CN114726103B - Optimal control method and system for power grid operation inspection robot - Google Patents
Optimal control method and system for power grid operation inspection robot Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00002—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by monitoring
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- H—ELECTRICITY
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- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00001—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by the display of information or by user interaction, e.g. supervisory control and data acquisition systems [SCADA] or graphical user interfaces [GUI]
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- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00006—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment
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- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
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Abstract
The invention discloses an optimal control method and system for a power grid operation inspection robot, and relates to the field of power grid inspection. The method comprises the following steps: the auxiliary power tower distribution of the transformer substation is subjected to data acquisition, the acquired data are subjected to multi-feature analysis, meanwhile, the transformer substation data acquired by the power grid operation robot are subjected to log integration, the operation inspection parameters of the power grid operation inspection robot and the influence logic of the transformer substation operation log are constructed through communication, the operation inspection parameters of the power grid operation inspection robot and the operation log optimization model can be matched and trained based on the model, so that the influence parameters of the transformer substation are obtained, the transformer substation operation inspection data are optimally controlled according to the influence parameters, and when the power grid operation robot is used for carrying out daily inspection on the transformer substation, the inspection data of the robot are optimized through the auxiliary power tower data, the multi-feature comprehensiveness of the inspection data is met, and the intelligent power grid is accurately monitored.
Description
Technical Field
The invention relates to the field of power grid inspection, in particular to an optimal control method and system for a power grid operation inspection robot.
Background
With the start of automatic transformation of various industries, robots with high degree of intellectualization are increasingly brought into our field of view, the robots replace security patrol duty in a park, operation and maintenance work such as meter reading in a workshop factory is provided, and the inspection robots are not lack in a transformer substation to provide power inspection and construction planning tasks for the robots. As is well known, the operation quality of a transformer substation is closely related to the safe and stable operation of the whole power grid as a power grid hub, and regular inspection and daily defect elimination work are important ways for maintaining the stable operation of the transformer substation.
However, in the prior art, when a power grid operation robot is used for carrying out daily inspection on a transformer substation, the intelligent power grid is monitored only by means of single inspection data of the robot, so that the inspection data lack of multi-feature functions with comprehensiveness, and the technical problem of inaccurate monitoring on the intelligent power grid is caused.
Disclosure of Invention
The invention aims to provide an optimal control method and system for a power grid operation inspection robot, which are used for solving the technical problem that in the prior art, when a power grid operation robot is used for carrying out daily inspection on a transformer substation, the intelligent power grid is monitored only by means of single inspection data of the robot, so that the inspection data lack of comprehensive multi-feature functions, and the intelligent power grid is not accurately monitored.
In view of the above problems, the invention provides an optimal control method and system for a power grid operation and detection robot.
In a first aspect, the present invention provides an optimization control method for a power grid operation inspection robot, the method comprising: obtaining auxiliary power tower distribution of a target transformer substation, wherein the target transformer substation is used for detecting operation of the auxiliary power tower distribution; acquiring data of historical time nodes of the auxiliary power tower distribution through unmanned aerial vehicle equipment to obtain a historical operation and detection parameter set; the historical operation detection parameter set is transmitted back to a power grid operation monitoring system of the target transformer substation through a transmission module, visual parameter representation is carried out, and a tower visual operation network is generated; based on a power grid operation detection robot, operation detection data of the historical time node are collected for the target transformer substation, and collected data are integrated to generate a historical operation log set; according to the historical time node, correspondingly uploading the historical operation log set to the tower visual operation network, and constructing an operation detection parameter-operation log optimization model; and carrying out optimal control on substation operation detection data corresponding to the current time node based on the operation detection parameter-operation log optimization model.
In another aspect, the present invention further provides an optimization control system for a power grid operation inspection robot, configured to perform the optimization control method for a power grid operation inspection robot according to the first aspect, where the system includes: the system comprises a first obtaining unit, a second obtaining unit and a third obtaining unit, wherein the first obtaining unit is used for obtaining auxiliary power tower distribution of a target transformer substation, and the target transformer substation is used for detecting operation of the auxiliary power tower distribution; the first acquisition unit is used for acquiring data of historical time nodes of the auxiliary power tower distribution through unmanned aerial vehicle equipment to obtain a historical operation and detection parameter set; the first generation unit is used for transmitting the historical operation detection parameter set back to the power grid operation monitoring system of the target transformer substation through a transmission module, carrying out visual parameter representation and generating a tower visual operation network; the second generation unit is used for collecting the operation detection data of the historical time node for the target transformer substation based on the power grid operation detection robot, integrating the collected data and generating a historical operation log set; the first construction unit is used for correspondingly uploading the historical operation log set to the tower visual operation network according to the historical time node and constructing an operation detection parameter-operation log optimization model; the first optimizing unit is used for optimally controlling the transformer substation operation detection data corresponding to the current time node based on the operation detection parameter-operation log optimizing model.
In a third aspect, an electronic device includes a processor and a memory;
the memory is used for storing;
the processor is configured to execute the method according to any one of the first aspects by calling.
In a fourth aspect, a computer program product comprising a computer program and/or instructions which, when executed by a processor, implement the steps of the method according to any of the first aspects.
