CN114090667A - Distributed intelligent integrated management platform for cross-basin hydropower station group - Google Patents
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Abstract
The invention belongs to the technical field of intelligent power generation. A distributed intelligent integrated management platform for a cross-basin hydropower station group comprises a management information I area, a management information II area and a real-time and non-real-time control large area; the management information I area, the management information II area and the real-time and non-real-time control large area are respectively set into separate local area networks, each network is isolated safely through firewall equipment, and the management information II area synchronizes the acquired data to the real-time and non-real-time control large area for storage; the management information I area manages the acquired data. The distributed intelligent comprehensive management platform for the cross-basin hydropower station group is based on the production and operation characteristics of each hydropower station at present, adopts a longitudinal layered and transverse partitioned system structure, can realize safety, reliability, economy, high efficiency, flexibility and intelligence of hydroelectric power generation, and realizes the automatic diagnosis and early warning functions of the state of production equipment.
Description
Technical Field
The invention belongs to the technical field of intelligent power generation, and particularly relates to a distributed intelligent comprehensive management platform for a cross-basin hydropower station group.
Background
With the increasing of the number of the plant stations accessed to the controlled plant station by the centralized control center according to a plan, the continuous expansion of the intelligent sensing and execution, intelligent control and optimization requirements of the plant station enables the high-speed and massive real-time data exchange between the centralized control center and the plant station to be multiplied, the high-efficiency processing, compression, filing, storage organization and query retrieval strategies of the repeated data and intelligent basic sensing data of multiple systems are optimized, the research and development of intelligent execution and control technologies for providing clear and accurate intelligent data analysis results for more applications becomes more important, and the data resource integration is developed into the necessary route of the productivity improvement and production relation optimization of the traditional power enterprises. Meanwhile, along with the great improvement of the precision and the sensitivity of the intelligent sensor of the plant station, the continuous change of the operation condition and the production operation environment of the unit, the alarm system of the traditional computer monitoring system mainly aiming at real-time section data is still limited by the manual conservative setting of a fixed alarm threshold value, so that the situations of missing report and false report of state information occur, a large number of maintenance personnel are required to continuously correct system parameters, the traditional system is continuously optimized and upgraded, and under the condition that the maintenance real-time property cannot be ensured, the operation monitoring, the production operation, the risk management and control and the analysis decision of the operation personnel are greatly limited.
Therefore, a safe, reliable, economical and efficient distributed intelligent comprehensive management platform for the cross-basin hydropower station group is urgently needed to realize the automatic diagnosis and early warning functions of the state of the production equipment.
Disclosure of Invention
The invention overcomes the defects of the technical problems and provides a distributed intelligent comprehensive management platform for a cross-basin hydropower station group, which can realize safe, reliable, economical, efficient, flexible and intelligent hydroelectric generation and realize the automatic diagnosis and early warning functions of the state of production equipment.
In order to solve the technical problems, the invention adopts the following technical scheme:
the utility model provides a cross basin water power station crowd distributing type intelligence integrated management platform which characterized in that: the system comprises a management information I area, a management information II area and a real-time and non-real-time control large area; the management information I area, the management information II area and the real-time and non-real-time control large area are respectively set into separate local area networks, each network is isolated safely through firewall equipment, and the management information II area synchronizes the acquired data to the real-time and non-real-time control large area for storage; the management information I area manages the acquired data;
the management information I area comprises a power plant production management system; the power plant production management system is a junction of a hydropower station data integration platform, information and application, and flood control dispatching of watershed hydropower station groups is realized;
the management information II area comprises an information acquisition module, a WEB release module, an APP service module, an intelligent report module, a trend analysis module and an intelligent alarm module; the information acquisition module is used for acquiring running parameters such as running information of the hydroelectric equipment, state information of the hydroelectric equipment, working condition changes and the like; the WEB release module is externally used in a service form and can intensively and remotely check the communication messages and the state information of the hydroelectric equipment; the APP service module is used for remotely monitoring the production operation condition of the hydropower station in real time, checking the working state of equipment and analyzing main production operation indexes of the hydropower station; the intelligent report module is used for reading required data from the real-time database, performing characteristic extraction, automatic analysis and statistical judgment on the data, generating a report according to a predefined report template, and automatically finishing the generation of a production data report; the trend analysis module is used for establishing a hydropower intelligent alarm model according to characteristic data and related operation experience of long-term operation of hydropower equipment on the basis of a historical data interface and a real-time data interface, eliminating interference data and judging a characteristic trend by establishing a characteristic extraction method according with the operation condition of the hydropower station equipment; the intelligent alarm module is used for setting an early warning rule for the operation parameters of the hydroelectric equipment, establishing an auxiliary analysis decision-making library, dynamically monitoring the change trend of the operation parameters of the hydroelectric equipment in real time, comparing historical parameters under the same working condition, and sending alarm information if the early warning rule is started;
the real-time and non-real-time control large area comprises a monitoring system, a water regulation system, an electric energy acquisition system and a protection management system; the monitoring system is connected with the management information I area and the management information II area, so that various data can be called, and the control function of the hydropower equipment can be realized; the water regulation system is used for providing water regime data, and is convenient for the management information II area to call the water regime data so as to carry out report statistics, real-time display, data analysis and alarm; the electric quantity acquisition system is used for providing generated energy data of each unit of the hydropower station, and the protection management system is used for realizing parameter adjustment and system control of the hydropower equipment according to a system control instruction.
