【作者】 隋丽颖；

【导师】 谭文； 黄孝彬；

【作者基本信息】 华北电力大学（北京） ， 控制理论与控制工程， 2010， 硕士

【摘要】 计算机技术的迅速发展使得大量的火电机组运行记录能够保存到实时／历史数据库中,这些海量数据的背后往往蕴藏着丰富的信息,利用数据挖掘技术对这些数据进行分析和应用对机组的优化运行有着重要的意义。本文的主要研究工作集中在利用基于聚类分析的数据挖掘技术对火电机组的运行记录进行工况的划分以及模式的挖掘。第一部分分析了数据挖掘技术在火电机组优化运行的研究现状及可行性,并介绍了单元机组运行调节的内容、基本方法。第二部分阐述了机组典型经济运行模式的总体设计思路。第三部分针对某600MW机组一个月的历史运行数据进行模式挖掘算法的数据实验,并分析了不同工况下的挖掘结果。试验结果表明,数据挖掘对机组运行模式的建立和分析具有实际的指导意义。更多还原

【Abstract】 The rapid development of computer technology enables a large number of operating records of thermal power units saved to the real/historical database, which is rich in information. Analysis and application of these data by the light of data mining technology has an important significance on optimal operation of units. This research mainly focuses on classifying records of the operation of thermal power unit by working conditions based on the clustering analysis of data mining technology and mining the operation modes.The first part is to analyze current status and feasibility of data mining technology in optimal operation of thermal power units, and introduce regulation, basic methods. The second part describes overall design ideas of typical economic operation mode of units. The third involves data experiment of mining algorithm on historical operating data of a 600MW unit for one month, and analysis of mining results under different conditions. These results show that data mining is significant in analyzing and building unit operation modes in practice.更多还原