One or more technical schemes provided by the invention have at least the following technical effects or advantages:
the auxiliary power tower distribution of the transformer substation is subjected to data acquisition, the acquired data are subjected to multi-feature analysis, meanwhile, the transformer substation data acquired by the power grid operation robot are subjected to log integration, the operation inspection parameters of the power grid operation inspection robot and the influence logic of the transformer substation operation log are constructed through communication, the operation inspection parameters of the power grid operation inspection robot and the operation log optimization model can be matched and trained based on the model, so that the influence parameters of the transformer substation are obtained, the transformer substation operation inspection data are optimally controlled according to the influence parameters, and when the power grid operation robot is used for carrying out daily inspection on the transformer substation, the inspection data of the robot are optimized through the auxiliary power tower data, the multi-feature comprehensiveness of the inspection data is met, and the technical effect of accurately monitoring the intelligent power grid is achieved.
The foregoing description is only an overview of the present invention, and is intended to be implemented in accordance with the teachings of the present invention in order that the same may be more clearly understood and to make the same and other objects, features and advantages of the present invention more readily apparent.
Drawings
In order to more clearly illustrate the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described below, it being obvious that the drawings in the description below are only exemplary and that other drawings can be obtained according to the provided drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of an optimized control method for a power grid operation and inspection robot;
FIG. 2 is a schematic flow chart of constructing an operation inspection parameter-operation log optimization model in an optimization control method for an electric network operation inspection robot;
fig. 3 is a schematic flow chart of optimizing control of the substation operation and detection data in the optimizing control method for the power grid operation and detection robot;
FIG. 4 is a schematic diagram of an optimized control system for a grid operation robot according to the present invention;
fig. 5 is a schematic structural view of an exemplary electronic device of the present invention.
Reference numerals illustrate:
the system comprises a first obtaining unit 11, a first acquisition unit 12, a first generation unit 13, a second generation unit 14, a first construction unit 15, a first optimization unit 16, a bus 300, a receiver 301, a processor 302, a transmitter 303, a memory 304 and a bus interface 305.
Detailed Description
The invention provides an optimal control method and system for a power grid operation robot, which solve the technical problem that in the prior art, when the power grid operation robot is used for carrying out daily inspection on a transformer substation, the intelligent power grid is monitored only by means of single inspection data of the robot, so that the inspection data lack of comprehensive multi-feature functions, and the intelligent power grid is not accurately monitored. When the power grid operation robot is used for carrying out daily inspection on the transformer substation, inspection data of the robot are optimized through the attached power tower data, multi-feature comprehensiveness of the inspection data is met, and the technical effect of accurately monitoring the intelligent power grid is achieved.
The technical scheme of the invention obtains, stores, uses, processes and the like the data, which all meet the relevant regulations of national laws and regulations.
In the following, the technical solutions of the present invention will be clearly and completely described with reference to the accompanying drawings, and it should be understood that the described embodiments are only some embodiments of the present invention, but not all embodiments of the present invention, and that the present invention is not limited by the exemplary embodiments described herein. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention. It should be further noted that, for convenience of description, only some, but not all of the drawings related to the present invention are shown.
The invention provides an optimal control method for a power grid operation and detection robot, which comprises the following steps: the auxiliary power tower distribution of the transformer substation is subjected to data acquisition, the acquired data are subjected to multi-feature analysis, meanwhile, the transformer substation data acquired by the power grid operation robot are subjected to log integration, the operation inspection parameters of the power grid operation inspection robot and the influence logic of the transformer substation operation log are constructed through communication, the operation inspection parameters of the power grid operation inspection robot and the operation log optimization model can be matched and trained based on the model, so that the influence parameters of the transformer substation are obtained, the transformer substation operation inspection data are optimally controlled according to the influence parameters, and when the power grid operation robot is used for carrying out daily inspection on the transformer substation, the inspection data of the robot are optimized through the auxiliary power tower data, the multi-feature comprehensiveness of the inspection data is met, and the technical effect of accurately monitoring the intelligent power grid is achieved.
Having described the basic principles of the present invention, various non-limiting embodiments of the present invention will now be described in detail with reference to the accompanying drawings.
Example 1
Referring to fig. 1, the invention provides an optimized control method for a power grid operation inspection robot, which specifically comprises the following steps:
step S100: obtaining auxiliary power tower distribution of a target transformer substation, wherein the target transformer substation is used for detecting operation of the auxiliary power tower distribution;
step S200: acquiring data of historical time nodes of the auxiliary power tower distribution through unmanned aerial vehicle equipment to obtain a historical operation and detection parameter set;
further, step S200 includes:
step S210: taking foundation sliding as a first acquisition characteristic, sedimentation deformation as a second acquisition characteristic and iron tower inclination as a third acquisition characteristic;
step S220: and acquiring data of each node corresponding to the historical time node based on the first acquisition feature, the second acquisition feature and the third acquisition feature to obtain the historical operation detection parameter set.
Specifically, as each industry starts to be automatically transformed, robots with high-degree intellectualization increasingly enter our field of view, and the robots replace security patrol on duty in a park and provide operation and maintenance work such as meter reading in a workshop, and the inspection robots do not need to provide power inspection and construction planning tasks for the robots in a transformer substation. As is well known, the operation quality of a transformer substation is closely related to the safe and stable operation of the whole power grid as a power grid hub, and regular inspection and daily defect elimination work are important ways for maintaining the stable operation of the transformer substation.
However, in the prior art, when a power grid operation robot is used for carrying out daily inspection on a transformer substation, the intelligent power grid is monitored only by means of single inspection data of the robot, so that the inspection data lack of multi-feature functions with comprehensiveness, and the technical problem of inaccurate monitoring on the intelligent power grid is caused.
