CN114498942A - Transformer monitoring management system based on big data analysis - Google Patents
Transformer monitoring management system based on big data analysis Download PDFInfo
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- CN114498942A CN114498942A CN202210392214.2A CN202210392214A CN114498942A CN 114498942 A CN114498942 A CN 114498942A CN 202210392214 A CN202210392214 A CN 202210392214A CN 114498942 A CN114498942 A CN 114498942A
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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
- H02J13/00034—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for the elements or equipment being or involving an electric power substation
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B31/00—Predictive alarm systems characterised by extrapolation or other computation using updated historic data
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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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- 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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- Housings And Mounting Of Transformers (AREA)
Abstract
The invention belongs to the field of power equipment control, relates to a transformer management technology, and is used for solving the problem of potential safety hazard in the mode that the running state of a transformer is judged by adopting a uniform and fixed threshold value in the conventional transformer monitoring management system; the early warning module comprises a red signal lamp for indicating emergency power-off, a yellow signal lamp for indicating abnormal operation and a green signal lamp for indicating normal operation; the running state of the transformer is detected and analyzed in real time through the running analysis module, and the running coefficient is obtained through the running parameter calculation of the transformer, so that the transformer is protected, the over-use accelerated aging of the transformer is prevented, and the service life of the transformer is prolonged.
Description
Technical Field
The invention belongs to the field of power equipment control, relates to a transformer management technology, and particularly relates to a transformer monitoring and management system based on big data analysis.
Background
The intelligent transformer is a core device of an intelligent power grid, the construction of the intelligent power grid in China can be promoted just by continuous improvement of the intelligent transformer technology, the development direction of the intelligent power grid is the fusion of a primary system and a secondary system, the pursuit functional targets are intellectualization and self-adaptation, the pursuit economic targets are the lowest comprehensive construction cost and the lowest operation and maintenance cost, along with the promotion of the ubiquitous Internet of things of the state network and the development of artificial intelligence, the intelligent transformer becomes one of the future research directions, and the market demand is increased day by day.
In the existing transformer monitoring and management system, a threshold value for judging whether the running state of a transformer is qualified is a uniform and fixed numerical value, however, in the monitoring and management process, the loss degree of each transformer is different, and the loss degree of the same transformer in different use stages is also different, so that the mode of judging the running state of the transformer by using the uniform and fixed threshold value is not scientific, and the mode may cause wrong judgment result of the state of the transformer, thereby causing potential safety hazard.
In view of the above technical problem, the present application proposes a solution.
Disclosure of Invention
The invention aims to provide a transformer monitoring and management system based on big data analysis, which is used for solving the problem of potential safety hazard in the mode that the existing transformer monitoring and management system judges the running state of a transformer by adopting a uniform and fixed threshold value;
the technical problems to be solved by the invention are as follows: how to provide a transformer monitoring management system capable of carrying out accurate state analysis on each transformer.
The purpose of the invention can be realized by the following technical scheme:
a transformer monitoring and management system based on big data analysis comprises a monitoring and management platform, wherein the monitoring and management platform is in communication connection with an operation analysis module, an early warning module, a service life analysis module, a storage module and a controller;
the early warning module comprises a red signal lamp for indicating emergency power failure, a yellow signal lamp for indicating abnormal operation and a green signal lamp for indicating normal operation;
the operation analysis module is used for detecting and analyzing the operation state of the transformer, sending an early warning signal to the monitoring management platform when the operation state of an analysis object is unqualified, sending the early warning signal to the early warning module after the monitoring management platform receives the early warning signal, and controlling the yellow signal lamp to be turned on after the early warning module receives the early warning signal;
the method comprises the steps that operation coefficients of analysis objects are monitored in real time after yellow signal lamps are turned on, the corresponding analysis objects are marked as dangerous objects when the analysis objects are in dangerous operation states, operation dangerous signals are sent to a monitoring management platform by an operation analysis module, the operation dangerous signals are sent to an early warning module and a controller by the monitoring management module after the operation dangerous signals are received by the early warning module, red signal lamps are controlled to be turned on after the operation dangerous signals are received by the early warning module, circuits of the analysis objects are cut off after the operation dangerous signals are received by the controller, descending signals are generated after the circuits of the analysis objects are cut off by the controller and are sent to the monitoring management platform, and the descending signals are sent to a storage module by the monitoring management platform after the descending signals are received by the monitoring management platform;
and the service life analysis module is used for analyzing and judging whether the residual service life of the transformer meets the requirement.
