CN110729813A - Intelligent operation and maintenance and full life cycle management method for transformer substation and cloud management platform - Google Patents
Intelligent operation and maintenance and full life cycle management method for transformer substation and cloud management platform Download PDFInfo
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- CN110729813A CN110729813A CN201910832213.3A CN201910832213A CN110729813A CN 110729813 A CN110729813 A CN 110729813A CN 201910832213 A CN201910832213 A CN 201910832213A CN 110729813 A CN110729813 A CN 110729813A
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Abstract
The invention relates to the field of state evaluation of power sequential equipment, in particular to a management method for intelligent operation and maintenance and a full life cycle of a transformer substation. According to the cloud management platform on the intelligent operation and maintenance and full life cycle of the transformer substation, the service life evaluation and the quantitative evaluation of the overload capacity of the oil-immersed power transformer in the transformer substation are realized by applying the management method of the intelligent operation and maintenance and the full life cycle of the transformer substation.
Description
Technical Field
The invention relates to the field of power primary equipment state evaluation, in particular to a transformer substation intelligent operation and maintenance and full life cycle management method and a transformer substation intelligent operation and maintenance and full life cycle cloud management platform applying the method.
Background
Along with the enlargement of the scale of a power grid and the increase of the number of power transmission and transformation equipment, the informatization degree of the equipment is higher and higher, the equipment state monitoring system is increasingly popularized, and the requirement of a user on the power supply reliability is also continuously improved. However, a large amount of historical operation data of the existing online monitoring system for the power transmission and transformation equipment are not effectively utilized, the data contain important information of the operation state of the power transmission and transformation equipment, the potential value of the data needs to be developed urgently, the data can be applied to analyzing the operation state trend of the power transmission and transformation equipment, decision support is provided for maintenance and overhaul of the power transmission and transformation equipment, the probability of abnormity of the power transmission and transformation equipment is reduced, and the power supply reliability is improved.
At present, under a large operation mode of a power grid, monitoring of operation states of main equipment of a transformer substation faces outstanding problems and challenges of safety risk, heavy construction tasks, weak monitoring technology and the like. How to effectively monitor the running state of the main equipment of the transformer substation, reduce the operation and maintenance workload, relieve the personnel pressure, and improve the centralized monitoring work efficiency and the intelligent level becomes an important problem in the intelligent construction of the transformer substation at present.
Along with the development of the intellectualization of primary equipment of a transformer substation, an operation parameter monitoring device, a protection device and equipment of the primary equipment develop towards the integration direction, so that the primary equipment has the functions of self-monitoring and protection, and necessary conditions are provided for introducing a regulation and control system for state information of primary main equipment. The primary main equipment information is effectively combined with the monitoring and protecting information of the power grid, and the early warning of equipment faults and the stable operation of the power grid can play an important role.
The state evaluation is a technical means for acquiring the running state of the equipment, and is an important information source for overhauling, operating and maintaining. The intelligent monitoring system adopts an informatization technology, a monitoring device of an advanced sensing technology is installed on a transformer of a transformer substation, multi-parameter monitoring is carried out on equipment, data are collected in real time, multi-information comprehensive analysis is carried out, intellectualization and informatization of power transmission and transformation equipment are achieved, and the purposes of self-perception of the running state of the equipment and automatic fault diagnosis are achieved. However, for an operating substation, as the original primary equipment cannot be completely abandoned like a newly-built substation, the invention adopts a scheme that neither an intelligent sensor of the existing equipment nor additional intelligent electronic equipment is added on the original primary equipment, but key state quantity information of the integrated protection measurement and control background of the substation and the online monitoring device accessed by a third party is directly obtained, and online state monitoring, intelligent diagnosis and equipment full-life cycle management of important primary equipment (such as a power transformer, a high-voltage switch and the like) of the substation are realized by presetting an expert system diagnostic algorithm. The method can avoid a large amount of basic data synchronous work or repeated maintenance work with low efficiency and low reliability, greatly reduce the information flow between systems and effectively avoid the waste of software and hardware resources. By means of a nondestructive and non-invasive technical means, the availability and reliability of electric energy are improved to the maximum extent, and the safety, reliability and economy of a power grid are improved.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, provides a transformer substation intelligent operation and maintenance and full-life-cycle management method and a cloud management platform, and realizes state monitoring and intelligent diagnosis of an oil-immersed power transformer of a transformer substation by adopting a nondestructive and non-invasive technical means and a preset intelligent algorithm.
In order to achieve the purpose, the invention adopts the following technical scheme:
a transformer substation intelligent operation and maintenance and full life cycle management method comprises the following steps:
step 1, acquiring equipment data of primary power equipment of a transformer substation, wherein the equipment data comprises equipment basic data and factory test data, and the primary power equipment comprises an oil-immersed power transformer; acquiring comprehensive protection data and measurement and control data of the oil-immersed power transformer from a comprehensive and measurement and control background of a transformer substation; acquiring environmental data of the environment where the oil-immersed power transformer is located from an environmental temperature controller;
the equipment basic data and factory test data comprise temperature rise delta theta of winding hot spot temperature to top layer oil temperature under rated current of the oil-immersed power transformerhrConstant k of thermal model21And k22Time constant of winding τWTime constant of oil temperature τORated current INAnd a winding index y;
the comprehensive protection data and the measurement and control data comprise load current I of the oil-immersed power transformer and top oil temperature theta of the transformero(ii) a The environmental data comprises the environmental temperature theta of the environment where the oil-immersed power transformer is locateda；
Step 2, comprising step 21;
step 21, predicting the residual life of the oil-immersed power transformer by an intelligent algorithm according to the data acquired in the step 1, specifically as follows:
the initial state of service life loss of the oil-immersed power transformer is L(0)；
Initial hot spot temperature rise first term:
Δθh1(0)＝k21×ΔθhrKy；
initial hot spot temperature rise second term:
Δθh2(0)＝(k21-1)×ΔθhrKy；
calculating the winding hot spot temperature theta with the nth sampling period being t according to the differential equation formula of the hot spot temperature riseh(n)N is an integer and n is not less than 1,
the hot spot temperature rise of the nth sampling period is the first term:
Δθh1(n)＝Δθh1(n-1)+DΔθh1(n)，
wherein the content of the first and second substances,
second term of hot spot temperature rise of nth sampling period:
Δθh2(n)＝Δθh2(n-1)+DΔθh2(n)，
wherein the content of the first and second substances,
and when the nth sampling period is finished, the winding hot spot temperature increases the temperature of the oil temperature of the top layer:
Δθh(n)＝Δθh1(n)-Δθh2(n)；
at the end of the nth sampling period, the winding hot spot temperature:
θh(n)＝θo+Δθh(n)；
wherein, K is a load factor, and K is a load current I/rated current IN；
Calculating the residual life of the oil-immersed power transformer according to the calculated winding hot spot temperature, wherein the specific calculation process is as follows:
at the end of the nth sampling period, the relative aging rate V of the sampling periodnThe calculation formula of (2) is as follows:
L(n)＝L(n-1)+V(n)×Dt
calculating the remaining life L of the oil-immersed power transformer (1) from the loss of lifeResidual lifeThe calculation formula is as follows:
Lresidual life＝LDesign life-L(n)；
Wherein L isDesign lifeThe service life of the oil-immersed power transformer (1) is designed.