In order to solve the problems in the prior art, the application provides an optimal control method for a power grid operation and detection robot. The auxiliary power tower distribution of the transformer substation is subjected to data acquisition, the acquired data are subjected to multi-feature analysis, meanwhile, the transformer substation data acquired by the power grid operation robot are subjected to log integration, the operation inspection parameters of the power grid operation inspection robot and the influence logic of the transformer substation operation log are constructed through communication, the operation inspection parameters of the power grid operation inspection robot and the operation log optimization model can be matched and trained based on the model, so that the influence parameters of the transformer substation are obtained, the transformer substation operation inspection data are optimally controlled according to the influence parameters, and when the power grid operation robot is used for carrying out daily inspection on the transformer substation, the inspection data of the robot are optimized through the auxiliary power tower data, the multi-feature comprehensiveness of the inspection data is met, and the technical effect of accurately monitoring the intelligent power grid is achieved.
Specifically, the target transformer substation is a working point of the power grid operation inspection robot for power inspection, and the transformer substation refers to a place for converting voltage and current, receiving electric energy and distributing electric energy in a power system. After the distribution of the electric energy is completed by the transformer substation, the distributed electric energy needs to be transmitted by using an erected electric power tower, the distribution of the auxiliary electric power towers is the electric energy transmission device serving the target transformer substation, and the target transformer substation performs operation detection on the distribution of the auxiliary electric power towers, namely the transformer substation detects and is responsible for electric energy transmission data of the electric power towers.
When data acquisition is carried out on the distribution of the auxiliary power towers, the iron towers are generally arranged outdoors due to the position specificity, the distribution is wide, and a plurality of the iron towers are arranged in remote areas and are easily affected and damaged by nature and manpower. Therefore, an auxiliary method is needed to monitor the state of the communication tower in real time, and early warning is realized for possible problems, so that the effect of protecting the iron tower is achieved. The utility model discloses a data collection is carried out to affiliated electric power shaft tower distribution through unmanned aerial vehicle flying equipment, can gather the shaft tower data that historical time node corresponds, and exemplary can be 2016 years shaft tower data-2017 years shaft tower data-2018 years shaft tower data-to date, one year is a time node, gathers the data of shaft tower, historical fortune examines parameter set, is the data that the condition covers including shaft tower's ground, subsidence, deformation, slope, rupture and collapse that each time node gathered.
Specifically, foundation sliding can be used as a first acquisition characteristic, settlement deformation is used as a second acquisition characteristic and iron tower inclination is used as a third acquisition characteristic, and data of all nodes corresponding to the historical time nodes are acquired, wherein the foundation sliding represents the characteristics that the foundation of a tower moves and the like due to the change of geographic positions and erection areas, and when the foundation sliding occurs, the electric energy transmission process is influenced to a certain extent, so that monitoring data of a transformer substation are influenced; the settlement deformation characterizes that the erect soil layer of the tower is sunken, so that the tower is deformed, and the electric energy transmission process is influenced; the iron tower inclines, the erects the straightness that hangs down of having characterized the iron tower and has taken place the slope, leads to the high-tension cable to receive the pulling of slope external force, has also produced certain influence to the electric energy transmission process, through the data collection of characteristics such as follow ground slip, subsidence deformation and iron tower slope at each time node to the electric power shaft tower, can carry out contrast analysis effectively to the data of patrolling and examining of transformer substation.
Step S300: the historical operation detection parameter set is transmitted back to a power grid operation monitoring system of the target transformer substation through a transmission module, visual parameter representation is carried out, and a tower visual operation network is generated;
Step S400: based on a power grid operation detection robot, operation detection data of the historical time node are collected for the target transformer substation, and collected data are integrated to generate a historical operation log set;
specifically, after the operation and detection parameters of the power tower are collected, the historical operation and detection parameter set can be transmitted back to the power grid operation monitoring system of the target transformer substation through a network transmission module, wherein the network transmission module performs data transmission through a control end of unmanned aerial vehicle equipment, and is in communication connection with the power grid operation monitoring system, so that the network transmission module can effectively receive the data collected by the unmanned aerial vehicle equipment, and further, the collected historical operation and detection parameter set is subjected to visual parameter representation, a tower visual operation network can be generated,
when visual parameter representation is carried out, network simulation distribution is carried out on the power towers at first, and then multi-node acquisition data of each power tower are uploaded to the distributed power towers, so that visual parameter representation is carried out on the power towers, after a tower visual operation network is generated, operation detection data of an electric network operation detection robot in a transformer substation are required to be acquired, the electric network operation detection robot has functions of autonomous navigation, inspection, positioning, timing and the like, appearance images and temperature state images of various instrument readings and equipment in the transformer substation are accurately identified through a high-definition camera and infrared thermal imaging carried by the electric network operation detection robot, equipment defects are found in time, the operation workload of electric workers is greatly reduced, and urgent, difficult, dangerous, heavy and repetitive work encountered in transformer substation detection is replaced by manpower. The operation detection data of the historical time nodes are collected for the target transformer substation, namely, the transformer substation operation detection data of each time node in 2016-2017-2018-so far are collected, the collected data comprise various meter readings, appearance images of equipment, temperature state images and the like, and the collected data are integrated, namely, the collected time nodes, the collected states, fault report and corresponding maintenance records corresponding to each collected data are integrated, so that a transformer substation operation log set corresponding to each time node can be generated, and further data analysis is facilitated.
