CN112701787A - K-means algorithm-based automatic electric energy early warning device - Google Patents
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- 238000012545 processing Methods 0.000 claims description 9
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- 239000004973 liquid crystal related substance Substances 0.000 claims description 3
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- 238000007726 management method Methods 0.000 abstract description 9
- 238000012423 maintenance Methods 0.000 abstract description 8
- 238000012544 monitoring process Methods 0.000 abstract description 2
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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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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/23—Clustering techniques
- G06F18/232—Non-hierarchical techniques
- G06F18/2321—Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions
- G06F18/23213—Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions with fixed number of clusters, e.g. K-means clustering
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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
- H02J13/00006—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 information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment
- H02J13/00016—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 information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment using a wired telecommunication network or a data transmission bus
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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
- H02J13/00006—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 information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment
- H02J13/00022—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 information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment using wireless data transmission
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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
- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02B90/20—Smart grids as enabling technology in buildings sector
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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
- Y04S40/00—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them
- Y04S40/12—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them characterised by data transport means between the monitoring, controlling or managing units and monitored, controlled or operated electrical equipment
- Y04S40/124—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them characterised by data transport means between the monitoring, controlling or managing units and monitored, controlled or operated electrical equipment using wired telecommunication networks or data transmission busses
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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
- Y04S40/00—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them
- Y04S40/12—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them characterised by data transport means between the monitoring, controlling or managing units and monitored, controlled or operated electrical equipment
- Y04S40/126—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them characterised by data transport means between the monitoring, controlling or managing units and monitored, controlled or operated electrical equipment using wireless data transmission
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Abstract
The invention relates to the technical field of power monitoring. The cloud service terminal platform module is in wireless communication connection with a central control module through a wireless communication module, and the central control module is respectively and electrically connected with a display module, a clock synchronization module, a wired communication module, an electric quantity acquisition module, a data storage module, an early warning module and a power supply module; the central control module comprises a data cache unit, a K-means algorithm unit, a comparison identification unit, an early warning judgment unit and a control instruction output unit. According to the invention, the collected data is dynamically classified and judged, so that the accuracy of the early warning data is improved, a large amount of labor cost of operation and maintenance personnel is solved, and the operation and maintenance management level is improved.
Description
Technical Field
The invention relates to the technical field of power monitoring, in particular to an automatic electric energy early warning device based on a K-means algorithm.
Background
Along with the deepening of the innovation of the power system and the change of the current power utilization situation, the safe power utilization is more and more emphasized by people, and in the years, through the application of the electric energy acquisition device, the relevant management departments start to gradually realize the acquisition and early warning of electric energy data, gradually establish a safe power utilization management system and improve the automation level of the management system. However, the conventional power utilization management system adopted at present is too simple in early warning mode, generally adopts a threshold early warning mode, is too high in false alarm rate, and is not beneficial to operation and maintenance management. With the popularization and application of the data analysis technology, the early warning accuracy can be improved only by adopting a reasonable and effective data analysis method to analyze the abnormal electricity utilization condition in the user electricity utilization information, and the improvement of the operation and maintenance management level is facilitated.
Disclosure of Invention
The invention aims to provide an automatic electric energy early warning device based on a K-means algorithm, which improves the accuracy of early warning data by dynamically classifying and judging collected data, solves a large amount of labor cost of operation and maintenance personnel, and improves the operation and maintenance management level.
In order to achieve the purpose of the invention, the technical scheme adopted by the invention is as follows: an automatic electric energy early warning device based on a K-means algorithm comprises a cloud service terminal platform module, wherein the cloud service terminal platform module is in wireless communication connection with a central control module through a wireless communication module, and the central control module is respectively and electrically connected with a display module, a clock synchronization module, a wired communication module, an electric quantity acquisition module, a data storage module, an early warning module and a power supply module;
the central control module comprises a data cache unit, a K-means algorithm unit, a comparison identification unit, an early warning judgment unit and a control instruction output unit;
the data cache unit is used for receiving the electric quantity information data uploaded by the electric quantity acquisition module and sending the electric quantity information data to the K-means algorithm unit;
the K-means algorithm unit processes the electric quantity information data through a K-means algorithm and sends a processing result to the comparison and identification unit;
the comparison identification unit compares the processing result with the standard value proportion of the electric quantity data and sends the comparison data to the early warning judgment unit;
the early warning judgment unit carries out numerical judgment on the comparison data and sends the comparison result to the control instruction output unit;
and the control instruction output unit sends out a control instruction according to the comparison result and controls the output of the feedback signal.