Preferably, step 2 further comprises step 22;
step 22, quantitatively evaluating the overload capacity of the oil-immersed power transformer through an intelligent algorithm, wherein the step 22a and the step 22b are included:
step 22a, after each sampling period is finished, according to the maximum temperature limit requirement of the oil-immersed power transformer, the load current I and the top oil temperature theta of the transformeroLoad factor K and winding hot spot temperature theta calculated in step 21h(n)Judging the load type of the oil-immersed power transformer through a segmented threshold algorithm, wherein the load type comprises a normal periodic load,Short-term first-aid load and long-term first-aid periodic load;
step 22b, quantitatively giving the oil temperature theta of different transformer top layers before the oil immersed power transformer is overloaded according to the load type of the oil immersed power transformeroCorresponding to the maximum continuous operation time T under the normal overload multipleMAXAnd generating corresponding equipment overhaul recommendations.
Preferably, in step 22a, when the winding hot spot temperature θ is higher than the predetermined valueh(n)＜X1And 0 < X1130 or less, top oil temperature thetao＜Y1And 0 < Y1Less than or equal to 115 percent, and the maximum load coefficient K is Z1And 0 < Z1When the load type is less than or equal to 1.3, judging that the load type of the oil-immersed power transformer is a normal periodic load;
when winding hot spot temperature X1≤θh(n)＜X2And 130 < X2160 or less, top oil temperature thetao＜Y1The maximum load factor K is Z1Judging the load type of the oil-immersed power transformer to be a long-term first-aid periodic load;
when the maximum load factor K is Z2And 1.3 < Z2And when the load type is less than or equal to 1.5, judging that the load type of the oil-immersed power transformer is a short-term emergency load.
Preferably, in step 21, the top layer oil temperature θ of the oil-immersed power transformer is0The method comprises the steps that the top oil temperature is measured through a top oil temperature probe, and the top oil temperature probe continuously monitors the top oil temperature in the subsequent operation process of the oil-immersed power transformer to obtain a top oil temperature detection value; at the same time, by the ambient temperature θaAnd load current I, and top layer oil steady-state temperature rise delta theta under rated loss included by combining equipment basic data and factory test dataorConstant k of thermal model11Oil time constant τORated current, ratio R of load loss to no-load loss under rated current, and rated current INAnd calculating the oil index x of the total loss to the top oil temperature to obtain a top oil temperature calculated value thetaC：
Initial top oil temperature calculation θC(0)：
At the end of the nth sampling period, the calculated value of the top layer oil temperature is thetaC(n)：
θC(n)＝θC(n-1)+DθC(n),
Wherein the content of the first and second substances,
if the detected top oil temperature value and the calculated top oil temperature value thetaCIf the numerical difference is larger than or equal to m and m is larger than 0, whether the top oil temperature probe works normally is detected.
A cloud management platform on intelligent operation and maintenance and full life cycle of a transformer substation comprises an integrated protection and control background for acquiring integrated protection data and control data of the transformer substation, an environment temperature controller for acquiring environment data and a telemechanical, wherein the integrated protection and control background and the environment temperature controller are respectively connected with the telemechanical, and the telemechanical is connected with a cloud server end through a network;
the cloud server end is internally preset with equipment data of the primary power equipment; the cloud server side executes the intelligent substation operation and maintenance and full-life-cycle management method as claimed in any one of claims 1 to 4.
Preferably, the system also comprises a third-party online monitoring device for acquiring third-party monitoring data, wherein the third-party online monitoring device at least comprises a device for monitoring dissolved gas in oil, a device for monitoring iron core grounding current, a device for monitoring sleeve insulation, a device for monitoring partial discharge, a device for detecting micro water and a device for monitoring on-load tap-changer, which are respectively connected with the telemechanical.
Preferably, the cloud server includes a Web server, and the Web server provides a uniform Web release to the user side, and at least provides the following functions: unified authority management, equipment parameter integrated management, unified report management, unified graph release, a system notification mechanism and Web browsing; the cloud server side further comprises a database server used for storing the collected data and the equipment data.
Preferably, the user side can be a smart phone side, and/or a tablet computer side, and/or a PC side;
the comprehensive protection data and the measurement and control data comprise remote measurement data and remote signaling data; the remote measurement data comprises high-voltage side voltage/current, low-voltage side voltage/load current, active power, reactive power, a power factor and transformer top layer oil temperature; the remote communication data comprises a body gas alarm and trip signal, a body pressure release valve alarm and trip signal, a body oil level gauge high and low oil level, an on-load tap-changer gas alarm and trip signal, an on-load tap-changer pressure release valve alarm and trip signal, an on-load tap-changer oil level gauge high and low oil level and a fan starting/fault signal;
the equipment data also comprises daily maintenance data and overhaul record data;
the third-party monitoring data comprises monitoring data of gas dissolved in oil, detection data of iron core grounding current, detection data of sleeve insulation, detection data of partial discharge, detection data of micro water and detection data of an on-load tap-changer;
the cloud server side provides uniform Web release for the user side through the Web server, and the user can check the comprehensive protection data, the measurement and control data, the equipment data and the third-party monitoring data through the user side.
The intelligent operation and maintenance and full life cycle management method for the transformer substation adopts a nondestructive and non-invasive technical means, namely, a technical scheme that an intelligent sensor of existing transformer substation equipment is not replaced, and extra intelligent electronic equipment is not additionally arranged on an original oil-immersed power transformer is adopted, data are directly obtained from an integrated protection measurement and control background and an ambient temperature controller of the transformer substation, and state monitoring and intelligent diagnosis of the oil-immersed power transformer of the transformer substation are realized through a preset intelligent algorithm.
According to the intelligent operation and maintenance and full-life-cycle management platform for the transformer substation, the intelligent operation and maintenance and full-life-cycle management method for the transformer substation is adopted to realize state monitoring and intelligent diagnosis of the oil-immersed power transformer, a nondestructive and non-invasive technical means is adopted, namely, a technical scheme that an intelligent sensor of existing transformer substation equipment is not replaced, and extra intelligent electronic equipment is not additionally arranged on the original oil-immersed power transformer is not adopted, and the online state monitoring and intelligent diagnosis of the oil-immersed power transformer of the transformer substation are directly carried out from an integrated protection measurement and control background of the transformer substation.