As a further improvement of the invention, the platform adopts an SOA architecture based on Web services.
As a further improvement of the invention, the data interface of the platform supports the standard IEC104 or Modbus standard communication protocol.
As a further improvement of the invention, the real-time and non-real-time control large area adopts a distributed real-time database and a distributed historical database architecture.
As a further improvement of the invention, the trend analysis module comprises a BP neural network model building module and a fault prediction module, the BP neural network model building module is used for building a BP neural network model, and the fault prediction module carries out real-time prediction on the operation condition of the hydropower station equipment by using the built BP neural network model.
As a further improvement of the invention, the feature extraction method needs to preprocess data, and the preprocessing of the data comprises data format normalization, data validity check and data time information processing.
Compared with the prior art, the invention has the following beneficial effects:
the distributed intelligent comprehensive management platform for the cross-basin hydropower station group adopts a longitudinal layered and transverse partitioned system structure based on the production and operation characteristics of each hydropower station at present, a management information I area is a hub of the whole platform, and an automatic and information system of each power plant is taken as a basis; the system comprises a real-time control area, a non-real-time control area, a platform, a power supply system and a power supply system, wherein the real-time control area and the non-real-time control area are used for calling various data and realizing the control function of hydropower equipment, the platform is longitudinally divided into a plurality of application layers according to different applications, the platform is transversely divided into different safety areas according to the applications, safety isolation is implemented between the safety areas through firewall equipment, information interaction is carried out according to the safety protection regulations of an electric power secondary system, and meanwhile, the system provides information and service interaction aiming at regional power grids and downstream power plant applications according to application requirements.
The fault prediction module predicts the operation condition of hydropower station equipment in real time by utilizing an established BP neural network model, can perform modeling according to a unified standard equipment object, fully combines the related operation experience of operators and the characteristic historical data of long-term operation of the hydropower equipment, fits the characteristic historical data with time dimension to form a sample array, inputs the sample array into a neural network inference machine for training, dynamically finds out an operation interval with proper related physical quantity from the sample array through the self-learning of the BP neural network, and realizes the automatic diagnosis and early warning functions of the state of production equipment.
Drawings
FIG. 1 is a structural block diagram of a distributed intelligent integrated management platform of a cross-basin hydropower station group according to the invention;
fig. 2 is a diagram of the overall data transmission architecture of the present invention.
Detailed Description
The invention is further described with reference to the following figures and examples. It should be noted that the specific embodiments of the present invention are only for clearly describing the technical solutions, and should not be taken as a limitation to the scope of the present invention.
