CN116029699A - Power information system based on data twinning and operation and maintenance method - Google Patents
Power information system based on data twinning and operation and maintenance method Download PDFInfo
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Abstract
The invention relates to the field of electric power and digital twinning, in particular to an electric power information system and an operation and maintenance method based on digital twinning, comprising the following steps of S1, collecting operation data of power transformation equipment, S2, carrying out network transmission and storage on the operation data of the power transformation equipment through a unified standard protocol; s3: establishing an electric power operation and maintenance database based on the stored operation data, combining the electric power operation and maintenance database data with historical operation data, and evaluating and predicting the state of the equipment to generate alarm information; s4: and receiving the alarm information and carrying out data interaction with an application layer to generate an overhaul strategy.
Description
Technical Field
The invention relates to the field of electric power and digital twinning, in particular to an electric power information system based on digital twinning and an operation and maintenance method.
Background
In recent years, the construction of the energy Internet in China is faster, and meanwhile, the types and the scales of power equipment are greatly improved, so that higher requirements are provided for safe and stable operation of a power grid system. The operation and maintenance business of the traditional electric power information system is mainly conducted under the guidance of guidelines, regulations, expert experience or traditional ratio, waveform characteristic analysis methods and other modes, the methods are difficult to process the sea-based, refined and differentiated system data, and the problems of over repair or under repair are easy to occur, so that the resource waste of manpower and material resources is caused. In addition, a large amount of sleep history data can be accumulated in operation, maintenance and overhaul of the power grid equipment, the sleep history data are not explored and mined yet, and the data cannot be applied to the production operation process. Therefore, more sophisticated methods are needed to solve the various problems previously existing and to better perform operation and maintenance work on the power system.
Disclosure of Invention
In order to solve one of the problems, the invention provides a data twinning-based power information system which sequentially comprises a device layer, an acquisition layer, an application layer and a user layer according to the transmission direction of data,
the equipment layer is used for collecting operation data of the power transformation equipment;
the acquisition layer standardizes a communication protocol, and performs network transmission and storage on operation data of the power transformation equipment;
the application layer receives the equipment operation data of the acquisition layer to establish an electric operation data base, evaluates and predicts the state of the equipment and generates alarm information;
and the user layer receives the alarm information and performs data interaction with the application layer to generate an overhaul strategy.
Further, the equipment layer comprises transformer, switch cabinet, gas-insulated metal-enclosed switchgear of combined electrical apparatus, arc suppression coil, reactive compensation equipment, power distribution complete equipment and other primary equipment of power transformation, relay protection and communication type screen cabinet secondary equipment, and video recorder and inspection robot for collecting operation data of the power transformation equipment.
Further, a data transmission protocol standard unit, a video server and a patrol server are arranged on the acquisition layer, the data transmission protocol standard unit converts a communication protocol of the data acquisition layer into an http protocol, the http protocol is transmitted to the video server and the patrol server through a network to carry out data caching, and each server transmits acquired data to a central server to be summarized.
Furthermore, an expert knowledge base and an intelligent analysis unit are arranged on the application layer, the expert knowledge base stores historical operation data, and the intelligent analysis unit analyzes and predicts the operation state of the equipment based on the expert knowledge base data and the power operation data.
Furthermore, the application layer is provided with an equipment monitoring unit, an expert knowledge base, a transformer substation overview, an intelligent analysis unit and a system management unit.
Furthermore, the user layer and the application layer perform data interaction, and the expert knowledge base is updated based on equipment operation data and historical experience data by utilizing data intelligence and knowledge graph technology to perform auxiliary decision-making of equipment defect diagnosis.
An operation and maintenance method of a power information system based on data twinning comprises the following steps,
s1, collecting operation data of power transformation equipment,
s2, network transmission and storage are carried out on operation data of the power transformation equipment through a unified standard protocol;
s3: establishing an electric power operation data base based on the stored operation data, combining the real-time data with the historical operation data, and evaluating and predicting the state of the equipment to generate alarm information;
s4: and receiving the alarm information and carrying out data interaction with an application layer to generate an overhaul strategy.
Further, in S3, the LSTM algorithm is used to analyze and predict the degradation inflection point of the device, process the defect of the device, and make the next decision.
Further, in S3, based on the real-time operation data of the device, the device operation state is evaluated by using a device state classification evaluation model, a device operation state prediction model and a multi-parameter association relation analysis model, the obtained result is spliced with the device defect record history data, the device state classification evaluation model is input, the future period of operation state of the device is predicted, and if the predicted value exceeds the normal operation value of the device, fault early warning processing is performed.