In addition, the access of a third-party online monitoring device is supported, the key state quantity information of the oil-immersed power transformer is obtained, and the full life cycle management of the oil-immersed power transformer of the transformer substation is realized through a unified platform.
In addition, the remote motivation synthesizes, screens and arranges the sequence table for the acquired data, thereby avoiding a large amount of basic data synchronization work or repeated maintenance work with low efficiency and low reliability, greatly reducing the information flow among systems and effectively avoiding the waste of hardware resources.
Drawings
FIG. 1 is a schematic structural diagram of a cloud management platform on intelligent operation and maintenance and a full life cycle of a transformer substation according to the invention;
FIG. 2 is a schematic diagram of the overall design architecture of a networked graphical interface of a cloud management platform on the intelligent operation and maintenance and full life cycle of a transformer substation according to the present invention;
FIG. 3 is a step of equipment health assessment of the intelligent operation and maintenance and full-life cycle management method of the substation of the present invention;
fig. 4 is a modular schematic diagram of the cloud management platform on the intelligent operation and maintenance and full life cycle of the substation.
Detailed Description
The following further describes specific embodiments of the transformer substation intelligent operation and maintenance and full-life-cycle management method, device and cloud management platform according to the embodiments shown in fig. 1 to 4. The intelligent operation and maintenance and full life cycle management method, device and cloud management platform for the transformer substation are not limited to the description of the following embodiments.
The invention discloses a cloud management platform on intelligent operation, maintenance and full life cycle of a transformer substation, which comprises an integrated protection measurement and control background for acquiring integrated protection data and environmental measurement data of the transformer substation, an environment temperature controller for acquiring environment data and a telemechanical, wherein the integrated protection measurement and control background and the environment temperature controller are respectively connected with the telemechanical, and the telemechanical is connected with a cloud server through a network; the cloud server end is internally preset with equipment data of the primary power equipment;
the equipment data comprise equipment basic data and factory test data, the primary power equipment comprises an oil-immersed power transformer, and the equipment basic data and the factory test data comprise temperature rise delta theta of winding hot spot temperature to top layer oil temperature under rated current of the oil-immersed power transformerhrConstant k of thermal model21And k22Time constant of winding τWTime constant of oil temperature τORated current INAnd a winding index y;
the comprehensive protection data and the measurement and control data comprise load current I of the oil-immersed power transformer and top oil temperature theta of the transformero；
The environmental data comprises the environmental temperature theta of the environment where the oil-immersed power transformer is locateda；
The cloud server side executes the intelligent operation and maintenance and full life cycle management method of the transformer substation, and the method comprises the following steps of 21:
step 21, the cloud server side predicts the residual life of the oil-immersed power transformer through an intelligent algorithm according to the acquired data, and the method specifically comprises the following steps:
the initial state of service life loss of the oil-immersed power transformer is L(0)；
Initial hot spot temperature rise first term:
Δθh1(0)＝k21×ΔθhrKy；
initial hot spot temperature rise second term:
Δθh2(0)＝(k21-1)×ΔθhrKy；
step 2A1, calculating the winding hot spot temperature theta with the nth sampling period being t according to the differential equation formula of the hot spot temperature riseh(n)N is an integer and n is not less than 1,
the hot spot temperature rise of the nth sampling period is the first term:
Δθh1(n)＝Δθh1(n-1)+DΔθh1(n)，
wherein the content of the first and second substances,
second term of hot spot temperature rise of nth sampling period:
Δθh2(n)＝Δθh2(n-1)+DΔθh2(n)，
wherein the content of the first and second substances,
and when the nth sampling period is finished, the winding hot spot temperature increases the temperature of the oil temperature of the top layer:
Δθh(n)＝Δθh1(n)-Δθh2(n)；
at the end of the nth sampling period, the winding hot spot temperature:
θh(n)＝θo+Δθh(n)；
wherein, K is a load factor, and K is a load current I/rated current IN；
Calculating the residual life of the oil-immersed power transformer according to the calculated winding hot spot temperature, wherein the specific calculation process is as follows:
at the end of the nth sampling period, the relative aging rate V of the sampling periodnThe calculation formula of (2) is as follows:
relative aging rate V according to the sampling periodnCalculating the life loss L of the oil-immersed power transformer (1) in the sampling periodnThe calculation formula is as follows:
L(n)＝L(n-1)+V(n)×Dt
calculating oil-immersed power transformer from life loss (1) Residual life L ofResidual lifeThe calculation formula is as follows:
Lresidual life＝LDesign life-∑Ln；
Wherein L isDesign lifeThe design life of the oil-immersed power transformer (1) is prolonged;
step 22, the cloud server side carries out quantitative evaluation on the overload capacity of the oil-immersed power transformer through an intelligent algorithm, and the method comprises the following steps of 22a and 22 b:
step 22a, after each sampling period is finished, according to the maximum temperature limit requirement of the oil-immersed power transformer, the load current I and the top oil temperature theta of the transformeroLoad factor K and calculated winding hot spot temperature thetah(n)Judging the load type of the oil-immersed power transformer through a segmented threshold algorithm, wherein the load type comprises a normal periodic load, a short-term emergency load and a long-term emergency periodic load;
step 22b, quantitatively giving the oil temperature theta of different transformer top layers before the oil immersed power transformer is overloaded according to the load type of the oil immersed power transformeroCorresponding to the maximum continuous operation time T under the normal overload multipleMAXAnd generating corresponding equipment overhaul recommendations.
The intelligent operation and maintenance and full-life cycle management device for the transformer substation adopts a nondestructive and non-invasive technical means, namely a technical means of directly acquiring key state quantity information of the oil-immersed power transformer from an integrated protection measurement and control background of the transformer substation without replacing an intelligent sensor of the existing transformer substation equipment or additionally installing additional intelligent electronic equipment on the original oil-immersed power transformer, and realizes the residual life prediction of the oil-immersed power transformer and the overload quantitative evaluation of the oil-immersed power transformer according to the acquired data through the intelligent operation and maintenance and full-life cycle management method of the transformer substation, thereby maximally improving the availability and reliability of electric energy and improving the safety, reliability and economy of a power grid.
It should be noted that, for newly purchased oil-immersed power transformer, the initial state of life loss isState L(0)The value is 0.
Preferably, the remote motivation is used for synthesizing, screening and sequencing the acquired data, so that a large amount of low-efficiency and low-reliability basic data synchronization work or repeated maintenance work is avoided, the information flow between systems is greatly reduced, and the waste of hardware resources is effectively avoided.