Referring to fig. 1-2, a distributed intelligent integrated management platform for a cross-basin hydropower station group includes a management information I area, a management information II area, and a real-time and non-real-time control large area; the management information I area, the management information II area and the real-time and non-real-time control large areas are respectively set into independent local area networks, each network is safely isolated through firewall equipment, the platform distributes independent data channels for each data transmission link, and the management channels are separated from the data channels, so that the data transmission is not interfered with each other; by carrying out statistical analysis management technology on each data channel, the data transmission priority and flow distribution management among the data channels is achieved, and the data transmission efficiency maximization of colleagues guaranteeing timeliness is guaranteed; the management information II area synchronizes the acquired data to a real-time and non-real-time control large area for storage; the management information I area manages the acquired data;
the management information I area comprises a power plant production management system; the power plant production management system is a junction of a hydropower station data integration platform, information and application, and flood control dispatching of watershed hydropower station groups is realized; the system also comprises an ERP system and other learning systems for hydropower station enterprise management.
The management information II area comprises an information acquisition module, a WEB release module, an APP service module, an intelligent report module, a trend analysis module, an intelligent alarm module and other data analysis modules; the information acquisition module is used for acquiring running parameters such as running information of the hydroelectric equipment, state information of the hydroelectric equipment, working condition changes and the like; the WEB release module is externally used in a service form and can intensively and remotely check the communication messages and the state information of the hydroelectric equipment; the APP service module is used for remotely monitoring the production operation condition of the hydropower station in real time, checking the working state of equipment and analyzing main production operation indexes of the hydropower station; the intelligent report module is used for reading required data from the real-time database, performing characteristic extraction, automatic analysis and statistical judgment on the data, generating a report according to a predefined report template, and automatically finishing the generation of a production data report; the feature extraction method needs to preprocess data, and the preprocessing of the data comprises data format normalization, data validity check and data time information processing; the trend analysis module is used for establishing a hydropower intelligent alarm model according to characteristic data and related operation experience of long-term operation of hydropower equipment on the basis of a historical data interface and a real-time data interface, eliminating interference data and judging a characteristic trend by establishing a characteristic extraction method according with the operation condition of the hydropower station equipment; the intelligent alarm module is used for setting an early warning rule for the operation parameters of the hydroelectric equipment, establishing an auxiliary analysis decision-making library, dynamically monitoring the change trend of the operation parameters of the hydroelectric equipment in real time, comparing historical parameters under the same working condition, and sending alarm information if the early warning rule is started;
the method comprises the steps of analyzing the change trend of the hydroelectric equipment, realizing the characteristic excavation of mass historical data of the equipment, summarizing the running conditions of the hydroelectric equipment under different running conditions and different running conditions, obtaining the incidence relation among different running parameters, and analyzing the running change trend of the hydroelectric equipment by utilizing the accumulated running conditions and fault samples of the hydroelectric equipment. When the data points do not reach the alarm value, the change trend value of the data points is calculated, the data change trend is monitored, and when the data change trend is compared with the historical stable value or the equipment fixed value and exceeds a set deviation value, early warning information is generated to inform operators in advance that the trend of the water and electricity equipment towards fault alarm exists. And (4) carrying out statistical analysis on the running time and the start-stop period of periodic starting equipment such as oil pumps, water pumps and air compressors of each unit. Through comparison with the historical stable operation value, when a large difference exists, production alarm is carried out, and efficiency change trend prediction is achieved.
And counting the out-of-limit alarm condition of the equipment, positioning the out-of-limit alarm condition to a detail list through the statistical information, and performing trend analysis on the out-of-limit data in the detail list. And counting the collected alarm record information of the important equipment according to the grade, the processing condition, the times, the duration and the like. And counting the collected start-stop record information of the important equipment, and positioning to a detailed list through the statistical information.
The real-time and non-real-time control area comprises a monitoring system, a water regulation system, an electric energy acquisition system, a protection management system and other service systems; the monitoring system is connected with the management information I area and the management information II area, so that various data can be called, and the control function of the hydropower equipment can be realized; the monitoring picture of the monitoring system can highlight the characteristics of the production flow and correctly display information such as production process data, equipment state, alarm state, economic indexes and the like. The monitoring system dynamically displays the running state of the unit, real-time main wiring, basin water conditions, dam monitoring pictures and main production flow process pictures of the unit, and monitors the running state of the unit in real time; the water regulation system is used for providing water regime data, and is convenient for the management information II area to call the water regime data so as to carry out report statistics, real-time display, data analysis and alarm; the electric quantity acquisition system is used for providing generated energy data of each unit of the hydropower station, and the protection management system is used for realizing parameter adjustment and system control of the hydropower equipment according to a system control instruction.
