Keywords: grid automation, data mining, assisted decision-making
Chinese Classification Number: TP2 Literature Identifier: A Article Number: 1672-3791(2012)06(c)-0027-01
In recent years, with the rapid development of science and technology, the application of database technology is also more widely used, and most of the databases are only for data entry, statistics and query operations. Nowadays, most of the databases are only for data entry, statistics and query and other operational processing, the processed information is only a part of the information contained in the database, and can not be effective description and prediction of the overall characteristics of the data and development trends, and the application of data mining technology for grid automation to dig out more useful information knowledge and patterns, and provide more convenient decision-making support.
1 Overview of data mining
Data mining can also be called pattern discovery and knowledge discovery, etc., from different perspectives with a different overview of the understanding from a technical point of view, it is in a large amount of data in the use of various types of analytical tools to discover the process of data and the relationship between the model, based on these models and relationships to be able to make predictions; from the commercial point of view, it is a decision-making process, mainly using AL machines and statistics. The main use of AL machines and statistics and other technologies to automate the analysis of the original data of the enterprise, and make inductive reasoning, mining its potential patterns, so as to predict customer behavior, thus helping business decision makers to make adjustments to the market strategy, to avoid risk and make the right decision.
2 Application of data mining in grid automation
2.1 Application of data mining in scheduling operation of power system
Scheduling operation of the power system is in the core position, its task is to process a large amount of information on the system in real time, and to make the corresponding decisions, with the operation of the power market mechanism, the scheduling center not only to ensure the stability and security of the system, but also to ensure the stability and security of the various economic and social conditions. With the operation of the power market mechanism, the dispatch center not only to ensure the stability and security of the system, but also to consider a variety of economic issues, from the investor's point of view to consider its economic interests, and develop a more reasonable price of electricity, so that the scheduling operation is more complex to develop a scientific and standardized decision-making, you need to data mining technology to support the strong. Power system is divided into normal state, emergency state, alert state, test state and recovery state. When a certain state is determined, it will be sent to the operator, and complete the operation, and data mining algorithms will be able to help it to classify the processing, so that the instructions are more accurate and timely, and can describe the operating state of the power system, such as the emergency state of the power system, can be a number of bus voltage reduction and other characteristics of better discovery and description.
2.2 Data mining in the power system fault analysis and planning design
In the power system, fault acceptance system will accumulate a large amount of data, and take data mining technology can be hidden in the data of many facts, associations, and factors and other valuable information to be distilled, such as the use of data mining technology in the correlation analysis can be the cause of the failure and other factors to be analyzed. Correlation analysis can analyze the cause of failure and other factors, such as rainfall, temperature, load and lightning and other factors, in order to analyze the cause of failure in line with the objective law, and the use of sequence pattern method to find out the same pattern and common failure components, and then according to the classification method of common failure components to analyze and find out the rules, and as a key preventive maintenance reference to ensure that the safety and reliability of the power system. Power system planning and design, the need for load model caused by a variety of system structure may occur when the failure to consider and planning, to determine the parameters of the control and protection devices, we must process a large amount of data, and data mining can be used in a variety of analytical tools to analyze the model and the relationship between the data, and to determine the corresponding operating rules and failure response strategy.
2.3 Data mining can be used to assess the stability and safety of the power system and monitor the operation status
Using the decision tree method in data mining can classify the operation status of the power system as stable and unstable, and automatically analyze the system data according to the corresponding rules until the status is set to be stable, and then use the extracted knowledge of safety assessment to give guidance on possible safety hazards in the normal operation of the system. The extracted safety assessment knowledge can be used to give guidance to the potential safety hazards in the normal operation of the system, and the visualization technology can be used to analyze the stability and make decisions to improve the safety and stability of the power system. Relevant staff can use the state monitoring and predictive diagnostic results derived from data mining technology, scanning of the power system, and the problems found in a timely manner to give maintenance to prolong the service life of the equipment, reduce the cost of maintenance, so as to ensure the stable operation of the system.
3 Data mining in the grid automation decision-making and application
3.1 Data mining in the grid planning decision-making
Data mining technology in the monitoring, operation and planning of the power grid play a role in assisting decision-making, the next to the decision-making of the grid planning as an example of the decision-making process of the analysis of the grid planning decision-making is mainly centered on the changes in the supply load, the power sector, the power sector, the power sector, the power sector, the power sector, the power sector, the power sector, the power sector, the power sector, the power sector and the power sector. To carry out, the power sector decision makers need to grasp the relevant first-hand information at any time, and the load characteristics of the changes in the analysis and research, so as to adjust the grid planning strategy, the entire grid planning work mainly includes the collection of information activities, design activities, decision-making program evaluation, program selection and implementation and the internal environment of the enterprise, etc., in the collection of information activities in the stage, the need to carry out an assessment of the changes in the power supply load, and collect information about the transformer In the collection phase of intelligence activities, the need to assess the power supply load changes, and collect information about the substation load, new product information and new technologies, so as to make the decision-making goals, in the design phase of the activities, the need for decision makers based on the intelligence of the research and planning program, to give the relevant views, so as to assess the results of the program, in the program selection phase, the need to consider the effectiveness of the program, so as to use the 4PS strategy to develop a planning strategy that meets the requirements.
3.2 Application of Data Mining in Grid Automation Monitoring System
Grid automation monitoring system for the safe operation of the entire power system plays a safeguarding role, but when the power grid is found to exist in the security risks, if not to carry out the auxiliary decision-making tools for the calculation, only relying on experience to give the control measures, it will affect the entire accuracy of the grid security control, the power system is very important to mine the data in the power system, so as to ensure the safety of the power system, the power system is a very important part of the power system. In the data mining is very necessary, grid automation in the data mining mainly real-time business and quasi-real-time business two kinds of real-time business is the substation monitoring system in real-time data, and quasi-real-time business mainly includes fault recording, power billing metering information and security protection automatic device management data, which can be given to a large number of real-time data to the online analysis and processing and decision-making. Power equipment can be divided into primary and secondary equipment according to different functions, in which the primary equipment includes transformers, compatible equipment and switches and other monitoring systems, and the secondary equipment has relay protection, automatic devices, fault recorders and on-site monitoring and so on. Now most of the power system is the use of fieldbus to realize the data convergence, transmission and command of the conveyor control, this fieldbus technology land area is small, flexible configuration, reliability is also relatively high, but when the amount of data is relatively large, there will be a response to the phenomenon of slow, in order to further improve the function of the grid automation monitoring system, the need for further mining of the data, can be based on In order to further improve the function of the grid automation monitoring system, it is necessary to further mine the data, which can be used to troubleshoot grid faults based on the grid operation mode and stability changes, and according to the real-time dynamic information of the grid, the full-time domain simulation method in EEAC is used to carry out the quantitative assessment of the stability of the grid, after data mining, it is also possible to carry out on-line identification of the generator, substation equipment parameters, models and composites based on the grid's dynamic data, and the results of the identification can be used in the calculation of the power grid, in order to enhance the accuracy of the calculation. The results of the identification can be used in the calculation of the power grid to improve the accuracy of the calculation, but also based on the automatic protection device action behavior of the power grid stability and security analysis and protection.
4 Conclusion
With the rapid development of computer technology, grid automation data mining technology has been widely used, and has made great contributions to the entire power system, which provides reliable data security in the scheduling operation, monitoring systems and fault handling, etc. Of course, the application of its application is still a lot of shortcomings, the need to increase the data mining to provide more reliable auxiliary decision-making for the power system. It is necessary to increase the data mining, in order to provide more reliable auxiliary decision-making for the power system.
References
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