Preferably, the cloud server includes a Web server, and the Web server provides a unified Web release to the user side, and at least provides the following functions: unified authority management, equipment parameter integrated management, unified report management, unified graph release, a system notification mechanism and Web browsing; the cloud server side also comprises a database server used for storing the acquired data and the equipment data; the cloud server end comprises an application server, and an intelligent algorithm is preset in the application server and used for predicting the residual life of the oil-immersed power transformer and quantitatively evaluating the overload capacity of the oil-immersed power transformer. Furthermore, the user side can be a smart phone side, and/or a tablet computer side, and/or a PC side. Further, the device data can be input or imported into the cloud server side through the user side. Furthermore, the cloud server provides uniform Web release for the user side through the Web server, and the user can check the comprehensive protection data, the measurement and control data, the equipment data and the third-party monitoring data through the user side.
Preferably, the application server side can draw a remaining life graph and a table according to the predicted value of the remaining life of the oil-immersed power transformer so as to be visually displayed on the user side.
Fig. 1-4 show an embodiment of a cloud management platform for intelligent operation and maintenance and full life cycle of a substation according to the present invention.
As shown in fig. 1, the cloud management platform for intelligent operation and maintenance and full life cycle of a transformer substation of the present invention includes:
the data acquisition layer comprises a transformer substation integrated protection measurement and control background, an ambient temperature controller and a third party online monitoring device and is used for acquiring integrated protection data, measurement and control data, environmental data and third party online monitoring data of a transformer substation.
Preferably, the integrated protection data and the measurement and control data comprise telemeasuring data and teletraffic data. The telemetry data includes high side voltage/current, low side voltage/load current, active power, reactive power, power factor, and transformer top layer oil temperature. The remote communication data comprises a body gas alarm and trip signal, a body pressure release valve alarm and trip signal, a body oil level gauge high and low oil level, an on-load tap-changer gas alarm and trip signal, an on-load tap-changer pressure release valve alarm and trip signal, an on-load tap-changer oil level gauge high and low oil level and a fan starting/fault signal; load current I of oil-immersed power transformer and top layer oil temperature theta of oil-immersed power transformero。
The environmental data includes an ambient temperature θ of an environment in which the electric primary equipment is locatedaE.g. ambient temperature theta of the environment in which the oil-filled power transformer is locateda。
The third-party monitoring data comprises medium dissolved gas monitoring data, iron core grounding current monitoring data, sleeve insulation monitoring data, partial discharge monitoring data, micro water detection data and on-load tap-changer monitoring data.
And the data integration layer comprises a remote motivation and is used for synthesizing, screening and sequencing the acquired data. It should be pointed out that the remote motivation is a remote detection and control technology capable of realizing power system scheduling, which can convert the operation conditions (including on-off states and equipment operation data) of substations and users distributed at different positions and different types into a signal form convenient for transmission, and add protection measures to prevent external interference in the transmission process, and after data is modulated, the data is transmitted to a scheduling end through a special information channel, and a master station at the scheduling end is subjected to inverse modulation and is restored to original corresponding information to be displayed for monitoring by scheduling personnel; the above process actually involves telemetry, telecommand, remote control, and remote regulation. Of course, the control command of the dispatcher can also be transmitted to the controlled object at a remote place through a similar process.
The cloud client application layer comprises a client, and the device data of the power primary device can be preset into the cloud platform management layer through the client. Furthermore, the user side can be a smart phone side, and/or a tablet computer side, and/or a PC side. Furthermore, the user can check the comprehensive protection data, the measurement and control data, the equipment data and the third-party monitoring data through the user side. Specifically, a user can access a data center of a cloud server side through a transformer substation intelligent operation and maintenance on a user side and a cloud management platform APP on a full life cycle, and accesses a data center website of the cloud server side through a browser by means of a user name and a password.
The cloud platform management layer comprises a cloud server end and is used for classifying, processing and storing the acquired data, predicting the residual life of the oil-immersed power transformer by the intelligent operation and maintenance and full life cycle management method of the transformer substation, and quantitatively evaluating the overload of the oil-immersed power transformer. Further, the cloud server side comprises a Web server, an application server and a database server.
Preferably, the cloud server includes a Web server, and the Web server provides uniform Web publishing to the user side, and can flexibly display various models, graphs, data and system setting functions generated by the cloud server to the user, including but not limited to uniform authority management, device parameter integration management, uniform report management, uniform graph publishing, system notification mechanism and Web browsing. Furthermore, the Web server is a comprehensive release platform, a B/S program system architecture based on Web is adopted, a user can conveniently inquire and browse a networked graphical interface by adopting various cloud client modes, and the user only needs to install a common browser without any other special or customized software.
Preferably, the database server is used for storing the data collected by the data collection layer and the data imported into the cloud server through the user side. Further, the database server is a network database server and is used for classifying and storing the acquired data, after the cloud platform management layer classifies and stores the acquired data, the application server runs an intelligent algorithm preset in the application server, residual life prediction, overload capacity quantitative evaluation, cooling system intelligent monitoring and equipment alarm information processing are carried out on the power transformer, an equipment health evaluation result is obtained, and an equipment maintenance suggestion is generated. Furthermore, the cloud platform management layer stores data in a classified manner, including an RDBMS (relational database management system), a MySQL database, and a distributed file storage.
The cloud server end can visually display the three-dimensional entity graph of the oil-immersed power transformer through the user end, and analog alarm lamps are arranged in all the parts of the oil-immersed power transformer, so that the red color represents an alarm signal, and the green color represents normal operation. When the application server of the cloud server side processes the equipment alarm information, according to remote communication data of third-party monitoring data, when a monitored value exceeds a preset threshold value, an alarm or trip signal is given, for example, when the gas content of the body is higher than the preset threshold value, the corresponding alarm lamp can display red, and when the gas content of the body is lower than the preset threshold value, the corresponding alarm lamp displays green, so that a user can visually observe and process alarm information conveniently.
It should be noted that the cloud server can also monitor the cooling system, and control and set the cooling mode, the cooling system arrangement and combination mode, and the cooling system running time of the cooling system to indicate the normal/fault running state of the cooling system.
Fig. 2 shows a software networking graphical interface overall framework of the cloud management platform on the intelligent operation and maintenance and full life cycle of the transformer substation.
The software networking graphical interface overall framework comprises map navigation, equipment ledger, overview, state evaluation, maintenance record and safety management; the equipment standing book comprises nameplate information, spare parts and inspection records, the overview comprises measurement quantity and state quantity, the state evaluation comprises residual life prediction, overload evaluation, cooling system monitoring and a third party online monitoring device, the maintenance records comprise installation guidance, maintenance logs and fault logs, and the safety management comprises user management and historical data.