The invention has the beneficial effects that: the invention provides an operation and maintenance method of an electric power information system based on data twinning, which focuses on the application of the data twinning in the operation and maintenance field of electric power equipment, expounds the connotation and characteristics of the data twinning of the electric power information system, further constructs a basic frame of the data twinning system of the electric power equipment, and in practical application, the method can be found out through multiple times of verification.
Drawings
FIG. 1 is a schematic flow chart of an operation and maintenance method of a power information system based on data twinning;
fig. 2 is a schematic diagram of a framework structure of a transformer substation data twin system;
FIG. 3 is a schematic flow chart of screening, analyzing, predicting and formulating a defect treatment scheme in a device defect scene;
FIG. 4 is a schematic diagram showing the comparison of the true value and the predicted value of the X-phase temperature of the main transformer low-voltage bushing No. 1;
FIG. 5 is a schematic diagram showing the comparison of the true value and the predicted value of the Y-phase temperature of the main transformer low-voltage bushing No. 1;
fig. 6 is a schematic diagram of the result of data change after the transient voltage cleaning of the switch cabinet.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Referring to fig. 1-5, the invention provides a power information system based on data twinning, which sequentially comprises a device layer, an acquisition layer, an application layer and a user layer according to the transmission direction of data,
the equipment layer is used for collecting operation data of the power transformation equipment;
the acquisition layer standardizes a communication protocol, and performs network transmission and storage on operation data of the power transformation equipment;
the application layer receives the equipment operation data of the acquisition layer to establish an electric operation data base, evaluates and predicts the state of the equipment and generates alarm information;
and the user layer receives the alarm information and performs data interaction with the application layer to generate an overhaul strategy.
As an improvement of the scheme, the equipment layer comprises transformer, switch cabinet, gas-insulated metal-enclosed switchgear of combined electrical apparatus, arc suppression coil, reactive compensation equipment, distribution transformer complete equipment and other primary equipment for power transformation, relay protection and communication screen cabinet secondary equipment, and video recorder and inspection robot for collecting operation data of the power transformation equipment. The equipment can generate and record daily electricity consumption data of the electric power system, the method provided by the invention collects, sorts and summarizes the electricity consumption data through a series of electric power equipment, and finally, the electricity consumption data is applied to an acquisition layer for further normalization processing and data calculation.
As an improvement of the scheme, a data transmission protocol standard unit, a video server and an inspection server are arranged on the acquisition layer, the data transmission protocol standard unit converts a communication protocol of the data acquisition layer into an http protocol, the http protocol is transmitted to the video server and the inspection server through a network to carry out data caching, and each server transmits acquired data to a central server to be summarized. In the layer, the system collects power consumption data from primary equipment, secondary equipment, video recorders, inspection robots and other equipment of the equipment layer, and uses a service interface to carry out unified protocol specification on the obtained initial data, so that the data form is more unified, and a large amount of calculation is carried out in the application layer in the next step.
As an improvement of the scheme, the application layer is provided with an expert knowledge base and an intelligent analysis unit, the expert knowledge base stores historical operation data, and the intelligent analysis unit analyzes and predicts the operation state of the equipment based on the expert knowledge base data and the power operation data.
As an improvement of the scheme, the application layer is provided with an equipment monitoring unit, an expert knowledge base, a transformer substation overview, an intelligent analysis unit and a system management unit.
As an improvement of the scheme, data interaction is carried out between the user layer and the application layer, and the equipment defect diagnosis auxiliary decision is carried out and an expert knowledge base is updated based on equipment operation data and historical experience data by utilizing data intelligence and knowledge graph technology.
An operation and maintenance method of a power information system based on data twinning comprises the following steps,
s1, collecting operation data of power transformation equipment,
s2, network transmission and storage are carried out on operation data of the power transformation equipment through a unified standard protocol;
s3: establishing an electric power operation data base based on the stored operation data, combining the real-time data with the historical operation data, and evaluating and predicting the state of the equipment to generate alarm information;
s4: and receiving the alarm information and carrying out data interaction with an application layer to generate an overhaul strategy.
As an improvement of the scheme, in S3, the LSTM algorithm is used to analyze and predict the degradation inflection point of the device, process the defect of the device, and make the next decision.
In S3, based on the real-time running data of the equipment, the equipment running state is evaluated by adopting an equipment state classification evaluation model, an equipment running state prediction model and a multi-parameter association relation analysis model, the obtained result is spliced with the equipment defect record historical data, the equipment state classification evaluation model is input, the future running state of the equipment is predicted, and if the predicted value exceeds the normal running value of the equipment, fault early warning processing is carried out.