The distributed intelligent comprehensive management platform for the cross-basin hydropower station group adopts a longitudinal layered and transverse partitioned system structure based on the production and operation characteristics of each hydropower station at present, a management information I area is a hub of the whole platform, and an automatic and information system of each power plant is taken as a basis; the system comprises a real-time control area, a non-real-time control area, a platform, a power supply system and a power supply system, wherein the real-time control area and the non-real-time control area are used for calling various data and realizing the control function of hydropower equipment, the platform is longitudinally divided into a plurality of application layers according to different applications, the platform is transversely divided into different safety areas according to the applications, safety isolation is implemented between the safety areas through firewall equipment, information interaction is carried out according to the safety protection regulations of an electric power secondary system, and meanwhile, the system provides information and service interaction aiming at regional power grids and downstream power plant applications according to application requirements.
As a further improvement of the invention, the platform adopts an SOA architecture based on Web services, and the real-time and non-real-time control large area adopts a distributed real-time database and a distributed historical database architecture. And establishing a plug-in type, open and extensible dynamic application management platform, and taking various applications of the platform as service plug-ins for overall integration. The database cluster is used as a message engine, a stream processing engine is used for processing messages in the message cluster, near real-time warehousing and butt joint of real-time data of each centralized control center or hydropower station are achieved, and a parallel warehousing mode is adopted, and meanwhile warehousing real-time cache, a real-time data storage library and a historical data storage library are achieved.
The data interface of the platform supports standard IEC104 or Modbus standard communication protocol. The data interface integrates a plurality of core technologies such as network monitoring management, multi-level cache, flow control, high-concurrency data processing, three-dimensional network cache scheduling, safe gate-through data transmission and the like, and effectively guarantees the reliability, stability, instantaneity, accuracy and integrity of real-time data acquisition.
As a further improvement of the invention, the trend analysis module comprises a BP neural network model building module and a fault prediction module, the BP neural network model building module is used for building a BP neural network model, and the fault prediction module carries out real-time prediction on the operation condition of the hydropower station equipment by using the built BP neural network model. Model equipment in the BP neural network model building module is associated with the ledger information and the real-time operation data of the actual hydropower station equipment. The BP neural network is a network trained by a Back Propagation algorithm. In this embodiment, for the construction of the BP neural network model, assuming that there are n types of symptoms of the failure of the hydroelectric equipment, the output vector is X (X)1,x2,...xn) If m fault causes are possible to cause the symptom, the output vector is Y (Y)1,y2,...yn) The input layer is n neurons, the hidden layer is h neurons, the output layer is m neurons, and WijAs a connection weight between the input layer and the hidden layer, wjkFor the connection weight between the hidden layer and the output layer, the number of neurons of the hidden layer is related to the problem, and the value h can be obtained according to experience
In the meantime. When training BP algorithm samples, inputting learning samples (X)P,YP) And calculating an actual output OP, calculating a difference value between the actual output OP and the ideal input OX, and if the difference value is not within a preset threshold range, ending the training and predicting the corresponding learning sample as a fault point.
The method can be used for modeling according to a unified standard equipment object, fully combines the related operation experience of operators and the characteristic historical data of long-term operation of hydropower equipment, fits the data with time dimensions to form a sample array, inputs the sample array into a neural network inference machine for training, dynamically finds out an operation interval with appropriate related physical quantities from the sample array through error back propagation, association analysis and self-learning of a neural network, and achieves the automatic diagnosis and early warning functions of the state of production equipment.
The above description is intended to describe in detail the preferred embodiments of the present invention, but the embodiments are not intended to limit the scope of the claims of the present invention, and all equivalent changes and modifications made within the technical spirit of the present invention should fall within the scope of the claims of the present invention.