Step S500: according to the historical time node, correspondingly uploading the historical operation log set to the tower visual operation network, and constructing an operation detection parameter-operation log optimization model;
further, as shown in fig. 2, step S500 includes:
step S510: acquiring a first operation detection parameter and a first operation log corresponding to a first time node according to the historical time node, the historical operation detection parameter set and the historical operation log set;
step S520: splitting the first operation and detection parameters to obtain a first foundation sliding parameter, a first settlement deformation parameter and a first iron tower inclination parameter;
step S530: analyzing the first operation log to obtain first meter reading data, first appearance image data and first temperature state data;
step S540: defining the first foundation sliding parameter, the first settlement deformation parameter and the first iron tower inclination parameter as a first independent variable X 1 Defining the first meter reading data, the first appearance image data and the first temperature state data as a first dependent variable Y 1 ；
Step S550: traversing the operation detection parameters and the operation logs corresponding to the historical time nodes according to the data processing logic corresponding to the first time node to obtain a second independent variable X corresponding to a second time node 2 Second dependent variable Y 2 Up to the nth argument X corresponding to the nth time node n Nth dependent variable Y n ；
Step S560: the first independent variable X 1 Said second argument X 2 Up to the nth argument X n The first dependent variable Y is taken as an abscissa x-axis 1 The second dependent variable Y 2 Up to the nth dependent variable Y n Drawing a running log change curve of the operation detection parameter as an ordinate y-axis;
step S570: traversing the operation detection parameter-operation log change curve, extracting curve change characteristics and taking the curve change characteristics as a first optimization logic;
step S580: and constructing the operation checking parameter-operation log optimization model according to the first optimization logic.
Specifically, after the historical operation log set is obtained, the historical operation log set can be uploaded to a tower visual operation network, and in an exemplary data storage unit of a certain power tower, the data storage unit of the certain power tower comprises both tower operation detection data of each time node and transformer substation operation logs of corresponding time nodes, and the like, any power tower distribution node on the visual operation network comprises a corresponding data storage unit, and an operation detection parameter-operation log optimization model of each power tower can be constructed based on the data storage unit, wherein the operation detection parameter-operation log optimization model characterizes the influence of operation detection parameters of the power tower on the transformer substation operation log, and the operation detection data of the power grid robot can be optimized through the influence.
Specifically, when the operation checking parameter-operation log optimization model is constructed, a first operation checking parameter and a first operation log corresponding to a first time node can be obtained according to the historical time node, the historical operation checking parameter set and the historical operation log set, wherein the first time node can be understood as 2016, the first operation checking parameter can be understood as an operation checking parameter of a certain electric power tower in 2016, the first operation log can be understood as an operation log of a transformer substation corresponding to the 2016, further, the first operation checking parameter can be split to obtain a first foundation sliding parameter, a first settlement deformation parameter and a first iron tower inclination parameter, namely, the first operation checking parameter can be split from three characteristics of foundation sliding, settlement deformation, iron tower inclination and the like, so that concrete data influence analysis is facilitated. Meanwhile, the first operation log can be analyzed to obtain first meter reading data, first appearance image data and first temperature state data, wherein the first meter reading data represents various meter degrees in a transformer substation, the first appearance image data represents the switch opening and closing condition, and the first temperature state data represents the temperature state, the heat dissipation state and the like of various power equipment, so that the data can be deeply analyzed.
Further, in order to further analyze the split and resolved data, the first foundation sliding parameter, the first settlement deformation parameter, and the first tower inclination parameter may be defined as a first independent variable X 1 Defining the first meter reading data, the first appearance image data and the first temperature state data as a first dependent variable Y 1 Traversing the corresponding operation detection parameters and operation logs of each time node including 2017-2018-so far of the subsequent time nodes to obtain a second independent variable X corresponding to a second time node 2 Second dependent variable Y 2 Up to the nth argument X corresponding to the nth time node n Nth dependent variable Y n . The above independent variable set and dependent variable set can be used as sample data to draw the operation checking parameter-operation log change curve. Specifically, by combining the first argument X 1 Said second argument X 2 Up to the nth argument X n The first dependent variable Y is taken as an abscissa x-axis 1 The second dependent variable Y 2 Up to the nth dependent variable Y n As the y-axis of ordinate, to plot theThe operation detection parameter-operation log change curve intuitively reflects the monitoring influence of operation detection data of the power tower on the operation log of the transformer substation, and the operation detection parameter-operation log change curve is traversed to extract curve change characteristics and serve as first optimization logic, wherein the curve change characteristics reflect specific change relations of independent variables and dependent variables and specifically comprise positive/negative association degrees, change extremum and the like of the independent variables and the dependent variables, the first optimization logic represents the monitoring influence of operation detection data of the power tower on the operation log of the transformer substation, and the operation detection data of the transformer substation can be optimized according to the monitoring influence, so that an operation detection parameter-operation log optimization model can be constructed according to the first optimization logic to optimize the operation detection data of the transformer substation.
Step S600: and carrying out optimal control on substation operation detection data corresponding to the current time node based on the operation detection parameter-operation log optimization model.
Further, step S600 includes:
step S610: obtaining a current tower operation and detection parameter corresponding to the current time node;
step S620: inputting the current tower operation and detection parameters into the operation and detection parameter-operation log optimization model for matching training, and obtaining corresponding substation influence parameters;
step S630: and optimally controlling the substation operation and detection data according to the substation influence parameters.
