity stealing overhaul information is recorded to the cloud platform through the operation and maintenance tracking module; the grade evaluation module is used for performing monitoring grade evaluation on electricity stealing maintenance information with a time stamp stored in the cloud platform, calculating an electricity stealing protection coefficient LF of the platform region, determining the monitoring grade of the platform region according to the electricity stealing protection coefficient LF, and providing a basis for scheduling a power grid mode, so that maintenance efficiency is improved, and potential electric hazards are eliminated.
In the description of the present specification, the descriptions of the terms "one embodiment," "example," "specific example," and the like, mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
Claims (8)
1. The system is characterized by comprising a data acquisition module, an electricity stealing evaluation module, an operation and maintenance management module, an operation and maintenance tracking module and a grade evaluation module;
the data acquisition module is used for acquiring the electric energy data and the line loss data of each area and transmitting the acquired electric energy data and line loss data to the cloud server for caching;
the electricity stealing assessment module is used for acquiring the electric energy data and the line loss data of each platform area cached in the cloud server to carry out electricity stealing assessment, and calculating to obtain an electricity stealing assessment index Cs; judging whether each station area has electricity stealing phenomenon or not so as to remind an administrator to overhaul and maintain the station area;
when receiving the electricity larceny early warning signal, the cloud server is also used for generating an electricity larceny maintenance task to the operation and maintenance management module; the operation and maintenance management module is used for carrying out maintenance coefficient WX analysis on the electricity stealing maintenance task to obtain a priority processing table of the electricity stealing maintenance task; sequentially distributing electricity stealing maintenance tasks to corresponding power maintenance personnel according to the priority processing table;
the operation and maintenance tracking module is used for carrying out electricity stealing operation and maintenance tracking on each platform area; when the fact that each platform area is overhauled due to electricity stealing is monitored, electricity stealing overhauling information is recorded, and the electricity stealing overhauling information is transmitted to a cloud platform for storage by stamping a time stamp; the grade evaluation module is used for performing monitoring grade evaluation according to electricity stealing overhaul information with a time stamp stored in the cloud platform, and obtaining the monitoring grade of each platform region.
2. The system for monitoring the line loss of the transformer area based on big data according to claim 1, wherein the specific evaluation steps of the electricity larceny evaluation module are as follows:
acquiring electric energy data and line loss data of each station area, and marking the electric energy data and the line loss data as DSi and XSi respectively; the electric energy data is the difference value of the power supply quantity and the sales quantity; calculating to obtain a power loss value QPI by using a formula QPI=A1× (DS-XS), wherein alpha 1 is a preset proportionality coefficient, and i represents an ith station area;
establishing a graph of the change of the electric loss value QPI along with time; comparing the electrical loss value QPI with a preset loss threshold value; if the QPI is more than or equal to a preset loss threshold value, intercepting and marking a corresponding curve segment in a corresponding curve graph, and marking the curve segment as a loss curve segment;
in a preset time period, counting the number of loss curve segments to be C1; integrating all loss curve segments with time to obtain a loss reference area M1; calculating to obtain a power theft evaluation index Cs of the platform area by using a formula Cs=C1×a1+M1×a2, wherein a1 and a2 are coefficient factors;
comparing the electricity larceny evaluation index Cs with a preset evaluation threshold; if Cs is larger than a preset evaluation threshold, judging that the electricity larceny phenomenon exists in the station area, and generating an electricity larceny early warning signal.
3. The system for monitoring the line loss of the transformer area based on big data according to claim 2, wherein the specific analysis steps of the operation and maintenance management module are as follows:
acquiring the release time of an electricity stealing maintenance task, and calculating the time difference between the release time and the current time of the system to obtain release time FT1; acquiring a platform area corresponding to an electricity stealing maintenance task, and automatically calling a monitoring grade DT of the platform area from the cloud platform;
acquiring potential power supply related data of the station area, and calculating to obtain a power supply coefficient GD of the station area; calculating an overhaul coefficient WX of the electricity stealing overhaul task by using a formula WX=F1×b1+DT×b2+GDXb3, wherein b1, b2 and b3 are coefficient factors; and sequencing the electricity stealing overhaul tasks according to the size of the overhaul coefficient WX to obtain a priority processing table of the electricity stealing overhaul tasks.
