Research And Application Of Data Mining In Thermal Power Plant

There is a large numbers of DCS (Distributed Control System) system data collected in real-time database of thermal power plant. There are abundant and valuable information, which benefits to enhancing the efficiency and safety of operation in thermal power plant, hidden behind these data. But the data resource are wasted generally because not be used for comprehend and mining effectively. The Data Mining techniques can intelligently and automatically discover knowledge from data. In this paper, the application of data mining techniques in thermal power plant will be researched, in the interest of full use the function of DCS system data collected in database to direct the power generation.This paper discussed the applied actuality of data mining techniques in the thermal power plant, and mostly researchs the data preprocessing techniques,the fuzzy c-means algorithm,OLAP(online analytical processing) and the application of these techniques.Considering the characteristic of the data in thermal power plant, this paper attempt to apply the data preprocessing techniques to the data process of real-time database for guarantees the validity of data, so based the foundation for the father work of data mining. This paper attempt to establish the multi-dimensional data model based on the analysis of the condenser performance, and the fuzzy c-means algorithm to be used for the process of the multi-dimensional data. On the base of the data that have been processed, made an multi-dimensional analysis on the vacuum data with the OLAP (online analytical processing) method in the pivot table of Excel, and the data can be viewed in different ways by use the OLAP operations such as slice,roll-up,drill-down and pivot, the rule and the knowledge behind these data can be mined finally.