Specifically, after the operation inspection parameter-operation log optimization model is constructed, the transformer substation operation inspection data corresponding to the current time node can be optimally controlled based on the operation inspection parameter-operation log optimization model. The current time node is a node with the latest time effect, namely a current time node, a current tower operation detection parameter corresponding to the current time node can be obtained, the current tower operation detection parameter reflects an operation detection parameter of a current power tower, the current tower operation detection parameter is input into the operation detection parameter-operation log optimization model for matching training, a corresponding transformer substation influence parameter can be obtained, the transformer substation influence parameter is an influence parameter of the operation detection parameter of the current power tower on the operation log of the current transformer substation, further, the transformer substation operation detection data can be optimally controlled according to the transformer substation influence parameter, and if the inclination of the power tower and the like cause certain external influence on the power transmission line, the monitoring data of the transformer substation is abnormal, due to the delay and other factors of long-distance signal transmission, the transformer substation cannot respond abnormally at the first time, the sudden abnormal monitoring can be captured according to the power grid operation monitoring system, the transformer substation operation detection data is optimally controlled, and the abnormal monitoring is enabled to respond quickly.
Further, as shown in fig. 3, step S570 includes:
step S571: extracting a first maximum value change node and a first minimum value change node according to the operation detection parameter-operation log change curve;
step S572: identifying the first minimum change node as a first constraint condition;
step S573: presetting a dangerous period early warning node according to the first maximum change node, and marking the dangerous period early warning node as a first early warning condition;
step S574: and optimally controlling the substation operation and detection data according to the first constraint condition and the first early warning condition.
Specifically, when the curve change characteristic is extracted, a first maximum value change node and a first minimum value change node can be extracted according to the operation detection parameter-operation log change curve, the first maximum value change node reflects a maximum influence parameter node of the operation detection parameter of the power tower on the operation log of the transformer substation, and the first minimum value change node reflects a minimum influence parameter node of the operation detection parameter of the power tower on the operation log of the transformer substation, namely, almost negligible parameter nodes.
Furthermore, the first minimum value change node can be identified as a first constraint condition, the first constraint condition characterizes a condition that the operation detection parameter of the power tower can be dynamically monitored according to the minimum value change node, and if the operation detection parameter is close to the first constraint condition, the operation detection parameter of the power tower can be understood to not influence the operation log of the transformer substation. Meanwhile, according to the first maximum change node, a dangerous period early warning node is preset, the dangerous period early warning node is identified as a first early warning condition, wherein the first maximum change node reflects the maximum influence parameter node of the operation and detection parameters of the power towers on the operation logs of the transformer substation, namely the operation and detection parameters of the power towers corresponding to the node, and serious influence is caused on the operation logs of the transformer substation. And furthermore, the substation operation detection data is optimally controlled according to the first constraint condition and the first early warning condition, so that further efficient and scientific optimal control of the substation operation detection data is realized.
Further, step S220 includes:
step S221: obtaining a first characteristic data set according to the historical operation and detection parameter set;
step S222: performing centering processing on the first characteristic data set to obtain a second characteristic data set;
step S223: obtaining a first covariance matrix of the second feature data set;
step S224: operating the first covariance matrix to obtain a first eigenvalue and a first eigenvector of the first covariance matrix;
step S225: and projecting the first characteristic data set to the first characteristic vector to obtain a first dimension reduction data set, wherein the first dimension reduction data set is a characteristic data set obtained after dimension reduction of the first characteristic data set.
Specifically, after the set of historical shipping inspection parameters is obtained, it needs to be data pre-processed. Specifically, the extracted feature data, namely the historical operation and detection parameter set is subjected to numerical processing, and a feature data set matrix is constructed to obtain the first feature data set. And then carrying out centering processing on each feature data in the first feature data set, firstly solving the average value of each feature in the first feature data set, then subtracting the average value of each feature from each feature for all samples, and then obtaining a new feature value, wherein the second feature data set is formed by the new feature value, and is a data matrix. By covariance formula:
And operating the second characteristic data set to obtain a first covariance matrix of the second characteristic data set. Wherein,,feature data in the second feature data set; />Is the average value of the characteristic data; m is the total amount of sample data in the second feature data set. And then, calculating the eigenvalue and eigenvector of the first covariance matrix through matrix operation, wherein each eigenvalue corresponds to one eigenvector. And selecting the first K largest eigenvalues and the eigenvectors corresponding to the first eigenvalues from the first eigenvector, and projecting the original features in the first eigenvalue data set onto the selected eigenvector to obtain the first eigenvalue data set after dimension reduction. And performing dimension reduction processing on the characteristic data in the database by using a principal component analysis method, and removing redundant data on the premise of guaranteeing the information quantity, so that the sample quantity of the characteristic data in the database is reduced, the information quantity loss after dimension reduction is minimum, and the operation speed of the data is accelerated.
In summary, the optimized control method for the power grid operation and detection robot provided by the invention has the following technical effects:
1. the auxiliary power tower distribution of the transformer substation is subjected to data acquisition, the acquired data are subjected to multi-feature analysis, meanwhile, the transformer substation data acquired by the power grid operation robot are subjected to log integration, the operation inspection parameters of the power grid operation inspection robot and the influence logic of the transformer substation operation log are constructed through communication, the operation inspection parameters of the power grid operation inspection robot and the operation log optimization model can be matched and trained based on the model, so that the influence parameters of the transformer substation are obtained, the transformer substation operation inspection data are optimally controlled according to the influence parameters, and when the power grid operation robot is used for carrying out daily inspection on the transformer substation, the inspection data of the robot are optimized through the auxiliary power tower data, the multi-feature comprehensiveness of the inspection data is met, and the technical effect of accurately monitoring the intelligent power grid is achieved.
2. Drawing a running log change curve of the operation detection parameters by taking the independent variable set and the dependent variable set as sample data, reflecting the monitoring influence of the operation detection data of the power tower on the running log of the transformer substation, and optimizing the operation detection data of the transformer substation by traversing the running log change curve of the operation detection parameters and the operation log change curve and extracting curve change characteristics as first optimization logic.