As a preferred embodiment of the present invention, the specific process of the operation analysis module for detecting and analyzing the operation state of the transformer includes: the method comprises the steps of marking a transformer to be detected and analyzed as an analysis object i, wherein i =1, 2, …, n and n are positive integers, obtaining oil temperature data YWi, vibration data ZDi and noise data ZSi when the analysis object i works, obtaining an operation coefficient YXi by carrying out numerical calculation on the oil temperature data YWi, the vibration data ZDi and the noise data ZSi when the analysis object i works, obtaining an operation threshold YXmax through a storage module, comparing the operation coefficient YXi of the analysis object i with the operation threshold YXmax, and judging whether the operation state of the analysis object is qualified or not according to the comparison result.
As a preferred embodiment of the present invention, the acquisition process of the oil temperature data YWi of the analysis object i includes: acquiring an oil temperature value of an analysis object i, acquiring an oil temperature standard value through a storage module, and marking an absolute value of a difference value of the oil temperature value and the oil temperature standard value as oil temperature data YWi;
the acquisition process of the vibration data ZDi of the analysis object i includes: marking the maximum vibration frequency of the analysis object i in L1 seconds as vibration data ZDi;
the acquisition process of the noise data ZSi of the analysis object i includes: the maximum decibel value of noise generated by the analysis subject i within L1 seconds is labeled as noise data ZSi.
As a preferred embodiment of the present invention, the comparison of the operation coefficient YXi with the operation threshold YXmax includes:
if the analysis object with the operation coefficient YXi not smaller than the operation threshold YXmax exists, judging that the operation state of the analysis object i is unqualified;
if the analysis object with the operation coefficient YXi not smaller than the operation threshold YXmax does not exist, the operation state of the analysis object i meets the requirement, the operation analysis module sends an operation qualified signal to the monitoring management platform, the monitoring management platform sends the operation qualified signal to the early warning module after receiving the operation qualified signal, and the early warning module controls the green signal lamp to be turned on after receiving the operation qualified signal.
As a preferred embodiment of the present invention, the process of determining a dangerous object includes: acquiring the power failure threshold value DDi of the analysis object i through the storage module, and comparing the operation coefficient YXi of the analysis object i with the power failure threshold value DDi:
if the analysis object with the operation coefficient YXi being greater than or equal to the outage threshold value DDi exists, judging that the operation state of the analysis object is dangerous, and marking the corresponding analysis object as a dangerous object;
if there is no analysis object whose operation coefficient YXi is equal to or greater than the power-off threshold DDi, it is determined that the operation state of the analysis object is safe.
As a preferred embodiment of the present invention, after receiving the value reduction signal, the storage module assigns the outage threshold DDi of the dangerous object again to obtain a new outage threshold DXi, where the assignment formula of the outage threshold DXi is DXi = t × DDi, where t is a proportionality coefficient, and t is greater than or equal to 0.92 and less than or equal to 0.96, replaces the outage threshold DDi with the value of the new outage threshold DXi of the dangerous object, after the replacement is completed, the storage module sends a life analysis signal to the monitoring management platform, and the monitoring management platform sends the life analysis signal to the life analysis module after receiving the life analysis signal.