Preferably, the K-means algorithm comprises the following steps:
A. a sample set X containing n samples X ═ X (X)1,x2,x3....xn) Preliminarily judging and dividing into k classification groups C ═ C1,c2,…,cn) Each group cannot be an empty set, and each sample data x can be divided into only one group;
B. randomly selecting k points as initial clustering centers M of k subgroups (M ═ M1,m2...,mk);
C. Sequentially calculating x to k cluster centers (m) of each sample by taking Euclidean distance as a similarity measure1,m2...,mk) The distance of (d);
D. assigning each sample x to the class in which the initial cluster center closest to it is located;
E. the average value of each cluster after reclassification is calculated by the formula (i), and the value is taken as a new cluster center mi;
Wherein K is the number of clustering center values; m is a cluster center value set; m is a specific value of the clustering center, xijThe specific value of the sample in the cluster is obtained; n is a radical ofiThe number of samples in the ith cluster;
F. calculating a criterion function J according to equation (ii);
G. repeating the steps C-F to carry out iterative processing, and outputting (m) if the J value is converged1,m2...,mk)。
Preferably, the clock synchronization module includes a GPS time synchronization unit, a network NTP time synchronization unit, and a master station time synchronization unit.
Preferably, the display module comprises a display screen and a human-computer interaction operation panel; the display screen is an LCD (liquid crystal display), and the human-computer interaction operation panel is a control key board.
Preferably, the wired communication module comprises an Ethernet interface, an RS-232 interface and an RS-485 interface.
The beneficial effects of the invention are concentrated and expressed as follows:
1. the invention utilizes the K-means clustering algorithm to classify the electricity consumption information to obtain the corresponding electricity consumption proportion, namely, the electricity data is smaller than the standard value proportion, the electricity data is equal to the standard value proportion, and the electricity data is larger than the standard value proportion.
2. The wireless communication module integrates the 4G/3G/2G wireless communication function, greatly improves the convenience and flexibility of equipment, and meets the requirements of collecting electric energy meters in some remote areas.
3. The data acquisition module can acquire 256 electronic electric energy meter electric quantity data, and the acquisition interval is independent of the storage interval and is independently set, so that the real-time performance of data acquisition is ensured.
4. The storage module adopts the time marks to respectively store each electric quantity data, the electric quantity data are circularly stored according to the first-in first-out principle, the data can be stored for 10 years after power failure, and the data storage format comprises a data error code, namely a data zone bit when an error occurs, so that the reason of the data error can be identified.
5. The invention has novel design, simple structure and convenient use, is beneficial to improving the early warning accuracy, improving the safe power utilization and reducing the operation and maintenance cost, and the K-means clustering algorithm has simple theory and is easy to realize.
Drawings
FIG. 1 is a block diagram of the overall architecture of the present invention;
FIG. 2 is a flow chart of the electric quantity data early warning and discrimination work of the central control module of the invention;
FIG. 3 is a process diagram of a K-means clustering algorithm;
FIG. 4 is a flow chart of the K-means clustering algorithm.
Detailed Description
With reference to fig. 1-4, the automatic electric energy early warning device based on the K-means algorithm includes a cloud service terminal platform module 1, the cloud service terminal platform module 1 and a central control module 6 form a wireless communication connection through a wireless communication module 2, specifically, various modes such as 4G/3G/2G can be adopted, and the cloud service terminal platform module 1 can be used as a management tool for operation and maintenance managers to remotely check data of the automatic electric energy early warning device.
The central control module 6 is a core bridge for realizing data transmission and exchange with other modules, and the central control module 6 is electrically connected with the display module 3, the clock synchronization module 4, the wired communication module 5, the electric quantity acquisition module 7, the data storage module 8, the early warning module 9 and the power supply module 10 respectively.
The display module 3 comprises a display screen, a human-computer interaction operation panel and the like, wherein the display screen is generally an LCD (liquid crystal display), the human-computer interaction operation panel is a control key board, and the setting can be realized by operating the control key board. Of course, the touch screen is directly adopted as the display module, the integrated display and control functions are also feasible, and the display module 3 is mainly used for local control parameter setting, such as IP setting, time setting, short message setting and data checking, such as working condition information checking, collected data checking, communication state checking and the like.
The clock synchronization module 4 comprises a GPS time synchronization unit, a network NTP time synchronization unit and a master station time synchronization unit, can realize various time synchronization modes such as GPS time synchronization, network NTP time synchronization, master station time synchronization and the like at the same time, and is used for supporting the electric quantity acquisition module 7 to measure the time-interval electric quantity. The wired communication module 5 is provided with a plurality of interfaces including an Ethernet interface, an RS-232 interface, an RS-485 interface and the like, can be simultaneously connected with 256 electronic energy meters, and has excellent compatibility. The electric quantity data that each electric energy meter was gathered can be collected to electric quantity collection module 7. The early warning module 9 is mainly connected with other module fault sensing devices to detect fault problems among the modules, and the power supply module 10 is used for supplying power to the invention and can adopt a switchable dual-power module. The data storage module 8 is used for storing information such as voltage, current, power and electric quantity acquired by the electric quantity acquisition module 7 and data information in modules such as the early warning module 9 and the power supply module 10.
As a core module of the invention, the central control module 6 of the invention comprises a data cache unit, a K-means algorithm unit, a comparison identification unit, an early warning judgment unit and a control instruction output unit; the data cache unit is used for receiving the electric quantity information data uploaded by the electric quantity acquisition module 7 and sending the electric quantity information data to the K-means algorithm unit; and the K-means algorithm unit processes the electric quantity information data through a K-means algorithm and sends a processing result to the comparison and identification unit.
