Research On Scene Analysis And Visualization Of Power Station Operation Monitoring System Based On Big Data

With the rapid economic development in our country,the demand for electric energy in various fields is increasing day by day.In order to adapt to the trend of rapid development of the power industry,it is necessary for the power station to further enhance its stability,handle operational defects in time and ensure the safety and reliability of power production.Power station monitoring system is one of the most important information platform for power production enterprises,the purpose is to improve the monitoring and analysis capabilities through the unified management of power plant operation data.Now that the power station monitoring system has accumulated a large amount of data,including unstructured operational logs and structured indicator data,the analysis and utilization of these data are still in its infancy.The level of automation is very low,consuming manpower and resources,and lacking in timeliness.In order to improve the utilization of the power station's monitoring data and enhance the lean management level of the power station equipment,this paper takes the monitoring data of the pumped storage power station as the research object.Based on the internship in Xinyuan Company of State Grid,In this paper,a scene analysis model suitable for power plant monitoring and supervising was put forward and a scenario analysis and visual decision support system based on Spark big data processing framework was designed.Specific research work and the results of this paper:(1)In-depth exploration of the development and existing achievements of the operation and maintenance of power station and supervising the operation of the power station,studying the idea of the traditional scenario analysis method and putting forward the scene analysis requirements for the power station monitoring and supervision system.(2)Collecting and organizing the data of surveillance and monitoring of major domestic Pumped Storage Power Stations for nearly five years,feature extraction and classification of data based on the Spark Big Data Processing Framework,researching the preprocessing,and then constructing the scene generation,reduction and Classification model,and putting forward the decision support method of power plant supervision deficiencies.(3)The scene analysis model and visualization technology are combined to design the scene analysis and visual decision support system of power station monitoring and supervising,and effectively improve the utilization level of the power station monitoring data and providing auxiliary support for power production.