As a preferred embodiment of the present invention, the specific process of analyzing whether the remaining life of the transformer meets the requirement by the life analysis module includes: acquiring a power-off threshold value DDi of an analysis object i, acquiring a service life threshold value DDmin through a storage module, and comparing the power-off threshold value DDi of the analysis object i with the service life threshold value DDmin one by one:
if the power failure threshold value DDi of the analysis object i is less than or equal to the service life threshold value DDmin, judging that the residual service life of the corresponding analysis object does not meet the requirement, and marking the corresponding analysis object as a replacement object;
if the power-off threshold value DDi of the analysis object i is larger than the service life threshold value DDmin, judging that the residual service life of the corresponding analysis object meets the requirement, and marking the corresponding analysis object as a reserved object;
if the number of the replacing objects is not zero after the comparison is finished, generating replacing signals and sending the replacing signals to a monitoring management platform, sending the received replacing signals to a mobile phone terminal of a manager by the monitoring management platform, and replacing the replacing objects after the manager receives the replacing signals;
and after the comparison is finished, if the number of the replacing objects is zero, whether the distribution arrangement mode of the transformer bank is reasonable or not is analyzed.
As a preferred embodiment of the present invention, the specific process of analyzing whether the distribution arrangement of the transformer banks is reasonable includes: establishing a power failure set { DD1, DD2, …, DDn } with the power failure threshold of the reserved object, carrying out variance calculation on the power failure set to obtain a reasonable coefficient HL, obtaining a reasonable threshold HLmax through a storage module, and comparing the reasonable coefficient HL with the reasonable threshold HLmax:
if the reasonable coefficient HL is smaller than the reasonable threshold value HLmax, the distribution arrangement mode of the current transformer bank is judged to be reasonable, and a reasonable signal is sent to the monitoring management platform by the service life analysis module;
if the reasonable coefficient HL is larger than or equal to the reasonable threshold value HLmax, the distribution arrangement mode of the current transformer bank is judged to be unreasonable, the service life analysis module sends unreasonable signals to the monitoring management platform, the monitoring management platform sends the received unreasonable signals to a mobile phone terminal of a manager, and the manager replans the distribution arrangement mode of the transformer bank after receiving the unreasonable signals.
The invention has the following beneficial effects:
1. the running state of the transformer is detected and analyzed in real time through the running analysis module, the running coefficient is obtained through the running parameter calculation of the transformer, so that whether the running state of the transformer is qualified or not is judged according to the numerical value of the running coefficient, early warning is timely carried out through the early warning module when the transformer with the unqualified running state exists, and managers can manually power off the transformer after seeing the yellow signal lamp, so that the transformer is protected, the over-use accelerated aging of the transformer is prevented, and the service life of the transformer is prolonged;
2. the operation coefficient of the transformer is monitored in real time when the yellow signal lamp is turned on, when a manager does not timely cut off power, the operation coefficient of the transformer is continuously increased until the operation coefficient of the transformer exceeds a corresponding power-off threshold value, a circuit of the transformer is automatically cut off through the controller, the power-off threshold values correspond to the transformers one by one, the power-off threshold values of all the transformers in the same specification are the same in the initial state, the values of the power-off threshold values are updated according to the running danger times of the transformers, and the power-off threshold values correspond to the loss degrees of all the transformers respectively, so that accurate state analysis of all the transformers is guaranteed;
3. the residual service life of the transformer can be detected and analyzed through the service life analysis module, the power-off threshold value of the transformer is associated with the loss degree of the transformer, and the loss degree of the transformer is larger when the value of the power-off threshold value is smaller, so that the residual service life of the transformer can be monitored according to the value of the power-off threshold value of the transformer, the transformer can be replaced in time when being scrapped, and the influence on the normal work of power equipment is avoided;
4. the outage set established by the service life analysis module can analyze the deviation of the loss degree of each transformer in the power system, thereby avoiding the phenomenon that the loss degree of one part of the transformers is very large and the loss degree of the other part of the transformers is very small, the phenomenon can lead the frequency of the replacement of the transformers to be more frequent, the utilization rate of replacement personnel is too low, and potential safety hazards exist in each working time period of the transformers, the loss degree and the aging speed of each transformer can be closer after the transformers are reasonably distributed, thereby being capable of uniformly replacing and overhauling the transformers in one batch, and the working time period before the transformers in the batch are aged collectively is relatively smaller in potential safety hazards, so the safety monitoring prevention cost of the transformers is lower.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic block diagram of the system of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The transformer is basic equipment for power transmission and distribution, is widely applied to the fields of industry, agriculture, traffic, urban communities and the like, about 1700 thousands of transformers run in a network in China, the total capacity is about 110 hundred million kilo volt-ampere, the loss of the transformer accounts for about 40% of the power loss of power transmission and distribution, and the transformer has great energy-saving potential; in the power equipment control system, because the loss degrees of the transformers are different in the using process, the accuracy of the mode of judging the running state of the transformers by adopting a uniform and fixed threshold value is very low, and once the running state is judged incorrectly, a very serious safety accident can be caused.