The technical scheme for solving the technical problems is as follows:
the invention provides a data twinning-based power information system operation and maintenance method, which is shown in reference to fig. 1, and comprises the following steps:
s1: preliminarily designing a working frame of the data twin system;
the data twinning related to the electric power equipment focuses on the acquisition and analysis of the data, a corresponding operation and maintenance overhaul strategy is given by using a data driving algorithm, a working closed loop is formed in the processes of sensing, analyzing and deciding, so that a worker can acquire the state information of the equipment more accurately and timely, differential and fine operation and maintenance overhaul work is realized, and the operation and maintenance work is further advanced from preventive maintenance to predictive maintenance.
Fig. 2 is a framework of a substation data twin system, and the system can be divided into four layers of content including a device layer, a data layer, an application layer and an end user layer according to data flow.
S11: establishing an equipment layer;
the equipment layer comprises transformer, switch cabinet, gas-insulated metal-enclosed switchgear of combined electrical apparatus, arc suppression coil, reactive compensation equipment, power distribution complete equipment and other primary equipment for power transformation, relay protection, communication screen cabinet and other secondary equipment, and various intelligent sensors, inspection robots and the like for collecting operation data of the power transformation equipment.
S12: establishing an acquisition layer;
firstly, converting a communication protocol of a data acquisition system into an http protocol, then transmitting the http protocol to a server side for data caching through a network, transmitting acquired data to a central side server for summarizing by a plurality of servers, and performing data storage and data processing in the next step to prepare for the next step of work.
S13: establishing an application layer;
and an operation and maintenance database of the power equipment is established at the layer, so that the data application service functions such as equipment state monitoring, equipment defect inspection and the like are realized, and an LSTM algorithm can be used for analyzing and predicting equipment degradation inflection points, processing equipment defects and making decisions in the next step.
S14: establishing an end user layer;
and the power transformation equipment management, monitoring, alarm event management and other works are performed at the central server side, and the data interaction with the existing system can be realized.
S2: applying the designed data twin system work frame to the operation and maintenance work of the power information system, and further refining the technical steps of the system level;
s21: constructing a front end sensing network of the system;
the front end sensing is an entrance and a channel for realizing data sensing interconnection of the data twin system, and because the types and the quantity of the electric power equipment are huge and the situation structure of the electric power equipment is complex, the electric power equipment needs to be evaluated and designed from a plurality of indexes such as operation and maintenance cost, operation stability, data safety, defect detection effectiveness and the like, and typical equipment for data sampling is selected by combining the model number of the equipment, the operation period of the equipment and the actual operation condition of the equipment, so that a differential and hierarchical data sensing device is realized, and further, the operation and maintenance of the equipment of the same type are guided by summarizing and extracting the equipment image. The working process mainly occurs in the equipment layer and the acquisition layer constructed in the step S1, and the front-end sensing network of the system performs data sensing and data selection according to the operation characteristics of different equipment. In addition, the same kind of characteristics can be cross-verified by using a sensing device with non-homology or non-same principle, and the method can solve the problem of reliability of the alarm signal, so as to improve the defect cognition accuracy of the equipment.
S22: predicting and evaluating the state of the equipment;
the transformer substation data twin system frame constructed in the step S1 can know that after data acquisition is carried out, the obtained final equipment data can enter an application layer, and the application layer further evaluates and predicts the state of the equipment, and the specific working steps are as follows: the real-time operation data of the equipment obtained in the last step are continuously optimized by utilizing an artificial intelligence technology, an equipment state classification evaluation model, an equipment operation state prediction model and a multi-parameter association relation analysis model are utilized, the obtained results and equipment defect record data are combined to conduct next research and analysis, further, the change rules of the electric equipment of each type and parts thereof under different operation periods, operation conditions and operation environments are summarized, the real-time data and the historical operation data are combined to make accurate predictions on the equipment operation states in a future period, if the predicted results exceed the equipment normal operation values, early fault early warning can be achieved, the operation and maintenance work is assisted to the staff, and risks and losses are minimized.
