CN114123510B - Transformer monitoring method and system based on real-time data analysis - Google Patents

Transformer monitoring method and system based on real-time data analysis Download PDF

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CN114123510B
CN114123510B CN202111425559.5A CN202111425559A CN114123510B CN 114123510 B CN114123510 B CN 114123510B CN 202111425559 A CN202111425559 A CN 202111425559A CN 114123510 B CN114123510 B CN 114123510B
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transformer
sensor
node
real
time
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CN114123510A (en
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田静
张永良
冯彬杰
严冰
许世亮
姚毅
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Guangzhou Well Youth Energy Technology Co ltd
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Guangzhou Well Youth Energy Technology Co ltd
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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
    • 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]
    • 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
    • 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
    • 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

Abstract

The invention provides a transformer monitoring method and a system based on real-time data analysis, wherein the transformer monitoring system based on real-time data analysis comprises a monitoring data acquisition module, a local analysis module and a cloud analysis module; the monitoring data acquisition module and the local analysis module are arranged in the environment where the transformer is located; the monitoring data acquisition module is used for acquiring transformer state data and transmitting the acquired transformer state data to the data local analysis module in real time through a wireless sensor network; the local analysis module is used for converging the transformer state data collected by each sensor node and carrying out real-time running state analysis processing according to the received transformer state data to obtain a real-time state analysis result; the cloud analysis module is used for carrying out classified storage management and big data analysis processing on the transformer state data transmitted by the local analysis module and the corresponding real-time state analysis result. The invention is beneficial to improving the real-time performance level of transformer monitoring.

Description

Transformer monitoring method and system based on real-time data analysis
Technical Field
The invention relates to the technical field of transformer monitoring, in particular to a transformer monitoring method and a transformer monitoring system based on real-time data analysis.
Background
Along with the transformation and development of national economy, the contradiction between the development of the power supply capacity of partial areas and the increase of the actual demand is gradually shown, in order to actively cope with the situation, a plurality of technologies such as operation temperature improvement, short-time dynamic capacity increase, novel heat-resistant circuits and the like are popularized and adopted in a national grid system, the power transmission capacity of the circuits is greatly improved, and technical transformation is generally adopted for equipment breakers, isolating switches, current transformers and the like in a transformer substation matched with the circuits.
The transformer is the core equipment of power transmission and transformation, and along with the extension of electric wire netting, the distribution range of transformer is also wider and wider, therefore weather change, surrounding environment, power consumption accord with the increase, the circuit ages and thinks that damage becomes the important reason that influences transformer normal work and power supply line normal operating, often leads to transformer department to break down, leads to transformer damage when serious, threatens whole electric wire netting power supply safety.
At present, because the distribution range of the transformer is wide, the whole-course monitoring on the operation condition and related data of each transformer/distribution station cannot be timely and effectively realized only by the traditional manpower supervision, and the acquisition and the archiving of the operation data are more difficult, so that the fault early warning capability and the fault point positioning capability of the transformer are greatly weakened. In the prior art, some technologies for remotely monitoring transformers are also used, but in the prior art, most of the methods for remotely monitoring transformers are implemented by uploading transformer operation record logs to a unified management system for centralized supervision, but the management system processes massive transformer data, and generally, a processing result has delay, and the problem of timely supervision on transformers still cannot be solved.
Disclosure of Invention
Aiming at the technical problem that the transformer cannot be monitored in time, the invention aims to provide a transformer monitoring method and a transformer monitoring system based on real-time data analysis.
The purpose of the invention is realized by adopting the following technical scheme:
in a first aspect, the present invention provides a transformer monitoring system based on real-time data analysis, including: the system comprises a monitoring data acquisition module, a local analysis module and a cloud analysis module; the monitoring data acquisition module and the local analysis module are arranged in the environment where the transformer is located;
the monitoring data acquisition module comprises a plurality of sensor nodes, wherein the plurality of sensor nodes form a wireless sensor network, and each sensor node is used for acquiring transformer state data and transmitting the acquired transformer state data to the data local analysis module in real time through the wireless sensor network;
the local analysis module is used for converging the transformer state data collected by each sensor node and analyzing and processing the real-time running state according to the received transformer state data to obtain a real-time state analysis result; the cloud analysis module is used for transmitting the transformer state data and the corresponding real-time state analysis result to the cloud analysis module;
the cloud analysis module is used for carrying out classified storage management and big data analysis processing on the transformer state data transmitted by the local analysis module and the corresponding real-time state analysis result.