3. The first minimum value change node is identified as a first constraint condition, the dangerous period early warning node is preset according to the first maximum value change node, the first early warning condition is identified, the substation operation detection data is optimally controlled according to the first constraint condition and the first early warning condition, and further efficient and scientific optimal control of the substation operation detection data is realized.
Example two
Based on the same inventive concept as the optimization control method for the power grid operation inspection robot in the foregoing embodiment, the present invention further provides an optimization control system for the power grid operation inspection robot, referring to fig. 4, the system includes:
a first obtaining unit 11, where the first obtaining unit 11 is configured to obtain an auxiliary power tower distribution of a target substation, where the target substation is configured to perform operation detection on the auxiliary power tower distribution;
The first collection unit 12 is configured to collect data of a historical time node of the distribution of the auxiliary power tower through unmanned aerial vehicle equipment, so as to obtain a historical operation and detection parameter set;
the first generating unit 13 is configured to transmit the historical operation detection parameter set back to the power grid operation monitoring system of the target substation through a transmission module, perform visual parameter representation, and generate a tower visual operation network;
the second generating unit 14 is configured to collect operation detection data of the historical time node for the target substation based on the power grid operation detection robot, integrate the collected data, and generate a historical operation log set;
the first construction unit 15 is configured to correspondingly upload the historical operation log set to the tower visual operation network according to the historical time node, and construct an operation detection parameter-operation log optimization model;
the first optimizing unit 16 is configured to optimally control substation operation detection data corresponding to the current time node based on the operation detection parameter-operation log optimizing model by the first optimizing unit 16.
Further, the system further comprises:
the second obtaining unit is used for obtaining a first operation check parameter and a first operation log corresponding to a first time node according to the historical time node, the historical operation check parameter set and the historical operation log set;
the first splitting unit is used for splitting the first operation detection parameter to obtain a first foundation sliding parameter, a first settlement deformation parameter and a first iron tower inclination parameter;
the first analysis unit is used for analyzing the first operation log to obtain first meter reading data, first appearance image data and first temperature state data;
the first defining unit is used for defining the first foundation sliding parameter, the first settlement deformation parameter and the first iron tower inclination parameter as a first independent variable X 1 Defining the first meter reading data, the first appearance image data and the first temperature state data as a first dependent variable Y 1 ；
A third obtaining unit, configured to traverse the operation detection parameter and the operation log corresponding to the historical time node according to the data processing logic corresponding to the first time node, to obtain a second argument X corresponding to a second time node 2 Second dependent variable Y 2 Up to the nth argument X corresponding to the nth time node n Nth dependent variable Y n 。
Further, the system further comprises:
a first rendering unit for rendering the first argument X 1 Said second argument X 2 Up to the nth argument X n The first dependent variable Y is taken as an abscissa x-axis 1 The second dependent variable Y 2 Up to the nth dependent variable Y n Drawing a running log change curve of the operation detection parameter as an ordinate y-axis;
the first extraction unit is used for traversing the operation detection parameter-operation log change curve, extracting curve change characteristics and taking the curve change characteristics as first optimization logic;
the second construction unit is used for constructing the operation checking parameter-operation log optimization model according to the first optimization logic.
Further, the system further comprises:
the second extraction unit is used for extracting a first maximum value change node and a first minimum value change node according to the operation detection parameter-operation log change curve;
the first identification unit is used for identifying the first minimum value change node as a first constraint condition;
The second identification unit is used for presetting a dangerous period early warning node according to the first maximum value change node and identifying the dangerous period early warning node as a first early warning condition;
the second optimizing unit is used for optimally controlling the substation operation and detection data according to the first constraint condition and the first early warning condition.
Further, the system further comprises:
the third identification unit is used for taking foundation sliding as a first acquisition characteristic, sedimentation deformation as a second acquisition characteristic and iron tower inclination as a third acquisition characteristic;
the second acquisition unit is used for acquiring data of each node corresponding to the historical time node based on the first acquisition characteristic, the second acquisition characteristic and the third acquisition characteristic to obtain the historical operation detection parameter set.
Further, the system further comprises:
the fourth obtaining unit is used for obtaining a first characteristic data set according to the historical operation detection parameter set;
a fifth obtaining unit, configured to perform a centering process on the first feature data set, to obtain a second feature data set;
A sixth obtaining unit configured to obtain a first covariance matrix of the second feature data set;
the first operation unit is used for operating the first covariance matrix to obtain a first eigenvalue and a first eigenvector of the first covariance matrix;
a seventh obtaining unit, configured to project the first feature data set to the first feature vector, and obtain a first dimension-reduction data set, where the first dimension-reduction data set is a feature data set obtained after dimension reduction of the first feature data set.
Further, the system further comprises:
the eighth obtaining unit is used for obtaining the current tower operation and detection parameters corresponding to the current time node;
a ninth obtaining unit, configured to input the current tower operation and detection parameter to the operation and detection parameter-operation log optimization model for matching training, to obtain a corresponding substation influence parameter;
and the third optimizing unit is used for optimally controlling the substation operation and detection data according to the substation influence parameters.
In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the difference from other embodiments, and the foregoing method and specific example for optimizing control of a power grid operation inspection robot in the first embodiment of fig. 1 are also applicable to an optimizing control system for a power grid operation inspection robot in this embodiment, and by the foregoing detailed description of an optimizing control method for a power grid operation inspection robot, those skilled in the art can clearly know that an optimizing control system for a power grid operation inspection robot in this embodiment is not described in detail herein for brevity of the specification. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Exemplary electronic device
The electronic device of the present invention is described below with reference to fig. 5.