S23: performing defect diagnosis on the equipment to assist decision making work;
the transformer substation data twin system frame constructed in the S1 can know that after the application layer finishes the equipment state evaluation and prediction work, the final result can be fed back to the user layer, and the two layers can perform data interaction, so that the system can diagnose the defects of equipment more accurately and make decisions. And the accumulated equipment operation data and the past working experience of staff are combined by utilizing the technologies of data intelligence, knowledge graph and the like, the auxiliary decision-making research of equipment defect diagnosis is carried out, and the data twin expert knowledge base is further perfected. The equipment defect diagnosis knowledge standard template is formulated, operation information of various types of equipment and abnormal performance and abnormal data values when defects occur are summarized and analyzed, the equipment information is extracted from standard guidelines and defect cases, and the comments and experiences of each expert are collected to form a complete knowledge base; the knowledge graph can be used for searching the equipment defect record to determine the specific type of the defect, so that the possible cause and the occurrence probability of the defect are obtained according to the defect type analysis, the screening, analysis, prediction and the defect processing scheme of the data twin system under the equipment defect scene are realized, and the algorithm flow can be shown as shown in figure 3.
S24: establishing a standard of a data twin system;
in order to further expand the working range of the data twinning system, specific standards for the data twinning of the power equipment are required to be formulated. The labeling mainly comprises a data twin system architecture standard, a device state acquisition standard, a data interface standard and a device data model delivery standard. Through detailed labeling, the method can be applied to the data twinning construction work of power grid equipment to form a system equipment operation and maintenance management rule based on data twinning, and guide the operation and maintenance work of equipment such as conventional electrical equipment, sensing devices and the like.
S3: the practical case is applied to research and analysis of the data twin system of the operation and maintenance of the power information system;
after a transformer substation data twin system framework is successfully constructed and main working technical steps are realized in each system layer, the system is researched and analyzed by using real cases so as to observe the actual application effect of the system.
S31: analyzing an abnormal temperature rise alarm example of a main transformer of a 35kV transformer substation;
due to hot weather, the main transformer load rate of a certain 35kV transformer substation is up to 90%. The data twinning system predicts future trends using LSTM algorithm models. Fig. 4 and 5 are the comparison of the actual value and the predicted value of the phase temperature of the main transformer low-voltage bushing X, Y of No. 1.
After the steps are completed, the system combines the historical data value with future data predicted by the LSTM algorithm, and transmits the combined historical data value and the future data as input values to a support vector machine classification algorithm model, and the classification model judges whether the current equipment operation trend has abnormal operation or not.
If the system judges that the development trend of the equipment is abnormal, a correlation analysis module is triggered, all feature data of the equipment in the near two weeks are analyzed, feature elements with higher correlation are analyzed and summarized, and corresponding maintenance strategies are formulated for the feature elements. Meanwhile, the system pushes the alarm information and the processing strategy to terminal operation and maintenance personnel, and the measure can solve the abnormal situation in time, so that the fault risk and the fault influence are minimized.
S32: judging partial discharge defects in a 35kV transformer substation switch cabinet;
the transient voltage data of 32 switch cabinets in the transformer substation are monitored in real time and uploaded to a data twinning system, the system sorts and cleans the acquired data, and the data change result after the transient voltage cleaning of the switch cabinets is shown in fig. 6.
And then taking the discretized trend data as an input characteristic value, training the XGBoost algorithm model, and carrying out state classification and evaluation on the known data by using the XGBoost classification model by the system, so that the algorithm can predict whether the running state of the equipment is normal or not through the voltage trend value, successfully detect and locate abnormal equipment, and timely process the abnormal equipment, thereby avoiding the occurrence of a larger crisis.
S4: summarizing the problems from the operation results of the actual cases and carrying out the next working plan;
through the experiment and analysis of the real case in the previous step, the analysis is carried out aiming at the experimental result, and the method mainly comprises the following aspects:
(1) From the algorithm point of view, since the detailed structure of the inside of the current algorithm model for processing large-scale data is still unknown, the output result of the algorithm model is difficult to deduce by logic, and the equipment operation and maintenance unit bears the risk brought by decision errors, so that further analysis and research on the interpretability and reliability of the algorithm model are needed.
(2) From the data perspective, the over-fitting phenomenon is easy to occur due to the imbalance of the number of positive and negative samples, so that on one hand, equipment with high defect occurrence rate is monitored to accumulate more development trend data of the equipment in an abnormal state; on the other hand, the method simulates the fault condition of real equipment in a laboratory scene, and explores an algorithm for acquiring unbalanced samples and learning small samples.
(3) In the aspect of a sensing device, a large number of miniaturized, low-power-consumption and high-reliability sensors are arranged to sense the state of the power equipment in a comprehensive system. Meanwhile, along with the continuous increase of data volume and continuous improvement of data quality requirements, the sensor is further improved in the aspects of high precision, integration and the like.
The invention has the beneficial effects that: the invention provides an operation and maintenance method of an electric power information system based on data twinning, which focuses on the application of the data twinning in the operation and maintenance field of electric power equipment, expounds the connotation and characteristics of the data twinning of the electric power information system, further constructs a basic frame of the data twinning system of the electric power equipment, and in practical application, the method can be found out through multiple times of verification.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, and alternatives falling within the spirit and principles of the invention.