In one embodiment, the sensor nodes include a transformer operation state monitoring node and a transformer environment monitoring node, wherein the transformer operation state monitoring node includes: at least one of a current sensor, a voltage sensor, a temperature sensor, a humidity sensor, and a vibration sensor; the transformer environmental monitoring node includes: at least one of an audio sensor, an image sensor, and a fire sensing sensor.
In one embodiment, the local analysis module comprises a base station node unit and a local analysis unit;
the base station node unit is used for converging the transformer state data collected by each sensor node;
the local analysis unit is used for analyzing and processing the real-time running state according to the received transformer state data to obtain a real-time state analysis result;
the base station node is further used for transmitting the transformer state data and the corresponding real-time state analysis result to the cloud analysis module.
In one embodiment, the system further comprises an alarm module;
when the obtained real-time state analysis result is abnormal, the local analysis module is also used for generating a corresponding alarm instruction according to the obtained real-time state analysis result and transmitting the alarm instruction to the alarm module;
the alarm module is used for sending out corresponding alarm information according to the received alarm instruction.
In one embodiment, the cloud analysis module comprises a database unit and a big data analysis unit;
the database unit is used for performing classified storage management on the transformer state data transmitted by the local analysis module and the corresponding real-time state analysis result to construct a transformer state database;
and the big data analysis unit is used for carrying out big data analysis on the data in the transformer state database based on the big data analysis model to obtain a transformer state big data analysis result.
In one embodiment, the sensor nodes and the base station node unit are deployed together in an environment where the transformer is located, wherein the sensor nodes transmit the transformer state data collected by the sensor nodes to the base station node unit, and the base station node unit aggregates the transformer state data collected by each sensor node and then transmits the aggregated transformer state data to the local analysis unit.
In one embodiment, each sensor node transmits transformer status data to a base station node unit through a wireless sensor network, which specifically includes:
the method comprises the steps that sensor nodes acquire sensor node information collected and transmitted by a base station node unit at intervals of set time, wherein the sensor node information comprises distance information between the sensor nodes and the base station node unit and communication state information between each sensor node and the base station node unit in a sensor network;
(1) when the communication delay between the sensor node and the base station node unit is smaller than the set standard value delay, the sensor node directly transmits the transformer state data acquired in real time to the base station node unit;
(2) when the communication delay between the sensor node and the base station node unit is not less than the set standard value delay, the sensor node selects a next hop node from other neighbor sensor nodes in the set communication range, the transformer state data acquired in real time is transmitted to the next hop node, and the next hop node further transmits the transformer state data to the base station node unit.
In a second aspect, the present invention is directed to a transformer monitoring method based on real-time data analysis, including:
a plurality of sensor nodes of the monitoring data acquisition module form a wireless sensor network, and each sensor node is used for acquiring transformer state data and transmitting the acquired transformer state data to the data local analysis module in real time through the wireless sensor network;
the local analysis module gathers the transformer state data collected by each sensor node, and carries out real-time running state analysis processing according to the received transformer state data to obtain a real-time state analysis result; the local analysis module transmits the transformer state data and the corresponding real-time state analysis result to the cloud analysis module;
and the cloud analysis module is used for carrying out classified storage management and big data analysis processing on the transformer state data transmitted by the local analysis module and the corresponding real-time state analysis result.
The invention has the beneficial effects that: the monitoring data acquisition module and the local analysis module are arranged at the position of the transformer, the monitoring data acquisition module is used for acquiring and transmitting the state data of the transformer in real time, and meanwhile, the local analysis module is used for completing the real-time local analysis and processing of the state data of the transformer to obtain a corresponding real-time state analysis result, so that the real-time state supervision of the transformer can be completed according to the real-time state analysis result, and the data processing pressure of the cloud analysis module is reduced. Meanwhile, the local analysis module transmits the transformer state data and the corresponding real-time analysis result to the cloud analysis module for centralized management, so that the uniformity of transformer management is guaranteed.
Drawings
The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, without inventive effort, further drawings may be derived from the following figures.
Fig. 1 is a frame structure diagram of an embodiment of a transformer monitoring system based on real-time data analysis according to the present invention.
Reference numerals:
a monitoring data acquisition module 10; a local analysis module 20; a cloud analysis module 30.
Detailed Description
The invention is further described in connection with the following application scenarios.