As shown in fig. 1, a transformer monitoring and management system based on big data analysis includes a monitoring and management platform, and the monitoring and management platform is communicatively connected with an operation analysis module, an early warning module, a life analysis module, a storage module, and a controller.
The early warning module comprises a red signal lamp for indicating emergency power failure, a yellow signal lamp for indicating abnormal operation and a green signal lamp for indicating normal operation.
The operation analysis module is used for detecting and analyzing the operation state of the transformer: marking a transformer to be detected and analyzed as an analysis object i, wherein i =1, 2, …, n is a positive integer, acquiring oil temperature data YWi, vibration data ZDi and noise data ZSi when the analysis object i works, and acquiring oil temperature data YWi of the analysis object i comprises the following steps: acquiring an oil temperature value of an analysis object i, wherein the oil temperature value is directly acquired by a temperature sensor, the temperature sensor is a sensor which can sense temperature and convert the temperature into an available output signal, the temperature sensor is a core part of a temperature measuring instrument, is wide in variety, can be divided into a contact type and a non-contact type according to a measuring mode, is divided into a thermal resistor and a thermocouple according to characteristics of sensor materials and electronic elements, acquires an oil temperature standard value through a storage module, and marks an absolute value of the difference value of the oil temperature value and the oil temperature standard value as oil temperature data YWi; the acquisition process of the vibration data ZDi of the analysis object i includes: the maximum vibration frequency of an analysis object i in L1 seconds is marked as vibration data ZDi, the vibration frequency is directly obtained by a vibration sensor, the vibration sensor is one of key components in the test technology, and the vibration sensor mainly receives mechanical quantity and converts the mechanical quantity into electric quantity proportional to the mechanical quantity. Since it is also an electromechanical conversion device, we sometimes refer to it as a transducer, a vibration pickup, etc.; the acquisition process of the noise data ZSi of the analysis object i includes: the maximum noise decibel value generated by an analysis object i within L1 seconds is marked as noise data ZSi, L1 is a numerical constant, the noise decibel value is directly acquired by a noise sensor, and the noise sensor is a capacitance type electret microphone sensitive to sound, so that an electret film in the microphone vibrates by sound waves to cause the change of capacitance, and tiny voltage which changes correspondingly to the capacitance is generated, and the conversion from an optical signal to an electric signal is realized. An operation coefficient YXi is obtained by a formula YXi = α 1 × YWi + α 2 × ZDi + α 3 × ZSi, it should be noted that the operation coefficient is a numerical value reflecting how good the transformer operates, and the larger the numerical value of the operation coefficient is, the worse the corresponding transformer operates, where α 1, α 2, and α 3 are proportionality coefficients, and α 1 > α 2 > α 3 > 1; acquiring an operation threshold YXmax through a storage module, and comparing an operation coefficient of an analysis object i with the operation threshold YXmax: if an analysis object with an operation coefficient YXi not less than an operation threshold YXmax exists, judging that the operation state of the analysis object i is unqualified, sending an early warning signal to a monitoring management platform by an operation analysis module, sending the early warning signal to the early warning module after the monitoring management platform receives the early warning signal, controlling a yellow signal lamp to be turned on by the early warning module after the early warning signal is received, manually cutting off a circuit of the transformer by a manager after the yellow signal lamp is turned on, wherein the turning-on process of the yellow signal lamp is a buffering process, the operation state of the transformer reaches a zero-limit edge in the buffering process, and directly automatically powering off by using a controller once the operation state of the transformer reaches the zero-limit; if the analysis object with the operation coefficient YXi not smaller than the operation threshold YXmax does not exist, the operation state of the analysis object i meets the requirement, the operation analysis module sends an operation qualified signal to the monitoring management platform, the monitoring management platform sends the operation qualified signal to the early warning module after receiving the operation qualified signal, and the early warning module controls the green signal lamp to be turned on after receiving the operation qualified signal.