It should be noted that when the user accesses the cloud management platform on the intelligent operation and maintenance and full life cycle of the transformer substation, the software networking graphical interface shown in fig. 2 can be displayed, and corresponding browsing and operation can be performed. Furthermore, the software networking graphical interface overall framework is developed by using a Strurs2MVC framework, and a neat Web application program framework realized by an MVC design mode is provided; after a user logs in the system, data are screened according to user permissions and are respectively displayed to overhaul managers, overhaul technicians, equipment experts and equipment manufacturers, so that users with different permissions can conveniently browse the health state of equipment, the service life assessment of the equipment, overhaul suggestions, real-time online monitoring data, basic data of the equipment and the like at any time and any place, and the data can be displayed through the forms of an equipment model, a service life curve, a data table, a data trend graph, a text description and the like.
Preferably, as shown in fig. 1, the cloud platform management layer interacts with the user side through a VPN private network established by a GPRS/3G/4G network.
It should be noted that, in the intelligent operation and maintenance and full life cycle cloud management platform for the transformer substation, a cloud platform management layer can be deployed on a commercial cloud platform or an enterprise cloud platform.
The cloud platform management layer is deployed on an enterprise cloud platform, a VPN remote access technology is adopted to realize the scheme that cloud client users at different sites in the whole country access cloud platform data, a PPTP tunnel is established by fully utilizing an enterprise-level router supporting a VPN server function, so that remote users can access the enterprise cloud platform safely by dialing in an ISP (Internet service provider) or directly connecting the Internet or other networks, and the specific flow of VPN remote access is as follows:
(1) the enterprise router establishes a VPN server, starts a PPTP tunnel function and opens different VPN connection user names and passwords of each substation;
(2) configuring a VPN server;
(3) configuring a non-repetitive network segment by the router;
(4) the router configuration establishes PPTP channel connection setting;
after the VPN connection is established, a network terminal user accesses an internal application system according to a preset authority, the network terminal user and the internal application system are isolated by adopting a firewall, and IP addresses and ports are filtered on the firewall.
The cloud platform management layer is deployed on a commercial cloud platform, the commercial cloud platform can be an Aries cloud, an Tencent cloud, a Baidu cloud and the like, the cloud platform management layer can reduce hardware cost and operation and maintenance cost and can utilize various application services provided by a cloud server provider, and the specific flow is as follows:
(1) purchasing and opening a commercial cloud server;
(2) installing TOMCAT, MySQL and other software;
(3) configuring a website operating environment;
(4) deploying the project to a Web server;
according to the intelligent operation and maintenance and full life cycle cloud management platform, the application program of the cloud management platform is completely deployed in the commercial cloud, and all corresponding components operate in the commercial cloud.
Preferably, the intelligent operation and maintenance and full life cycle cloud management platform of the transformer substation supports the functions of online printing of the residual life prediction result of the transformer and processing of the advice report, and also supports the functions of online printing of the overload evaluation result of the transformer and giving of the corresponding advice report. It should be noted that the intelligent operation and maintenance and full life cycle cloud management platform of the transformer substation can be connected with at least 3000 transformers, and the access amount of front-end users is not limited.
The invention also discloses a transformer substation intelligent operation and maintenance and full life cycle management method, which comprises the following steps:
step 1, acquiring equipment data of primary power equipment of a transformer substation, wherein the equipment data comprises equipment basic data and factory test data, and the primary power equipment comprises an oil-immersed power transformer; acquiring comprehensive protection data and measurement and control data of the oil-immersed power transformer from a comprehensive and measurement and control background of a transformer substation; acquiring environmental data of the environment where the oil-immersed power transformer is located from an environmental temperature controller;
the equipment basic data and factory test data comprise winding hot spot temperature to top layer of oil-immersed power transformer under rated currentTemperature rise delta theta of oil temperaturehrConstant k of thermal model21And k22Time constant of winding τWTime constant of oil temperature τORated current INAnd a winding index y;
the comprehensive protection data and the measurement and control data comprise load current I of the oil-immersed power transformer and top oil temperature theta of the transformero(ii) a The environmental data comprises the environmental temperature theta of the environment where the oil-immersed power transformer is locateda；
Step 2, comprising step 21 and step 22,
step 21, predicting the residual life of the oil-immersed power transformer according to the data acquired in the step 1, specifically as follows:
according to the GB/T1094.7 rule, the initial state of the service life loss of the oil-immersed power transformer is L(0)；
Initial hot spot temperature rise first term:
Δθh1(0)＝k21×ΔθhrKy；
initial hot spot temperature rise second term:
Δθh2(0)＝(k21-1)×ΔθhrKy；
calculating the winding hot spot temperature theta with the nth sampling period being t according to the differential equation formula of the hot spot temperature riseh(n)N is an integer and n is not less than 1,
the hot spot temperature rise of the nth sampling period is the first term:
Δθh1(n)＝Δθh1(n-1)+DΔθh1(n)，
wherein the content of the first and second substances,
second term of hot spot temperature rise of nth sampling period:
Δθ2(n)＝Δθh2(n-1)+DΔθh2(n)，
wherein the content of the first and second substances,
and when the nth sampling period is finished, the winding hot spot temperature increases the temperature of the oil temperature of the top layer:
Δθh(n)＝Δθh1(n)-Δθh2(n)；
at the end of the nth sampling period, the winding hot spot temperature:
θh(n)＝θo+Δθh(n)；
wherein, K is a load factor, and K is a load current I/rated current IN；
Calculating the residual life of the oil-immersed power transformer according to the calculated winding hot spot temperature, wherein the specific calculation process is as follows:
at the end of the nth sampling period, the relative aging rate V of the sampling periodnThe calculation formula of (2) is as follows:
relative aging rate V according to the sampling periodnCalculating the life loss L of the oil-immersed power transformer (1) in the sampling periodnThe calculation formula is as follows:
L(n)＝L(n-1)+V(n)×Dt
calculating the remaining life L of the oil-immersed power transformer (1) from the loss of lifeResidual lifeThe calculation formula is as follows:
Lresidual life＝LDesign life-L(n)；
That is, the remaining life L of the oil-filled power transformer 1Residual lifeDesign life L of oil-immersed power transformer 1Design lifeThe sum of the lost lives of the oil-immersed transformers after the end of each sampling period (i.e. the sum of the lost lives of the oil-immersed power transformers 1 after the end of the nth sampling period is
)。
Wherein L isDesign lifeIs oilThe design life of the immersed power transformer (1);
preferably, in step 21, the top oil temperature θoThe method is calculated according to the following calculation formula:
θo(n)＝Dθo(n)+θo(n-1)。
preferably, in step 21, the top oil temperature θoIs measured by a top oil temperature probe in real time.