Referring to fig. 1, an embodiment of a transformer monitoring system based on real-time data analysis includes: the monitoring data acquisition module 10, the local analysis module 20 and the cloud analysis module 30; the monitoring data acquisition module 10 and the local analysis module 20 are arranged in the environment where the transformer is located;
the monitoring data acquisition module 10 comprises a plurality of sensor nodes, wherein the plurality of sensor nodes form a wireless sensor network, and each sensor node is used for acquiring transformer state data and transmitting the acquired transformer state data to the data local analysis module 20 in real time through the wireless sensor network;
the local analysis module 20 is configured to aggregate the transformer state data collected by each sensor node, and perform real-time operation state analysis processing according to the received transformer state data to obtain a real-time state analysis result; and for transmitting the transformer status data and the corresponding real-time status analysis results to the cloud analysis module 30;
the cloud analysis module 30 is configured to perform classified storage management and big data analysis processing on the transformer state data and the corresponding real-time state analysis result transmitted by the local analysis module 20.
In the above embodiment of the present invention, the monitoring data acquisition module 10 and the local analysis module 20 are disposed at the position of the transformer, the monitoring data acquisition module 10 acquires and transmits the transformer status data in real time, and the local analysis module 20 performs real-time local analysis and processing on the transformer status data to obtain a corresponding real-time status analysis result, which is helpful for completing real-time status supervision on the transformer according to the real-time status analysis result, and simultaneously reduces the data processing pressure of the cloud analysis module 30. Meanwhile, the local analysis module 20 also transmits the transformer state data and the corresponding real-time analysis result to the cloud analysis module 30 for centralized management, so that the uniformity of transformer management is ensured.
In one embodiment, the sensor nodes include a transformer operation state monitoring node and a transformer environment monitoring node, wherein the transformer operation state monitoring node includes: at least one of a current sensor, a voltage sensor, a temperature sensor, a humidity sensor, and a vibration sensor; the transformer environmental monitoring node includes: at least one of an audio sensor, an image sensor, and a fire sensing sensor.
Correspondingly, the transformer state data comprises transformer operation state data and transformer environment state data; the transformer operation state data comprises transformer three-phase current and voltage information, transformer internal temperature information, transformer vibration monitoring information and the like; the transformer environment state data comprises external temperature and humidity information of the transformer, image monitoring information, sound monitoring information, fire monitoring information and the like.
According to the requirement of transformer state monitoring, sensor nodes with different functions can be set to monitor the state of the transformer in real time, and the reliability and the adaptability of transformer monitoring are improved.
In one embodiment, the local analysis module 20 includes a base station node unit and a local analysis unit;
the base station node unit is used for converging the transformer state data acquired by each sensor node;
the local analysis unit is used for analyzing and processing the real-time running state according to the received transformer state data to obtain a real-time state analysis result;
the base station node is further configured to transmit the transformer state data and the corresponding real-time state analysis result to the cloud analysis module 30.
In one embodiment, the system further comprises an alarm module;
when the obtained real-time state analysis result is abnormal, the local analysis module 20 is further configured to generate a corresponding alarm instruction according to the obtained real-time state analysis result and transmit the alarm instruction to the alarm module;
the alarm module is used for sending out corresponding alarm information according to the received alarm instruction.
In one scenario, when the obtained real-time state analysis result is abnormal, the local analysis module 20 is further configured to transmit the obtained real-time state analysis result to the local management terminal, so that a local manager can timely know the abnormal condition of the transformer and perform corresponding processing, which is beneficial to improving the real-time performance and reliability of transformer state monitoring.
In one embodiment, the cloud analysis module 30 includes a database unit and a big data analysis unit;
the database unit is used for performing classified storage management on the transformer state data transmitted by the local analysis module 20 and the corresponding real-time state analysis result to construct a transformer state database;
and the big data analysis unit is used for carrying out big data analysis on the data in the transformer state database based on the big data analysis model to obtain a transformer state big data analysis result.
The local analysis module 20 performs direct analysis processing on the acquired transformer state data, for example, whether each transformer state data meets a set standard range or not is judged, and the transformer state can be directly and primarily judged through real-time analysis processing, so that the real-time performance of transformer state monitoring is ensured, and a basis is provided for a manager to manage the transformer in real time;
the cloud analysis module 30 plays a role in data management and subsequent further advanced analysis and processing for the managed data; through the AI/big data analysis engine carried on the cloud analysis module 30, more complex data analysis processing tasks can be further performed on the data related to the transformer, for example, the state of the transformer is predicted or multi-dimensional analyzed, so that a more accurate and wider transformer state analysis result is obtained, and a basis is provided for a manager to perform long-term management on the state of the transformer.