The comparison identification unit compares the processing result with the standard value proportion of the electric quantity data and sends the comparison data to the early warning judgment unit; the comparison and identification unit compares the data to obtain three results, namely, the electric quantity data is smaller than the standard value proportion, the electric quantity data is equal to the standard value proportion, and the electric quantity data is larger than the standard value proportion, and sends the three results to the early warning judgment unit. The early warning judging unit is used for carrying out numerical judgment on the comparison data, judging whether early warning is needed or not and sending a comparison result to the control instruction output unit, and the control instruction output unit is used for sending a control instruction according to the comparison result and controlling feedback signals to be output. The output of the feedback signal may include normal power usage, outputting pre-alarm data.
The invention generally utilizes a K-means clustering algorithm to classify the electricity consumption information to obtain corresponding electricity consumption proportions, namely, the electricity data is smaller than a standard value proportion, the electricity data is equal to a standard value proportion, and the electricity data is larger than the standard value proportion. The K-means algorithm comprises the following steps:
A. a sample set X containing n samples X ═ X (X)1,x2,x3....xn) Preliminarily judging and dividing into k classification groups C ═ C1,c2,…,cn) Each group cannot be an empty set, and each sample data x can be divided into only one group;
B. randomly selecting k points as initial clustering centers M of k subgroups (M ═ M1,m2...,mk);
C. Sequentially calculating x to k cluster centers (m) of each sample by taking Euclidean distance as a similarity measure1,m2...,mk) The distance of (d);
D. assigning each sample x to the class in which the initial cluster center closest to it is located;
E. the average value of each cluster after reclassification is calculated by the formula (i), and the value is taken as a new cluster center mi;
Wherein K is the number of clustering center values; m is a cluster center value set; m is a specific value of the clustering center, xijThe specific value of the sample in the cluster is obtained; n is a radical ofiThe number of samples in the ith cluster;
F. calculating a criterion function J according to equation (ii);
G. repeating the steps C-F to carry out iterative processing, and outputting (m) if the J value is converged1,m2...,mk)。
Claims (5)
1. An automatic electric energy early warning device based on a K-means algorithm is characterized in that: the cloud service terminal platform module is in wireless communication connection with a central control module through a wireless communication module, and the central control module is electrically connected with a display module, a clock synchronization module, a wired communication module, an electric quantity acquisition module, a data storage module, an early warning module and a power supply module respectively;
the central control module comprises a data cache unit, a K-means algorithm unit, a comparison identification unit, an early warning judgment unit and a control instruction output unit;
the data cache unit is used for receiving the electric quantity information data uploaded by the electric quantity acquisition module and sending the electric quantity information data to the K-means algorithm unit;
the K-means algorithm unit processes the electric quantity information data through a K-means algorithm and sends a processing result to the comparison and identification unit;
the comparison identification unit compares the processing result with the standard value proportion of the electric quantity data and sends the comparison data to the early warning judgment unit;
the early warning judgment unit carries out numerical judgment on the comparison data and sends the comparison result to the control instruction output unit;
and the control instruction output unit sends out a control instruction according to the comparison result and controls the output of the feedback signal.
2. The automatic electric energy early warning device based on the K-means algorithm as claimed in claim 1, wherein: the K-means algorithm comprises the following steps:
A. a sample set X containing n samples X ═ X (X)1,x2,x3....xn) Preliminarily judging and dividing into k classification groups C ═ C1,c2,…,cn) Each group cannot be an empty set, and each sample data x can be divided into only one group;
B. randomly selecting k points as initial clustering centers M of k subgroups (M ═ M1,m2...,mk);
C. Sequentially calculating x to k cluster centers (m) of each sample by taking Euclidean distance as a similarity measure1,m2...,mk) The distance of (d);
D. assigning each sample x to the class in which the initial cluster center closest to it is located;
E. the average value of each cluster after reclassification is calculated by the formula (i), and the value is taken as a new cluster center mi;
Wherein K is the number of clustering center values; m is a cluster center value set; m is a specific value of the clustering center, xijThe specific value of the sample in the cluster is obtained; n is a radical ofiThe number of samples in the ith cluster;
F. calculating a criterion function J according to equation (ii);
G. repeating the steps C-F to carry out iterative processing, and outputting (m) if the J value is converged1,m2...,mk)。
3. The automatic electric energy early warning device based on the K-means algorithm as claimed in claim 2, wherein: the clock synchronization module comprises a GPS time synchronization unit, a network NTP time synchronization unit and a master station time synchronization unit.
4. The automatic electric energy early warning device based on the K-means algorithm as claimed in claim 3, wherein: the display module comprises a display screen and a human-computer interaction operation panel; the display screen is an LCD (liquid crystal display), and the human-computer interaction operation panel is a control key board.
5. The automatic electric energy early warning device based on the K-means algorithm as claimed in claim 4, wherein: the wired communication module comprises an Ethernet interface, an RS-232 interface and an RS-485 interface.
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CN108336725A (en) * | 2016-12-16 | 2018-07-27 | 泰豪软件股份有限公司 | The management of dispatching of power netwoks monitoring of tools and intelligent analysis system |
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