Fig. 5 illustrates a schematic structural view of an electronic device according to the present invention.
Based on the inventive concept of an optimal control method for an electric grid operation inspection robot according to the foregoing embodiments, the present invention further provides an optimal control system for an electric grid operation inspection robot, on which a computer program is stored, which when executed by a processor, implements the steps of any one of the foregoing methods for an optimal control method for an electric grid operation inspection robot.
Where in FIG. 5, a bus architecture (represented by bus 300), bus 300 may comprise any number of interconnected buses and bridges, with bus 300 linking together various circuits, including one or more processors, represented by processor 302, and memory, represented by memory 304. Bus 300 may also link together various other circuits such as peripheral devices, voltage regulators, power management circuits, etc., as are well known in the art and, therefore, will not be described further herein. Bus interface 305 provides an interface between bus 300 and receiver 301 and transmitter 303. The receiver 301 and the transmitter 303 may be the same element, i.e. a transceiver, providing a means for communicating with various other apparatus over a transmission medium.
The processor 302 is responsible for managing the bus 300 and general processing, while the memory 304 may be used to store data used by the processor 302 in performing operations.
The invention provides an optimal control method for a power grid operation and detection robot, which comprises the following steps: obtaining auxiliary power tower distribution of a target transformer substation, wherein the target transformer substation is used for detecting operation of the auxiliary power tower distribution; acquiring data of historical time nodes of the auxiliary power tower distribution through unmanned aerial vehicle equipment to obtain a historical operation and detection parameter set; the historical operation detection parameter set is transmitted back to a power grid operation monitoring system of the target transformer substation through a transmission module, visual parameter representation is carried out, and a tower visual operation network is generated; based on a power grid operation detection robot, operation detection data of the historical time node are collected for the target transformer substation, and collected data are integrated to generate a historical operation log set; according to the historical time node, correspondingly uploading the historical operation log set to the tower visual operation network, and constructing an operation detection parameter-operation log optimization model; and carrying out optimal control on substation operation detection data corresponding to the current time node based on the operation detection parameter-operation log optimization model. The intelligent power grid monitoring system solves the technical problem that when a power grid operation robot is used for carrying out daily inspection on a transformer substation in the prior art, the intelligent power grid is monitored only by means of single inspection data of the robot, so that the inspection data lack of comprehensive multi-feature functions, and inaccurate monitoring on the intelligent power grid is caused. The auxiliary power tower distribution of the transformer substation is subjected to data acquisition, the acquired data are subjected to multi-feature analysis, meanwhile, the transformer substation data acquired by the power grid operation robot are subjected to log integration, the operation inspection parameters of the power grid operation inspection robot and the influence logic of the transformer substation operation log are constructed through communication, the operation inspection parameters of the power grid operation inspection robot and the operation log optimization model can be matched and trained based on the model, so that the influence parameters of the transformer substation are obtained, the transformer substation operation inspection data are optimally controlled according to the influence parameters, and when the power grid operation robot is used for carrying out daily inspection on the transformer substation, the inspection data of the robot are optimized through the auxiliary power tower data, the multi-feature comprehensiveness of the inspection data is met, and the technical effect of accurately monitoring the intelligent power grid is achieved.
The invention also provides an electronic device, which comprises a processor and a memory;
the memory is used for storing;
the processor is configured to execute the method according to any one of the above embodiments by calling.
The invention also provides a computer program product comprising a computer program and/or instructions which, when executed by a processor, implement the steps of the method of any of the above embodiments.
It will be apparent to those skilled in the art that embodiments of the present invention may be provided as a method, apparatus, or computer program product. Accordingly, the present invention may take the form of an entirely software embodiment, an entirely hardware embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention is in the form of a computer program product that can be embodied on one or more computer-usable storage media including computer-usable program code. And the computer-usable storage medium includes, but is not limited to: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk Memory, a Read-Only optical disk (Compact Disc Read-Only Memory, CD-ROM), an optical Memory, and other various media capable of storing program codes.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a system for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks. While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the present invention and the equivalent techniques thereof, the present invention is also intended to include such modifications and variations.
Claims (8)
1. An optimized control method for a power grid operation inspection robot, which is characterized by comprising the following steps:
obtaining auxiliary power tower distribution of a target transformer substation, wherein the target transformer substation is used for detecting operation of the auxiliary power tower distribution;
Acquiring data of historical time nodes of the auxiliary power tower distribution through unmanned aerial vehicle equipment to obtain a historical operation and detection parameter set;
the historical operation detection parameter set is transmitted back to a power grid operation monitoring system of the target transformer substation through a transmission module, visual parameter representation is carried out, and a tower visual operation network is generated;
based on a power grid operation detection robot, operation detection data of the historical time node are collected for the target transformer substation, and collected data are integrated to generate a historical operation log set;
acquiring a first operation detection parameter and a first operation log corresponding to a first time node according to the historical time node, the historical operation detection parameter set and the historical operation log set;
splitting the first operation and detection parameters to obtain a first foundation sliding parameter, a first settlement deformation parameter and a first iron tower inclination parameter;
analyzing the first operation log to obtain first meter reading data, first appearance image data and first temperature state data;
defining the first foundation sliding parameter, the first settlement deformation parameter and the first iron tower inclination parameter as a first independent variable X 1 Defining the first meter reading data, the first appearance image data and the first temperature state data as a first dependent variable Y 1； Traversing the operation detection parameters and the operation logs corresponding to the historical time nodes according to the data processing logic corresponding to the first time node to obtain a second independent variable X corresponding to a second time node 2 Second dependent variable Y 2 Up to the nth argument X corresponding to the nth time node n Nth dependent variable Y n The method comprises the steps of carrying out a first treatment on the surface of the The first independent variable X 1 Said second argument X 2 Up to the nth argument X n The first dependent variable Y is taken as an X axis of an abscissa 1 The second dependent variable Y 2 Up to the nth dependent variable Y n Drawing a running log change curve of the operation detection parameter as an ordinate y-axis; traversing the operation detection parameter-operation log change curve, extracting curve change characteristics and taking the curve change characteristics as a first optimization logic;
constructing the operation checking parameter-operation log optimization model according to the first optimization logic;
and carrying out optimal control on substation operation detection data corresponding to the current time node based on the operation detection parameter-operation log optimization model.