The operation analysis module detects and analyzes the operation state of the transformer in real time, and the operation coefficient is obtained through the operation parameter calculation of the transformer, so that whether the operation state of the transformer is qualified or not is judged through the numerical value of the operation coefficient, early warning is timely carried out through the early warning module when the transformer with unqualified operation state exists, managers can manually power off the transformer after seeing the yellow signal lamp, the transformer is protected, the transformer is prevented from being overused and accelerated aging, and the service life of the transformer is prolonged.
The method comprises the steps of monitoring an operation coefficient YXi of an analysis object i in real time after a yellow signal lamp is turned on, acquiring a power failure threshold value DDi of the analysis object i through a storage module, wherein the number of the power failure threshold values DDi is n, the power failure threshold values correspond to the analysis objects one to one, the power failure threshold values of all transformers in the same specification in an initial state are the same, the power failure threshold values are updated according to the operation dangerous times of the transformers, the power failure threshold values correspond to the loss degrees of all the transformers respectively, accurate state analysis is carried out on each transformer, and the operation coefficient YXi of the analysis object i is compared with the power failure threshold values DDi: if an analysis object with an operation coefficient YXi larger than or equal to the power-off threshold value DDi exists, judging that the operation state of the analysis object is dangerous, marking the corresponding analysis object as a dangerous object, sending an operation danger signal to a monitoring management platform by an operation analysis module, sending the operation danger signal to an early warning module and a controller by the monitoring management module after receiving the operation danger signal, controlling a red signal lamp to be turned on by the early warning module after receiving the operation danger signal, cutting off a circuit of the analysis object by the controller after receiving the operation danger signal, generating a value-reducing signal by the controller after cutting off the circuit of the analysis object and sending the value-reducing signal to the monitoring management platform, sending the value-reducing signal to a storage module by the monitoring management platform after receiving the value-reducing signal, and re-assigning the power-off threshold value DXi of the dangerous object to obtain a new power-off threshold value DXi, the assignment formula of the outage threshold value DXi is DXi = t × DDi, wherein t is a proportionality coefficient, t is more than or equal to 0.92 and less than or equal to 0.96, the outage threshold value DDi is replaced by the value of a new outage threshold value DXi of a dangerous object, after the replacement is completed, the storage module sends a service life analysis signal to the monitoring management platform, the monitoring management platform receives the service life analysis signal and sends the service life analysis signal to the service life analysis module, the operation coefficient of the transformer is monitored in real time when a yellow signal lamp is turned on, the operation coefficient of the transformer is continuously increased when a manager does not timely perform outage until the operation coefficient of the transformer exceeds the corresponding outage threshold value, the circuit of the transformer is automatically cut off through the controller, the outage threshold values correspond to the transformers one to one, the outage threshold values of the transformers in the same specification are the same in the initial state, and the value of the outage threshold value is updated according to the operation danger number of the transformers, each power-off threshold value corresponds to the loss degree of each transformer, so that accurate state analysis of each transformer is guaranteed; if there is no analysis object whose operation coefficient YXi is equal to or greater than the power-off threshold DDi, it is determined that the operation state of the analysis object is safe.