In one embodiment, the sensor nodes and the base station node unit are deployed together in an environment where the transformer is located, wherein the sensor nodes transmit the transformer state data collected by the sensor nodes to the base station node unit, and the base station node unit aggregates the transformer state data collected by each sensor node and then transmits the aggregated transformer state data to the local analysis unit.
In order to ensure the real-time property of the sensor nodes transmitting the transformer state data to the local analysis module 20 after acquiring the transformer state data, in an embodiment, each sensor node transmits the transformer state data to the base station node unit through a wireless sensor network, which specifically includes:
the method comprises the steps that sensor nodes acquire sensor node information collected and transmitted by a base station node unit at intervals of set time, wherein the sensor node information comprises distance information between the sensor nodes and the base station node unit and communication state information between each sensor node and the base station node unit in a sensor network;
(1) when the communication delay between the sensor node and the base station node unit is smaller than the set standard value delay, the sensor node directly transmits the transformer state data acquired in real time to the base station node unit;
(2) when the communication delay between the sensor node and the base station node unit is not less than the set standard value delay, the sensor node selects a next hop node from other neighbor sensor nodes in the set communication range, the transformer state data acquired in real time is transmitted to the next hop node, and the next hop node further transmits the transformer state data to the base station node unit;
the standard value time delay between the sensor node and the base station node unit is calculated by the following function:
Figure BDA0003378250180000061
in the formula, TiRepresenting a standard value delay between the sensor node i and the base station node unit; siRepresenting the distance between the sensor node i and the base station node unit; s' represents the set standard transmission distance of the sensor node; v. ofmeanThe average communication delay between each sensor node and a base station node unit in the wireless sensor network in the last time interval is represented; v' denotes a set targetA quasi-communication delay representing an average communication delay between each sensor node and a base station node unit in the wireless sensor network since the wireless sensor network starts to operate; t ' represents a set standard value delay initial parameter, T ' represents a set standard value delay adjusting parameter, wherein T ' - [0.1,0.5]T′。
In the above embodiment, when the number of sensor nodes in the wireless sensor network is large, the sensor nodes can select a direct or indirect transmission mode to transmit the acquired transformer state data to the local analysis module 20 according to the data transmission delay condition of the sensor nodes and the corresponding base station node units, and when the sensor nodes cannot directly establish a direct transmission relationship with the base station nodes in good real-time performance due to network fluctuation, the sensor nodes can select a mode of transmitting the data to the neighbor sensor nodes through the sensor nodes in an internet of things mode, and the neighbor sensor nodes assist in completing the transmission of the data, so as to ensure the real-time performance of transmitting the transformer state data acquired by the sensor nodes to the base station node units. The specific calculation mode of the standard value delay is provided, the standard value delay which meets the current situation can be set in a self-adaptive mode according to the self state of each sensor node, the situation that the sensor node cannot accurately judge the actual transmission performance of the sensor node (for example, the whole network delay and the like are not considered) due to poor performance in the traditional fixed value delay standard is avoided, the adaptability and the accuracy of the sensor node in the judgment of which transmission mode is adopted are improved, and the real-time level of the transformer state monitoring is indirectly improved.
The sensor node uploads the sensor information of the sensor node to a base station node unit at set time intervals, and the sensor node information is obtained from the base station node unit; wherein the sensor information further comprises other information required for calculating the standard value delay or the dominance value of the neighboring sensor node.
The sensor nodes can finish the selection of the next hop nodes thereof, or the base station nodes finish the configuration of the next hop nodes of each sensor node in a unified way and then transmit the corresponding next hop node information to the corresponding sensor nodes; the present application is not specifically limited herein.
In one embodiment, the selecting, by a sensor node, a next hop node from other neighboring sensor nodes within a set communication range of the sensor node specifically includes:
the sensor node calculates the dominant values of other neighbor sensor nodes, and selects the neighbor sensor node with the largest dominant value as a next hop node;
the advantage value of the neighbor sensor node is calculated by the following function:
Figure BDA0003378250180000071
in the formula, YixRepresents the dominance value of the neighbor sensor node x to the sensor node i, where vi0Representing the communication delay between the sensor node i and the base station node unit; v. ofixRepresenting the communication delay between the sensor node i and the neighbor sensor node x; v. ofx0Representing the communication delay between the neighbor sensor node x and the base station node unit; t' represents a set standard value delay initial parameter; s. theiRepresenting the distance between the sensor node i and the base station node unit; sxRepresents the distance between the sensor node x and the base station node unit; alpha represents a set communication dominance weight coefficient; beta represents the set channel dominance weight coefficient.