Claims (6)
1. The utility model provides a cross basin water power station crowd distributing type intelligence integrated management platform which characterized in that: the system comprises a management information I area, a management information II area and a real-time and non-real-time control large area; the management information I area, the management information II area and the real-time and non-real-time control large areas are respectively set into separate local area networks, and each network is safely isolated through firewall equipment; the management information II area synchronizes the acquired data to a real-time and non-real-time control large area for storage; the management information I area manages the acquired data;
the management information I area comprises a power plant production management system; the power plant production management system is a junction of a hydropower station data integration platform, information and application, and flood control dispatching of watershed hydropower station groups is realized;
the management information II area comprises an information acquisition module, a WEB release module, an APP service module, an intelligent report module, a trend analysis module and an intelligent alarm module; the information acquisition module is used for acquiring running parameters such as running information of the hydroelectric equipment, state information of the hydroelectric equipment, working condition changes and the like; the WEB release module is externally used in a service form and can intensively and remotely check the communication messages and the state information of the hydroelectric equipment; the APP service module is used for remotely monitoring the production operation condition of the hydropower station in real time, checking the working state of equipment and analyzing main production operation indexes of the hydropower station; the intelligent report module is used for reading required data from the real-time database, performing characteristic extraction, automatic analysis and statistical judgment on the data, generating a report according to a predefined report template, and automatically finishing the generation of a production data report; the trend analysis module is used for establishing a hydropower intelligent alarm model according to characteristic data and related operation experience of long-term operation of hydropower equipment on the basis of a historical data interface and a real-time data interface, eliminating interference data and judging a characteristic trend by establishing a characteristic extraction method according with the operation condition of the hydropower station equipment; the intelligent alarm module is used for setting an early warning rule for the operation parameters of the hydroelectric equipment, establishing an auxiliary analysis decision-making library, dynamically monitoring the change trend of the operation parameters of the hydroelectric equipment in real time, comparing historical parameters under the same working condition, and sending alarm information if the early warning rule is started;
the real-time and non-real-time control large area comprises a monitoring system, a water regulation system, an electric energy acquisition system and a protection management system; the monitoring system is connected with the management information I area and the management information II area, so that various data can be called, and the control function of the hydropower equipment can be realized; the water regulation system is used for providing water regime data, and is convenient for the management information II area to call the water regime data so as to carry out report statistics, real-time display, data analysis and alarm; the electric quantity acquisition system is used for providing generated energy data of each unit of the hydropower station, and the protection management system is used for realizing parameter adjustment and system control of the hydropower equipment according to a system control instruction.
2. The distributed intelligent integrated management platform for the cross-basin hydropower station group according to claim 1, characterized in that: the platform adopts an SOA architecture based on Web services.
3. The distributed intelligent integrated management platform for the cross-basin hydropower station group according to claim 1, characterized in that: the data interface of the platform supports standard IEC104 or Modbus standard communication protocol.
4. The distributed intelligent integrated management platform for the cross-basin hydropower station group according to claim 1, characterized in that: the real-time and non-real-time control large area adopts a distributed real-time database and a distributed historical database framework.
5. The distributed intelligent integrated management platform for the cross-basin hydropower station group according to claim 1, characterized in that: the trend analysis module comprises a BP neural network model building module and a fault prediction module, the BP neural network model building module is used for building a BP neural network model, and the fault prediction module carries out real-time prediction on the operation condition of the hydropower station equipment by using the built BP neural network model.
6. The distributed intelligent integrated management platform for the cross-basin hydropower station group according to claim 1, characterized in that: the feature extraction method needs to preprocess data, and the preprocessing of the data comprises data format normalization, data validity check and data time information processing.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116074321A (en) * | 2023-01-18 | 2023-05-05 | 长江生态环保集团有限公司 | Multi-station communication optimization system in urban water management centralized control system based on load balancing mode |
| CN116385206A (en) * | 2023-04-23 | 2023-07-04 | 中国长江电力股份有限公司 | Centralized control integrated intelligent management system for hydropower station |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116074321A (en) * | 2023-01-18 | 2023-05-05 | 长江生态环保集团有限公司 | Multi-station communication optimization system in urban water management centralized control system based on load balancing mode |
| CN116074321B (en) * | 2023-01-18 | 2023-10-27 | 长江生态环保集团有限公司 | Multi-station communication optimization system in urban water management centralized control system based on load balancing mode |
| CN116385206A (en) * | 2023-04-23 | 2023-07-04 | 中国长江电力股份有限公司 | Centralized control integrated intelligent management system for hydropower station |
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