Step 22, performing quantitative assessment on the overload of the oil-immersed power transformer, wherein the quantitative assessment includes steps 22a and 22 b:
step 22a, after each sampling period is finished, according to the maximum temperature limit requirement of the oil-immersed power transformer, the load current I and the top oil temperature theta of the transformeroLoad factor K and winding hot spot temperature theta calculated in step 21h(n)Judging the load type of the oil-immersed power transformer through a segmented threshold algorithm, wherein the load type comprises a normal periodic load, a short-term emergency load and a long-term emergency periodic load;
step 22b, quantitatively giving the oil temperature theta of different transformer top layers before the oil immersed power transformer is overloaded according to the load type of the oil immersed power transformeroCorresponding to the maximum continuous operation time T under the normal overload multipleMAXAnd generating corresponding equipment overhaul recommendations.
Preferably, the maximum temperature limit requirement of the oil-immersed power transformer meets the maximum temperature limit requirement and the load current of the transformer specified in the DL/T572-2010 standard.
Preferably, in step 22a, when the winding hot spot temperature θ is higher than the predetermined valueh(n)＜X1And 0 < X1The temperature of the top oil is less than or equal to 130 DEG Co＜Y1And 0 < Y1Not more than 115 ℃ and the maximum load coefficient K is Z1And 0 < Z1When 1.3 is not more than, then judge that oil-immersed power transformer's load type is normal periodic load, the equipment overhaul suggestion of giving is:under the load type running state, the aging of the oil-immersed power transformer can be accelerated, but the insulation safety is not directly endangered, and the running time M of the oil-immersed power transformer can be more than or equal to 1 week;
when winding hot spot temperature X1≤θh(n)＜X2And X is less than 130 DEG C2The temperature of the top oil is less than or equal to 160 DEG Co＜Y1The maximum load factor K is Z1And judging that the load type of the oil-immersed power transformer is a long-term first-aid periodic load, wherein the given equipment overhaul suggestion is as follows: under the load type operation condition, the temperature of a winding hot spot of the oil-immersed power transformer can reach a dangerous degree, so that the insulation strength of the oil-immersed power transformer is temporarily reduced, and the oil-immersed power transformer is stopped to operate;
when the maximum load factor K is Z2And 1.3 < Z2When the load type is less than or equal to 1.5, judging that the load type of the oil-immersed power transformer is a short-term emergency load, and giving an equipment overhaul suggestion that: under the load type operation condition, the temperature of a winding hot spot of the oil-immersed power transformer can reach a dangerous degree, all coolers including a standby cooler are required to be put into the oil-immersed power transformer, the load is compressed, the operation time is reduced, the operation time of the oil-immersed power transformer can be M, and M is less than or equal to 0.5 h.
According to the intelligent operation and maintenance and full-life-cycle management method for the transformer substation, data are directly obtained from an integrated protection measurement and control background, an environment temperature controller and a third-party online monitoring device of the transformer substation through a technical scheme that a nondestructive and non-invasive technical means is adopted, namely, an intelligent sensor of existing equipment is not replaced, and additional intelligent electronic equipment is not additionally arranged on original primary equipment.
Preferably, in step 21, the top layer oil temperature θ of the oil-immersed power transformer isoThe method comprises the steps that the top oil temperature is measured through a top oil temperature probe, and the top oil temperature probe continuously monitors the top oil temperature in the subsequent operation process of the oil-immersed power transformer to obtain a top oil temperature detection value; at the same time, through the ringAmbient temperature thetaaAnd load current I, and top layer oil steady-state temperature rise delta theta under rated loss included by combining equipment basic data and factory test dataorConstant k of thermal model11Oil time constant τORated current, ratio R of load loss to no-load loss under rated current, and rated current INAnd calculating the oil index x of the total loss to the top oil temperature to obtain a top oil temperature calculated value thetaC：
Initial top oil temperature calculation θC(0)：
At the end of the nth sampling period, the calculated value of the top layer oil temperature is thetaC(n)：
θC(n)＝θC(n-1)+DθC(n),
Wherein the content of the first and second substances,
if the detected top oil temperature value and the calculated top oil temperature value thetaCIf the numerical difference is larger than or equal to m and m is larger than 0, whether the top oil temperature probe works normally is detected. Further, m may be any number between 0 and 10, m may be 10, and m may be any number greater than 10.
The method for evaluating the service life of the oil-immersed power transformer realizes accurate evaluation of the residual service life of the oil-immersed power transformer, prolongs the service life of the oil-immersed power transformer to the maximum extent, reduces the replacement frequency of the oil-immersed power transformer, saves the maintenance cost of a power grid, realizes comprehensive detection and diagnosis of winding hot spot temperature, temperature rise, service life, load and the like of the oil-immersed power transformer, and can ensure the normal operation of top oil temperature.
The following is a specific embodiment of predicting the residual life of the oil-immersed power transformer by using the intelligent operation and maintenance and full life cycle management method of the transformer substation.
The oil-immersed power transformer comprises the following parameters:
standard service life of oil-immersed power transformer is LDesign life，
Temperature rise delta theta of winding hot spot temperature to top layer oil temperature under rated currenthr＝35K，
Steady temperature rise delta theta of top layer oil under rated lossor＝45K，
The loss ratio R is 8,
the oil index x of the total loss to the top oil temperature is 0.8,
constant k of thermal model11＝0.5，
Constant k of thermal model21、k22Are all the components in the total number of 2,
time constant τ of windingW＝7min，
Time constant of oil temperature τO＝150min，
The load factor K is equal to the load current I/the rated current IN，
Winding hot spot temperature thetah(n)，
Top layer oil temperature θo，
Temperature rise delta theta of winding hot spot temperature to top layer oil temperatureh(n)，
The environment temperature of the environment where the oil-immersed power transformer is positioned is thetaa，
The sampling period t is 3 min.
Assuming that the initial state of life loss of the oil-immersed power transformer is L(0)For newly purchased power transformer, L can be taken(0)＝0；
(1) Calculating a first term delta theta of initial hot spot temperature riseh1(0)Initial hot spot temperature rise second term delta thetah2(0)：
When n is 0, t is 0, K is 0.81, thetaaWhen the temperature is higher than 30.3 ℃,
initial top oil temperature
Initial hot spot temperature rise first term Δ θh1(0)＝K21×ΔθhrKy＝2×35×K1.3Initial hot spot temperature rise second term Δ θ, 53.2Kh2(0)＝(k21-1)×ΔθhrKy＝(2-1)×35×K1.3＝26.6K；
(2) When n is 1, t is 3min, the load factor K is 0.87, thetaaCalculating the winding hot spot temperature theta at the end of the 1 st sampling period according to a hot spot temperature rise difference equation formula when the temperature is 29.9 DEG Ch(1)：
The top layer oil temperature change was as follows:
θo(1)＝Dθo(1)+θo(0)＝64℃
first term of hot spot temperature rise delta thetah1(1)＝Δθh1(0)+DΔθh1(1)＝53.2+1.12＝54.3K，
Wherein the content of the first and second substances,
second term of hot spot temperature rise Δ θh2(1)＝Δθh2(0)+DΔθh2(1)＝26.6+0.104＝26.7K，
Wherein the content of the first and second substances,
temperature rise delta theta of winding hot spot temperature to top layer oil temperatureh(1)＝Δθh1(1)-Δθh2(1)＝54.3-26.7＝27.6K；
Winding hot spot temperature thetah(1)＝θo(1)+Δθh(1)＝64.0+27.6＝91.6℃；
(3) Said oilAfter the first sampling period of the immersed power transformer is finished, the relative aging rate
Loss of life
Total loss of life L for oil immersed power transformers(1)＝L(0)+DL(1)＝L(0)+V(1)×Dt；
Residual life L of oil-immersed power transformerResidual life＝LDesign life-L(1)。
The following is a specific embodiment of quantitative evaluation of overload capacity of the oil-immersed power transformer by using the intelligent operation and maintenance and full life cycle management method of the transformer substation.