Claims (9)
1. A data twinning-based power information system, characterized in that: comprises a device layer, an acquisition layer, an application layer and a user layer in turn according to the data transmission direction,
the equipment layer is used for collecting operation data of the power transformation equipment;
the acquisition layer standardizes a communication protocol, and performs network transmission and storage on operation data of the power transformation equipment;
the application layer receives the equipment operation data of the acquisition layer to establish an electric operation data base, evaluates and predicts the state of the equipment and generates alarm information;
and the user layer receives the alarm information and performs data interaction with the application layer to generate an overhaul strategy.
2. A data twinning-based power information system in accordance with claim 1, wherein: the equipment layer comprises transformer, switch cabinet, gas-insulated metal-enclosed switchgear of combined electrical apparatus, arc suppression coil, reactive compensation equipment, power distribution complete equipment and other power transformation primary equipment, relay protection and communication screen cabinet secondary equipment, and video recorder and inspection robot for collecting operation data of the power transformation equipment.
3. A data twinning-based power information system in accordance with claim 1, wherein: the data transmission protocol standard unit converts the communication protocol of the data acquisition layer into an http protocol, and the http protocol is transmitted to the video server and the inspection server through a network to carry out data caching, and each server transmits the acquired data to the central server to be summarized.
4. A data twinning-based power information system in accordance with claim 1, wherein: the application layer is provided with an expert knowledge base and an intelligent analysis unit, the expert knowledge base stores historical operation data, and the intelligent analysis unit analyzes and predicts the operation state of the equipment based on the expert knowledge base data and the power operation data.
5. A data twinning-based power information system in accordance with claim 1, wherein: the application layer is provided with an equipment monitoring unit, an expert knowledge base, a transformer substation overview, an intelligent analysis unit and a system management unit.
6. A data twinning-based power information system in accordance with claim 1, wherein: and the user layer and the application layer perform data interaction, perform auxiliary decision making for equipment defect diagnosis based on equipment operation data and historical experience data by utilizing a data intelligence and knowledge graph technology, and update an expert knowledge base.
7. The utility model provides a power information system operation and maintenance method based on data twinning which is characterized in that: comprises the following steps of the method,
s1, collecting operation data of power transformation equipment;
s2, network transmission and storage are carried out on operation data of the power transformation equipment through a unified standard protocol;
s3: establishing an electric power operation and maintenance database based on the stored operation data, combining the electric power operation and maintenance database data with historical operation data, and evaluating and predicting the state of the equipment to generate alarm information;
s4: and receiving the alarm information and carrying out data interaction with an application layer to generate an overhaul strategy.
8. The method for operating and maintaining a power information system based on data twinning as claimed in claim 7, wherein: in S3, the LSTM algorithm is used to analyze and predict the degradation inflection point of the device, process the defect of the device, and make the next decision.
9. The method for operating and maintaining a power information system based on data twinning according to claim 8, wherein: and S3, based on the real-time operation data of the equipment, the equipment operation state is evaluated by adopting an equipment state classification evaluation model, an equipment operation state prediction model and a multi-parameter association relation analysis model, the obtained result is spliced with the equipment defect record historical data, the equipment state classification evaluation model is input, the future period of operation state of the equipment is predicted, and if the predicted value exceeds the normal operation value of the equipment, fault early warning processing is performed.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116894064A (en) * | 2023-07-18 | 2023-10-17 | 国网信息通信产业集团有限公司北京分公司 | Intelligent integrated power-transformation auxiliary control data system and method |
| CN116956720A (en) * | 2023-07-19 | 2023-10-27 | 安徽斯维尔信息科技有限公司 | Industrial digital twin simulation operation and maintenance system |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116894064A (en) * | 2023-07-18 | 2023-10-17 | 国网信息通信产业集团有限公司北京分公司 | Intelligent integrated power-transformation auxiliary control data system and method |
| CN116894064B (en) * | 2023-07-18 | 2024-04-09 | 国网信息通信产业集团有限公司北京分公司 | Intelligent integrated power-transformation auxiliary control data system and method |
| CN116956720A (en) * | 2023-07-19 | 2023-10-27 | 安徽斯维尔信息科技有限公司 | Industrial digital twin simulation operation and maintenance system |
| CN116956720B (en) * | 2023-07-19 | 2024-01-30 | 安徽斯维尔信息科技有限公司 | Industrial digital twin simulation operation and maintenance system |
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