In the embodiment, in the process that the sensor node transmits the transformer state data acquired by the sensor node to the neighbor sensor node in an indirect transmission mode and the neighbor node assists in completing data transmission, the technical scheme of judging and selecting the next hop node through the dominance value is also provided, meanwhile, a specific dominance value calculation function is provided, and the more appropriate neighbor sensor node is selected as the next hop node by considering the transmission performance and the position performance between the sensor node and the target neighbor sensor node, so that the performance of selecting the next hop node in the process of realizing indirect transmission through the wireless sensor network by the sensor node is improved, and the performance of acquiring and transmitting the transformer state data in real time is ensured.
Corresponding to the transformer monitoring system based on real-time data analysis, the application also provides a transformer monitoring method based on real-time data analysis, which comprises the following steps:
a plurality of sensor nodes of the monitoring data acquisition module 10 form a wireless sensor network, and each sensor node is used for acquiring transformer state data and transmitting the acquired transformer state data to the data local analysis module 20 in real time through the wireless sensor network;
the local analysis module 20 converges the transformer state data collected by each sensor node, and performs real-time running state analysis processing according to the received transformer state data to obtain a real-time state analysis result; the local analysis module 20 transmits the transformer state data and the corresponding real-time state analysis result to the cloud analysis module 30;
the cloud analysis module 30 performs classified storage management and big data analysis processing on the transformer state data and the corresponding real-time state analysis result transmitted by the local analysis module 20.
Meanwhile, the method steps of the transformer monitoring method based on real-time data analysis provided by the application also correspond to the specific real-time modes in the transformer monitoring system based on real-time data analysis, and repeated description is not provided herein.
It should be noted that, functional units/modules in the embodiments of the present invention may be integrated into one processing unit/module, or each unit/module may exist alone physically, or two or more units/modules are integrated into one unit/module. The integrated units/modules may be implemented in the form of hardware, or may be implemented in the form of software functional units/modules.
From the above description of embodiments, it is clear for a person skilled in the art that the embodiments described herein can be implemented in hardware, software, firmware, middleware, code or any appropriate combination thereof. For a hardware implementation, a processor may be implemented in one or more of the following units: an Application Specific Integrated Circuit (ASIC), a Digital Signal Processor (DSP), a Digital Signal Processing Device (DSPD), a Programmable Logic Device (PLD), a Field Programmable Gate Array (FPGA), a processor, a controller, a microcontroller, a microprocessor, other electronic units designed to perform the functions described herein, or a combination thereof. For a software implementation, some or all of the procedures of an embodiment may be performed by a computer program instructing associated hardware. In practice, the program may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a computer. Computer-readable media can include, but is not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the protection scope of the present invention, although the present invention is described in detail with reference to the preferred embodiments, it should be analyzed by those skilled in the art that modifications or equivalent substitutions can be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims (5)

1. A transformer monitoring system based on real-time data analysis, comprising: the system comprises a monitoring data acquisition module, a local analysis module and a cloud analysis module; the monitoring data acquisition module and the local analysis module are arranged in the environment where the transformer is located;
the monitoring data acquisition module comprises a plurality of sensor nodes, wherein the plurality of sensor nodes form a wireless sensor network, and each sensor node is used for acquiring transformer state data and transmitting the acquired transformer state data to the local analysis module in real time through the wireless sensor network;
the local analysis module is used for converging the transformer state data collected by each sensor node and carrying out real-time running state analysis processing according to the received transformer state data to obtain a real-time state analysis result; the cloud analysis module is used for transmitting the transformer state data and the corresponding real-time state analysis result to the cloud analysis module;
the cloud analysis module is used for performing classified storage management and big data analysis processing on the transformer state data transmitted by the local analysis module and the corresponding real-time state analysis result;
the local analysis module comprises a base station node unit and a local analysis unit;
the base station node unit is used for converging the transformer state data collected by each sensor node;
the local analysis unit is used for carrying out real-time running state analysis processing according to the received transformer state data to obtain a real-time state analysis result;
the base station node unit is also used for transmitting the transformer state data and the corresponding real-time state analysis result to the cloud analysis module;
the sensor nodes and the base station node units are jointly deployed in the environment where the transformer is located, the sensor nodes transmit the transformer state data acquired by the sensor nodes to the base station node units, and the base station node units converge the transformer state data acquired by the sensor nodes and then transmit the converged transformer state data to the local analysis unit;