(1) When the winding hot spot temperature is less than 130, the top layer oil temperature is less than 115, and the maximum load is 1.3, the load type of the oil-immersed power transformer is a normal periodic load, and the following equipment maintenance suggestions are given: under the load type operation condition, the aging of the oil-immersed power transformer can be accelerated, but the insulation safety can not be directly endangered, and the continuous operation time M can be prolonged, wherein M is more than 1 week. Further, the load type of the oil-immersed power transformer is a normal periodic load, and the cloud server side calculates the maximum continuous operation time T of the oil-immersed power transformer according to an overload multiple (the overload multiple is actual current/rated current) and the top oil temperatureMAX: when the overload multiple is 1.05 and the top oil temperature is less than 18 ℃, the maximum continuous operation time T of the oil-immersed power transformerMAXThe maximum continuous operation time T of the oil-immersed power transformer is 5 hours and 50 minutes, and the maximum continuous operation time T of the oil-immersed power transformer is less than or equal to 42 ℃ when the oil temperature of the top layer is more than 36 DEG CMAX4 hours; when the overload multiple is 1.10 and the top oil temperature is less than 18 ℃, the maximum continuous operation time T of the oil-immersed power transformerMAX3 hours and 50 minutes, when the temperature of the top oil is more than or equal to 36 ℃ and less than 42 ℃, the maximum continuous operation time TMAXFor 1 hour and 20 minutes.
(2) When the winding hot spot temperature is less than 160 ℃, the top oil temperature is less than 115 ℃ and the maximum load coefficient is 1.3, the load type of the oil-immersed power transformer is a long-term first-aid periodic load, and the following equipment maintenance suggestions are given: under the load type operation condition, the hot point temperature of the winding of the oil-immersed power transformer can reach a dangerous degree, the insulation strength is temporarily reduced, and the operation is stopped;
(3) when the maximum load factor is 1.5, the load type of the oil-immersed power transformer is a short-term emergency load, and the equipment maintenance suggestion is as follows: under the load type operation condition, the temperature of a winding hot spot of the power transformer can reach a dangerous degree, all coolers including a standby cooler are required to be put into the power transformer, the load is compressed as much as possible, the operation time is reduced, the operation time of the oil-immersed power transformer can be M, and M is less than or equal to 0.5 h.
As shown in fig. 1, the invention further provides a transformer substation intelligent operation and maintenance and full life cycle management device, which includes an integrated protection measurement and control background for collecting integrated protection data and measurement and control data of a transformer substation, an environment temperature controller for collecting environment data, a telemechanical device and a local terminal, wherein the integrated protection measurement and control background and the environment temperature controller are respectively connected with a telemechanical device, and the telemechanical device is connected with the local terminal; the local terminal is internally preset with equipment data of the primary power equipment; the local terminal executes the intelligent operation and maintenance and full life cycle management method of the transformer substation. The intelligent operation and maintenance and full life cycle management device for the transformer substation enables a user to browse data on a remote machine at a local terminal, and particularly meets the requirement that part of special users who are not allowed to go to the cloud browse the data. Furthermore, the local terminal is a local PC terminal and is connected with the remote machine through a network port/serial port.
It should be noted that the local terminal can visually display the three-dimensional entity graph of the oil-immersed power transformer through the user terminal, and the simulated alarm lamps are arranged in all the components of the oil-immersed power transformer, so that the red represents the alarm signal, and the green represents the normal operation. When the local terminal processes the alarm information of the equipment, according to remote communication data of third-party monitoring data, when a monitored value exceeds a preset threshold value, an alarm or trip signal is given, for example, when the gas content of the body is higher than the preset threshold value, the corresponding alarm lamp can display red, and when the gas content of the body is lower than the preset threshold value, the corresponding alarm lamp displays green, so that the visual observation and processing of the alarm information of a user are facilitated.
The foregoing is a more detailed description of the invention in connection with specific preferred embodiments and it is not intended that the invention be limited to these specific details. For those skilled in the art to which the invention pertains, several simple deductions or substitutions can be made without departing from the spirit of the invention, and all shall be considered as belonging to the protection scope of the invention.
Claims (8)
1. A transformer substation intelligent operation and maintenance and full life cycle management method is characterized by comprising the following steps:
step 1, acquiring equipment data of primary power equipment of a transformer substation, wherein the equipment data comprises equipment basic data and factory test data, and the primary power equipment comprises an oil-immersed power transformer; acquiring comprehensive protection data and measurement and control data of the oil-immersed power transformer from a comprehensive and measurement and control background of a transformer substation; acquiring environmental data of the environment where the oil-immersed power transformer is located from an environmental temperature controller;
the equipment basic data and factory test data comprise temperature rise delta theta of winding hot spot temperature to top layer oil temperature under rated current of the oil-immersed power transformerhrConstant k of thermal model21And k22Time constant of winding τWTime constant of oil temperature τORated current INAnd a winding index y;
the comprehensive protection data and the measurement and control data comprise load current I of the oil-immersed power transformer and top oil temperature theta of the transformero(ii) a The environmental data comprises the environmental temperature theta of the environment where the oil-immersed power transformer is locateda；
Step 2, comprising step 21;
step 21, predicting the residual life of the oil-immersed power transformer by an intelligent algorithm according to the data acquired in the step 1, specifically as follows:
the initial state of service life loss of the oil-immersed power transformer is L(0)；
Initial hot spot temperature rise first term:
Δθh1(0)-k21×ΔθhrKy；
initial hot spot temperature rise second term:
Δθh2(0)＝(k21-1)×ΔθhrKy；
calculating the winding hot spot temperature theta with the nth sampling period being t according to the differential equation formula of the hot spot temperature riseh(n)N is an integer and n is not less than 1,
the hot spot temperature rise of the nth sampling period is the first term:
Δθh1(n)＝Δθh1(n-1)+DΔθh1(n)，
wherein the content of the first and second substances,
second term of hot spot temperature rise of nth sampling period:
Δθh2(n)＝Δθh2(n-1)+DΔθh2(n)，
wherein the content of the first and second substances,
and when the nth sampling period is finished, the winding hot spot temperature increases the temperature of the oil temperature of the top layer:
Δθh(n)＝Δθh1(n)-Δθh2(n)；
at the end of the nth sampling period, the winding hot spot temperature:
θh(n)＝θo+Δθh(n)；
wherein, K is a load factor, and K is a load current I/rated current IN；
Calculating the residual life of the oil-immersed power transformer according to the calculated winding hot spot temperature, wherein the specific calculation process is as follows:
at the end of the nth sampling period, the relative aging rate V of the sampling periodnThe calculation formula of (2) is as follows:
L(n)＝L(n-1)+V(n)×Dt
calculating the remaining life L of the oil-immersed power transformer (1) from the loss of lifeResidual lifeThe calculation formula is as follows:
Lresidual life＝LDesign life-L(n)；
Wherein L isDesign lifeThe service life of the oil-immersed power transformer (1) is designed.