The service life analysis module is used for analyzing and judging whether the residual service life of the transformer meets the requirements: acquiring a power-off threshold value DDi of an analysis object i, acquiring a service life threshold value DDmin through a storage module, and comparing the power-off threshold value DDi of the analysis object i with the service life threshold value DDmin one by one: if the outage threshold value DDi of the analysis object i is smaller than or equal to the service life threshold value DDmin, judging that the residual service life of the corresponding analysis object does not meet the requirement, marking the corresponding analysis object as a replacement object, detecting and analyzing the residual service life of the transformer by a service life analysis module, wherein the outage threshold value of the transformer is related to the loss degree of the transformer, and the loss degree of the transformer is larger when the value of the outage threshold value is smaller, so that the residual service life of the transformer can be monitored according to the value of the outage threshold value of the transformer, the transformer is replaced in time when being near to scrap, and the normal work of power equipment is prevented from being influenced; if the power-off threshold value DDi of the analysis object i is larger than the service life threshold value DDmin, judging that the residual service life of the corresponding analysis object meets the requirement, and marking the corresponding analysis object as a reserved object; if the number of the replacing objects is not zero after the comparison is finished, generating replacing signals and sending the replacing signals to a monitoring management platform, sending the received replacing signals to a mobile phone terminal of a manager by the monitoring management platform, and replacing the replacing objects after the manager receives the replacing signals; if the number of the replaced objects is zero after the comparison is finished, a power failure set { DD1, DD2, …, DDn } is established for the power failure threshold of the reserved objects, the deviation of the loss degree of each transformer in the power system can be analyzed through the established power failure set, so that the phenomenon that the loss degree of one part of the transformers is very large and the loss degree of the other part of the transformers is very small is avoided, the phenomenon can cause that the frequency of the transformers is changed frequently, the utilization rate of the replaced personnel is too low, potential safety hazards exist in each time period of the transformer operation, a reasonable coefficient HL is obtained by performing variance calculation on the power failure set, the reasonable coefficient is a numerical value reflecting the loss deviation degree of each transformer in the transformer group, the larger the numerical value of the reasonable coefficient is, the larger the damage deviation degree of each transformer in the transformer group is represented, and the reasonable threshold HLmax is obtained through the storage module, compare the reasonable coefficient HL with a reasonable threshold HLmax: if the reasonable coefficient HL is smaller than the reasonable threshold value HLmax, judging that the distribution arrangement mode of the current transformer bank is reasonable, and sending a reasonable signal to the monitoring management platform by the service life analysis module; if the reasonable coefficient HL is larger than or equal to the reasonable threshold value HLmax, the distribution arrangement mode of the current transformer bank is judged to be unreasonable, the service life analysis module sends unreasonable signals to the monitoring management platform, the monitoring management platform sends the received unreasonable signals to a mobile phone terminal of a manager, the manager replans the distribution arrangement mode of the transformer bank after receiving the unreasonable signals, the loss degree and the aging speed of each transformer can be closer after the transformers are reasonably arranged, therefore, the transformers in a batch can be uniformly replaced and maintained, the working time period before the transformers in the batch are collectively aged is relatively small in potential safety hazard, and therefore the safety monitoring prevention cost of the transformers is low.
A transformer monitoring and management system based on big data analysis is characterized in that when the transformer monitoring and management system works, an operation analysis module is used for detecting and analyzing the operation state of a transformer, and sending an early warning signal to a monitoring and management platform when the operation state of an analysis object is unqualified; the method comprises the steps that operation coefficients of analysis objects are monitored in real time after yellow signal lamps are turned on, the corresponding analysis objects are marked as dangerous objects when the analysis objects are in dangerous operation states, operation dangerous signals are sent to a monitoring management platform by an operation analysis module, the operation dangerous signals are sent to an early warning module and a controller by the monitoring management module after the operation dangerous signals are received by the early warning module, red signal lamps are controlled to be turned on after the operation dangerous signals are received by the early warning module, circuits of the analysis objects are cut off after the operation dangerous signals are received by the controller, descending signals are generated after the circuits of the analysis objects are cut off by the controller and are sent to the monitoring management platform, and the descending signals are sent to a storage module by the monitoring management platform after the descending signals are received by the monitoring management platform; after the storage module receives the value reduction signal, the storage module replaces the outage threshold value DDi with the value of the new outage threshold value DXi of the dangerous object, the storage module sends a service life analysis signal to the service life analysis module through the monitoring management platform after replacement is completed, the service life analysis module receives the service life analysis signal and then analyzes and judges whether the residual service life of the transformer meets the requirements and whether the distribution arrangement mode of the transformer is reasonable or not, and a manager receives an unreasonable signal and then replans the distribution arrangement mode of the transformer set, so that unified replacement and maintenance can be performed on the transformers in a batch, the working time period before the transformers in the batch are aged collectively is relatively small in potential safety hazard, and therefore the safety monitoring prevention cost of the transformers is low.