wherein, each sensor node transmits transformer state data to the base station node unit through the wireless sensor network, specifically includes:
the method comprises the steps that sensor nodes acquire sensor node information collected and transmitted by a base station node unit at intervals of set time, wherein the sensor node information comprises distance information between the sensor nodes and the base station node unit and communication state information between each sensor node and the base station node unit in a sensor network;
(1) when the communication delay between the sensor node and the base station node unit is smaller than the set standard value delay, the sensor node directly transmits the transformer state data acquired in real time to the base station node unit;
(2) when the communication delay between the sensor node and the base station node unit is not less than the set standard value delay, the sensor node selects a next hop node from other neighbor sensor nodes in the set communication range, the transformer state data acquired in real time is transmitted to the next hop node, and the next hop node further transmits the transformer state data to the base station node unit;
the standard value time delay between the sensor node and the base station node unit is calculated by the following function:
Figure FDA0003632339940000021
in the formula, TiRepresenting a standard value delay between the sensor node i and the base station node unit; siRepresenting the distance between the sensor node i and the base station node unit; s' represents the set standard transmission distance of the sensor node; v. ofmeanThe average communication delay between each sensor node and a base station node unit in the wireless sensor network in the last time interval is represented; v' represents a set standard communication delay which represents an average communication delay between each sensor node and a base station node unit in the wireless sensor network since the wireless sensor network starts to work; t ' represents a set standard value delay initial parameter, T ' represents a set standard value delay adjusting parameter, wherein T ' - [0.1,0.5]T′；
The method for selecting the next hop node from the other neighbor sensor nodes in the set communication range includes:
the sensor node calculates the dominance values of other neighbor sensor nodes, and selects the neighbor sensor node with the largest dominance value as a next hop node;
the advantage value of the neighbor sensor node is calculated by the following function:
Figure FDA0003632339940000022
in the formula, YixRepresents the dominance value of the neighbor sensor node x to the sensor node i, where vi0Representing the communication delay between the sensor node i and the base station node unit; v. ofixRepresenting the communication delay between the sensor node i and the neighbor sensor node x; v. ofx0Representing the communication delay between the neighbor sensor node x and the base station node unit; t' represents a set standard value delay initial parameter; siRepresenting the distance between the sensor node i and the base station node unit; sxRepresents the distance between the sensor node x and the base station node unit; alpha represents a set communication dominance weight coefficient; beta represents the set channel dominance weight coefficient.
2. The transformer monitoring system based on real-time data analysis of claim 1, wherein the sensor nodes comprise a transformer operation state monitoring node and a transformer environment monitoring node, wherein the transformer operation state monitoring node comprises: at least one of a current sensor, a voltage sensor, a temperature sensor, a humidity sensor, and a vibration sensor; the transformer environmental monitoring node includes: at least one of an audio sensor, an image sensor, and a fire sensing sensor.
3. The transformer monitoring system based on real-time data analysis according to claim 1, further comprising an alarm module;
when the obtained real-time state analysis result is abnormal, the local analysis module is also used for generating a corresponding alarm instruction according to the obtained real-time state analysis result and transmitting the alarm instruction to the alarm module;
the alarm module is used for sending out corresponding alarm information according to the received alarm instruction.
4. The transformer monitoring system based on real-time data analysis as claimed in claim 1, wherein the cloud analysis module comprises a database unit and a big data analysis unit;
the database unit is used for performing classified storage management on the transformer state data transmitted by the local analysis module and the corresponding real-time state analysis result to construct a transformer state database;
and the big data analysis unit is used for carrying out big data analysis on the data in the transformer state database based on the big data analysis model to obtain a transformer state big data analysis result.
5. A monitoring method of a transformer monitoring system according to any of claims 1-4, characterized by comprising:
a plurality of sensor nodes of the monitoring data acquisition module form a wireless sensor network, and each sensor node is used for acquiring transformer state data and transmitting the acquired transformer state data to the local analysis module in real time through the wireless sensor network;
the local analysis module gathers the transformer state data collected by each sensor node, and carries out real-time running state analysis processing according to the received transformer state data to obtain a real-time state analysis result; the local analysis module transmits the transformer state data and the corresponding real-time state analysis result to the cloud analysis module;
and the cloud analysis module is used for carrying out classified storage management and big data analysis processing on the transformer state data transmitted by the local analysis module and the corresponding real-time state analysis result.
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