2. The substation intelligent operation and maintenance and full-life-cycle management method according to claim 1, characterized in that: step 2 further comprises step 22;
step 22, quantitatively evaluating the overload capacity of the oil-immersed power transformer through an intelligent algorithm, wherein the step 22a and the step 22b are included:
step 22a, after each sampling period is finished, according to the maximum temperature limit requirement of the oil-immersed power transformer, the load current I and the top oil temperature theta of the transformeroLoad factor K and winding hot spot temperature theta calculated in step 21h(n)Judging the load type of the oil-immersed power transformer through a segmented threshold algorithm, wherein the load type comprises a normal periodic load, a short-term emergency load and a long-term emergency periodic load;
step 22b, quantitatively giving the oil temperature theta of different transformer top layers before the oil immersed power transformer is overloaded according to the load type of the oil immersed power transformeroCorresponding to the maximum continuous operation time T under the normal overload multipleMAXAnd generatesAnd (5) corresponding equipment maintenance suggestions.
3. The substation intelligent operation and maintenance and full-life-cycle management method according to claim 2, characterized in that: in step 22a, when the winding hot spot temperature thetah(n)＜X1And 0 < X1130 or less, top oil temperature thetao＜Y1And 0 < Y1Less than or equal to 115 percent, and the maximum load coefficient K is Z1And 0 < Z1When the load type is less than or equal to 1.3, judging that the load type of the oil-immersed power transformer is a normal periodic load;
when winding hot spot temperature X1≤θh(n)＜X2And 130 < X2160 or less, top oil temperature thetao＜Y1The maximum load factor K is Z1Judging the load type of the oil-immersed power transformer to be a long-term first-aid periodic load;
when the maximum load factor K is Z2And 1.3 < Z2And when the load type is less than or equal to 1.5, judging that the load type of the oil-immersed power transformer is a short-term emergency load.
4. The substation intelligent operation and maintenance and full-life-cycle management method according to claim 1, characterized in that: in step 21, the top layer oil temperature θ of the oil-immersed power transformer0The method comprises the steps that the top oil temperature is measured through a top oil temperature probe, and the top oil temperature probe continuously monitors the top oil temperature in the subsequent operation process of the oil-immersed power transformer to obtain a top oil temperature detection value; at the same time, by the ambient temperature θaAnd load current I, and top layer oil steady-state temperature rise delta theta under rated loss included by combining equipment basic data and factory test dataorConstant k of thermal model11Oil time constant τORated current, ratio R of load loss to no-load loss under rated current, and rated current INAnd calculating the oil index x of the total loss to the top oil temperature to obtain a top oil temperature calculated value thetaC：
Initial top oil temperature calculation θC(0)：
At the end of the nth sampling period, the calculated value of the top layer oil temperature is thetaC(n)：
θC(n)＝θC(n-1)+DθC(n),
Wherein the content of the first and second substances,
if the detected top oil temperature value and the calculated top oil temperature value thetaCIf the numerical difference is larger than or equal to m and m is larger than 0, whether the top oil temperature probe works normally is detected.
5. The utility model provides a cloud management platform on transformer substation's intelligence fortune dimension and full life cycle which characterized in that: the comprehensive protection, measurement and control system comprises a comprehensive protection, measurement and control background for collecting comprehensive protection data and measurement and control data of a transformer substation, an environment temperature controller for collecting environment data and a telemechanical, wherein the comprehensive protection, measurement and control background and the environment temperature controller are respectively connected with the telemechanical, and the telemechanical is connected with a cloud server end through a network;
the cloud server end is internally preset with equipment data of the primary power equipment; the cloud server side executes the intelligent substation operation and maintenance and full-life-cycle management method as claimed in any one of claims 1 to 4.
6. The substation intelligent operation and maintenance and full-life-cycle cloud-based management platform of claim 5, wherein: the system at least comprises a monitoring device for monitoring dissolved gas in oil, an iron core grounding current monitoring device, a sleeve insulation monitoring device, a partial discharge monitoring device, a micro-water detection device and an on-load tap-changer monitoring device, wherein the monitoring device is connected with the telemechanical motor respectively.
7. The substation intelligent operation and maintenance and full-life-cycle cloud-based management platform of claim 6, wherein: the cloud server end comprises a Web server, the Web server provides uniform Web release for the user end, and at least the following functions are provided: unified authority management, equipment parameter integrated management, unified report management, unified graph release, a system notification mechanism and Web browsing; the cloud server side further comprises a database server used for storing the collected data and the equipment data.
8. The substation intelligent operation and maintenance and full-life-cycle cloud-based management platform of claim 7, wherein: the user side can be a smart phone side, and/or a tablet computer side, and/or a PC side;
the comprehensive protection data and the measurement and control data comprise remote measurement data and remote signaling data; the remote measurement data comprises high-voltage side voltage/current, low-voltage side voltage/load current, active power, reactive power, a power factor and transformer top layer oil temperature; the remote communication data comprises a body gas alarm and trip signal, a body pressure release valve alarm and trip signal, a body oil level gauge high and low oil level, an on-load tap-changer gas alarm and trip signal, an on-load tap-changer pressure release valve alarm and trip signal, an on-load tap-changer oil level gauge high and low oil level and a fan starting/fault signal;
the equipment data also comprises daily maintenance data and overhaul record data;
the third-party monitoring data comprises monitoring data of gas dissolved in oil, detection data of iron core grounding current, detection data of sleeve insulation, detection data of partial discharge, detection data of micro water and detection data of an on-load tap-changer;
the cloud server side provides uniform Web release for the user side through the Web server, and the user can check the comprehensive protection data, the measurement and control data, the equipment data and the third-party monitoring data through the user side.
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