The foregoing is merely illustrative and explanatory of the present invention and various modifications, additions or substitutions may be made to the specific embodiments described by those skilled in the art without departing from the scope of the invention as defined in the accompanying claims.
The formulas are obtained by acquiring a large amount of data and performing software simulation, and the coefficients in the formulas are set by the technicians in the field according to actual conditions; such as: formula YXi = α 1 × YWi + α 2 × ZDi + α 3 × ZSi; collecting multiple groups of sample data and setting corresponding operation coefficients for each group of sample data by a person skilled in the art; substituting the set operation coefficient and the acquired sample data into formulas, forming a ternary linear equation set by any three formulas, screening the calculated coefficients and taking the mean value to obtain values of alpha 1, alpha 2 and alpha 3 which are respectively 4.52, 2.68 and 2.27;
the size of the coefficient is a specific numerical value obtained by quantizing each parameter, so that the subsequent comparison is convenient, and the size of the coefficient depends on the number of sample data and the corresponding operation coefficient is preliminarily set for each group of sample data by a person skilled in the art; it is sufficient if the proportional relationship between the parameter and the quantized value is not affected, for example, the operation coefficient is proportional to the value of the vibration data.
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to 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 invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. 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 to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise forms 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 utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (7)
1. A transformer monitoring and management system based on big data analysis comprises a monitoring and management platform and is characterized in that the monitoring and management platform is in communication connection with an operation analysis module, an early warning module, a service life analysis module, a storage module and a controller;
the early warning module comprises a red signal lamp for indicating emergency power failure, a yellow signal lamp for indicating abnormal operation and a green signal lamp for indicating normal operation;
the operation analysis module is used for detecting and analyzing the operation state of the transformer, sending an early warning signal to the monitoring management platform when the operation state of an analysis object is unqualified, sending the early warning signal to the early warning module after the monitoring management platform receives the early warning signal, and controlling the yellow signal lamp to be turned on after the early warning module receives the early warning signal;
the method comprises the steps that operation coefficients of analysis objects are monitored in real time after yellow signal lamps are turned on, the corresponding analysis objects are marked as dangerous objects when the analysis objects are in dangerous operation states, operation dangerous signals are sent to a monitoring management platform by an operation analysis module, the operation dangerous signals are sent to an early warning module and a controller by the monitoring management module after the operation dangerous signals are received by the early warning module, red signal lamps are controlled to be turned on after the operation dangerous signals are received by the early warning module, circuits of the analysis objects are cut off after the operation dangerous signals are received by the controller, descending signals are generated after the circuits of the analysis objects are cut off by the controller and are sent to the monitoring management platform, and the descending signals are sent to a storage module by the monitoring management platform after the descending signals are received by the monitoring management platform;
and the service life analysis module is used for analyzing and judging whether the residual service life of the transformer meets the requirement.
2. The transformer monitoring and management system based on big data analysis according to claim 1, wherein the specific process of the operation analysis module for performing detection and analysis on the operation state of the transformer comprises: the method comprises the steps of marking a transformer to be detected and analyzed as an analysis object i, wherein i =1, 2, …, n and n are positive integers, obtaining oil temperature data YWi, vibration data ZDi and noise data ZSi when the analysis object i works, obtaining an operation coefficient YXi by carrying out numerical calculation on the oil temperature data YWi, the vibration data ZDi and the noise data ZSi when the analysis object i works, obtaining an operation threshold YXmax through a storage module, comparing the operation coefficient YXi of the analysis object i with the operation threshold YXmax, and judging whether the operation state of the analysis object is qualified or not according to the comparison result.
