【作者】 牛成林；

【导师】 于希宁；

【作者基本信息】 华北电力大学（河北） ， 控制理论与控制工程， 2006， 硕士

【摘要】 随着世界能源的紧张及竞争的加剧,作为耗能大户的电厂如何节能降耗变得越来越重要。同时,随着电站SIS和MIS的发展,大量历史数据被存入数据库。大量的信息如数据的整体特征及其发展趋势等隐藏在这些数据背后,它们对决策制定具有重要的参考价值,数据挖掘就是指从大量数据中发现潜在的有用信息。本文将数据挖掘引入电站运行优化,提出利用模糊关联规则挖掘算法挖掘电厂重要运行参数的优化目标值,以降低机组供电煤耗率,提高电站整体运行效率。比较试验表明,该方法具有较好的效果。更多还原

【Abstract】 With the lack of energy and the increase of competition, it is more and more importantfor power plant to decrease coal consumption. At the same time, with the development of SISand MIS in power plant, large amount of data were sent to database. Great knowledge wascontained in these data such as holistic character and trend. They are valuable to decisionmaking. Data mining is to find these valuable knowledge from large amount of data.This paper induced fuzzy association rule mining algorithm to find operation parameterstarget value to improve power plant efficiency. Experiments shows that this method canachieve a good effect.更多还原