2. The method of claim 1, wherein the method comprises:
Extracting a first maximum value change node and a first minimum value change node according to the operation detection parameter-operation log change curve;
identifying the first minimum change node as a first constraint condition;
presetting a dangerous period early warning node according to the first maximum change node, and marking the dangerous period early warning node as a first early warning condition;
and optimally controlling the substation operation and detection data according to the first constraint condition and the first early warning condition.
3. The method of claim 1, wherein the obtaining a set of historical shipping inspection parameters comprises:
taking foundation sliding as a first acquisition characteristic, sedimentation deformation as a second acquisition characteristic and iron tower inclination as a third acquisition characteristic;
and acquiring data of each node corresponding to the historical time node based on the first acquisition feature, the second acquisition feature and the third acquisition feature to obtain the historical operation detection parameter set.
4. A method according to claim 3, wherein the method comprises:
obtaining a first characteristic data set according to the historical operation and detection parameter set;
performing centering processing on the first characteristic data set to obtain a second characteristic data set;
Obtaining a first covariance matrix of the second feature data set;
operating the first covariance matrix to obtain a first eigenvalue and a first eigenvector of the first covariance matrix;
and projecting the first characteristic data set to the first characteristic vector to obtain a first dimension reduction data set, wherein the first dimension reduction data set is a characteristic data set obtained after dimension reduction of the first characteristic data set.
5. The method of claim 1, wherein the optimally controlling the substation operation and inspection data corresponding to the current time node comprises:
obtaining a current tower operation and detection parameter corresponding to the current time node;
inputting the current tower operation and detection parameters into the operation and detection parameter-operation log optimization model for matching training, and obtaining corresponding substation influence parameters;
and optimally controlling the substation operation and detection data according to the substation influence parameters.
6. An optimal control system for a grid operation inspection robot, the system comprising:
the system comprises a first obtaining unit, a second obtaining unit and a third obtaining unit, wherein the first obtaining unit is used for obtaining auxiliary power tower distribution of a target transformer substation, and the target transformer substation is used for detecting operation of the auxiliary power tower distribution;
The first acquisition unit is used for acquiring data of historical time nodes of the auxiliary power tower distribution through unmanned aerial vehicle equipment to obtain a historical operation and detection parameter set;
the first generation unit is used for transmitting the historical operation detection parameter set back to the power grid operation monitoring system of the target transformer substation through a transmission module, carrying out visual parameter representation and generating a tower visual operation network;
the second generation unit is used for collecting the operation detection data of the historical time node for the target transformer substation based on the power grid operation detection robot, integrating the collected data and generating a historical operation log set;
the second obtaining unit is used for obtaining a first operation check parameter and a first operation log corresponding to a first time node according to the historical time node, the historical operation check parameter set and the historical operation log set;
the first splitting unit is used for splitting the first operation detection parameter to obtain a first foundation sliding parameter, a first settlement deformation parameter and a first iron tower inclination parameter;
The first analysis unit is used for analyzing the first operation log to obtain first meter reading data, first appearance image data and first temperature state data;
the first defining unit is used for defining the first foundation sliding parameter, the first settlement deformation parameter and the first iron tower inclination parameter as a first independent variable X 1 Defining the first meter reading data, the first appearance image data and the first temperature state data as a first dependent variable Y 1；
A third obtaining unit, configured to traverse the operation detection parameter and the operation log corresponding to the historical time node according to the data processing logic corresponding to the first time node, to obtain a second argument X corresponding to a second time node 2 Second dependent variable Y 2 Up to the nth argument X corresponding to the nth time node n Nth dependent variable Y n； A first rendering unit for rendering the first argument X 1 Said second argument X 2 Up to the nth argument X n， The first dependent variable Y is taken as an X axis of abscissa 1 The second dependent variable Y 2 Up to the nth dependent variable Y n Drawing a running log change curve of the operation detection parameter as an ordinate y-axis; the first extraction unit is used for traversing the operation detection parameter-operation log change curve, extracting curve change characteristics and taking the curve change characteristics as first optimization logic;
a second construction unit for constructing the operation inspection parameter-operation log optimization model according to the first optimization logic
The first optimizing unit is used for optimally controlling the transformer substation operation detection data corresponding to the current time node based on the operation detection parameter-operation log optimizing model.
7. An electronic device comprising a processor and a memory;
the memory is used for storing;
the processor is configured to execute the method of any one of claims 1 to 5 by calling.
8. A computer program product comprising a computer program and/or instructions which, when executed by a processor, implement the steps of the method of any one of claims 1 to 5.
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