3. The transformer monitoring and management system based on big data analysis as claimed in claim 2, wherein the obtaining process of the oil temperature data YWi of the analysis object i comprises: acquiring an oil temperature value of an analysis object i, acquiring an oil temperature standard value through a storage module, and marking an absolute value of a difference value of the oil temperature value and the oil temperature standard value as oil temperature data YWi;
the acquisition process of the vibration data ZDi of the analysis object i includes: marking the maximum vibration frequency of the analysis object i in L1 seconds as vibration data ZDi;
the acquisition process of the noise data ZSi of the analysis object i includes: the maximum decibel value of noise generated by the analysis subject i within L1 seconds is labeled as noise data ZSi.
4. The transformer monitoring and management system based on big data analysis according to claim 2, wherein the comparison process between the operation coefficient YXi and the operation threshold YXmax comprises:
if the analysis object with the operation coefficient YXi not smaller than the operation threshold YXmax exists, judging that the operation state of the analysis object i is unqualified;
if the analysis object with the operation coefficient YXi not smaller than the operation threshold YXmax does not exist, the operation state of the analysis object i meets the requirement, the operation analysis module sends an operation qualified signal to the monitoring management platform, the monitoring management platform sends the operation qualified signal to the early warning module after receiving the operation qualified signal, and the early warning module controls the green signal lamp to be turned on after receiving the operation qualified signal.
5. The transformer monitoring and management system based on big data analysis as claimed in claim 2, wherein the process of determining the dangerous object comprises: acquiring a power failure threshold value DDi of an analysis object i through a storage module, and comparing an operation coefficient YXi of the analysis object i with the power failure threshold value DDi:
if the analysis object with the operation coefficient YXi being greater than or equal to the outage threshold value DDi exists, judging that the operation state of the analysis object is dangerous, and marking the corresponding analysis object as a dangerous object;
if there is no analysis object whose operation coefficient YXi is equal to or greater than the power-off threshold DDi, it is determined that the operation state of the analysis object is safe.
6. The transformer monitoring and management system based on big data analysis as claimed in claim 5, wherein the storage module re-assigns the outage threshold value DDi of the dangerous object to obtain a new outage threshold value DXi after receiving the degradation signal, the assignment formula of the outage threshold value DXi is DXi = txddi, where t is a scaling coefficient and t is 0.92 ≤ t ≤ 0.96, replaces the outage threshold value DDi with the value of the new outage threshold value DXi of the dangerous object, sends the lifetime analysis signal to the monitoring and management platform after the replacement is completed, and sends the lifetime analysis signal to the lifetime analysis module after the monitoring and management platform receives the lifetime analysis signal.
7. The transformer monitoring and management system based on big data analysis according to claim 6, wherein the specific process of the life analysis module analyzing whether the remaining life of the transformer meets the requirement includes: acquiring a power-off threshold value DDi of an analysis object i, acquiring a service life threshold value DDmin through a storage module, and comparing the power-off threshold value DDi of the analysis object i with the service life threshold value DDmin one by one:
if the power failure threshold value DDi of the analysis object i is less than or equal to the service life threshold value DDmin, judging that the residual service life of the corresponding analysis object does not meet the requirement, and marking the corresponding analysis object as a replacement object;
if the power-off threshold value DDi of the analysis object i is larger than the service life threshold value DDmin, judging that the residual service life of the corresponding analysis object meets the requirement, and marking the corresponding analysis object as a reserved object;
if the number of the replacing objects is not zero after the comparison is finished, generating replacing signals and sending the replacing signals to a monitoring management platform, sending the received replacing signals to a mobile phone terminal of a manager by the monitoring management platform, and replacing the replacing objects after the manager receives the replacing signals;
and after the comparison is finished, if the number of the replacing objects is zero, whether the distribution arrangement mode of the transformer bank is reasonable or not is analyzed.
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