4. The system for monitoring line loss of a transformer area based on big data according to claim 3, wherein the specific evaluation steps of the level evaluation module are as follows:
acquiring all electricity stealing overhaul information of a platform region within a preset time period according to the platform region identification;
counting the total times of electricity stealing and maintenance of the station area as Z1; marking the overhaul duration of each piece of electricity stealing overhaul information as GTi and the overhaul grade as GDi; the maintenance value JXi is calculated by using a formula JXi =GTi×g1+GDi×g2, wherein g1 and g2 are coefficient factors;
comparing the service value JXi with a preset service threshold; counting the times of JXi which are larger than a preset overhaul threshold value as Zb1; when JXi is greater than the preset maintenance, obtaining a difference value between JXi and a preset maintenance threshold value and summing to obtain a total superpositioning value CH; the super-detection attraction coefficient CX is calculated by using a formula CX=Zb1×g3+CH×g4, wherein g3 and g4 are coefficient factors;
calculating to obtain a power theft protection coefficient LF of the platform area by using a formula LF=C1×g5+CXXg6, wherein g5 and g6 are coefficient factors;
determining that the monitoring grade of the platform area is DT according to the electricity larceny protection coefficient LF, specifically: a mapping relation table of the electricity larceny protection coefficient range and the monitoring level is stored in the database; the grade evaluation module is used for stamping the monitoring grade DT of the platform area with a time stamp and storing the time stamp to the cloud platform.
5. The system for monitoring the line loss of the transformer area based on big data as set forth in claim 3, wherein the specific calculation method of the power supply coefficient GD is as follows:
the potential power supply related data comprise the length of a power transmission line, the number of power supplies in a power supply area and the average power consumption of a user; marking the length of a corresponding power transmission line as Ls, and sequentially marking the number of power supplies and the average power consumption of a user in a corresponding power supply area as Hs and Ds; and calculating the power supply coefficient GD of the station region by using a formula GD=ls×b6+Hs×b4+Ds×b5, wherein b4, b5 and b6 are coefficient factors.
6. The system for monitoring the line loss of the transformer area based on big data according to claim 4, wherein the electricity-stealing overhaul information comprises a transformer area identifier, overhaul duration and corresponding overhaul grades, and the overhaul grades are uploaded to the cloud platform after being overhauled by power maintenance personnel.
7. The system for monitoring the line loss of the transformer area based on big data according to claim 2, wherein the electricity larceny assessment module is used for sending an electricity larceny early warning signal to a cloud server; and the cloud server drives the control alarm module to send out an alarm after receiving the electricity stealing early warning signal.
8. The method for monitoring the line loss of the transformer area based on the big data is applied to the system for monitoring the line loss of the transformer area based on the big data as set forth in any one of claims 1 to 7, and is characterized by comprising the following steps:
step one: the data acquisition module acquires the electric energy data and the line loss data of each area and transmits the acquired electric energy data and line loss data to the cloud server for caching;
step two: the power stealing evaluation module is used for acquiring power data and line loss data of each platform area cached in the cloud server to perform power stealing evaluation, and a power loss value QPI is obtained through calculation;
evaluating the electricity stealing evaluation index Cs according to the space-time variation condition of the electricity loss value QPI; if Cs is greater than a preset evaluation threshold, judging that the electricity larceny phenomenon exists in the station area, and generating an electricity larceny early warning signal;
step three: when receiving the electricity larceny early warning signal, the cloud server is used for generating an electricity larceny maintenance task to the operation and maintenance management module; the operation and maintenance management module is used for carrying out maintenance coefficient WX analysis on the electricity stealing maintenance task to obtain a priority processing table of the electricity stealing maintenance task;
step four: the operation and maintenance management module is used for distributing corresponding power maintenance personnel for the electricity stealing maintenance tasks in sequence according to the priority processing table; after the overhaul is completed, the electricity stealing overhaul information is recorded to the cloud platform through the operation and maintenance tracking module;
step five: monitoring and grading evaluation is carried out on electricity stealing overhaul information with a time stamp stored in the cloud platform by using a grading evaluation module; and calculating to obtain the electricity stealing protection coefficient LF of the platform area, and determining the monitoring grade of the platform area according to the electricity stealing protection coefficient LF.
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