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一直以来电站锅炉面临着降低运行成本的要求,锅炉效率作为反映电站机组经济运行的重要参数之一,它的优化问题受到广泛的关注。由于锅炉系统结构及运行条件复杂,为了降低运行成本,机组负荷变化时往往需要调整很多的运行参数,这对于现场的监控和调整难度较高。借助粗糙集方法来发现数据间隐含的关系,对影响锅炉效率的参数进行约简,从而确定出目标优化参数。利用某600 MW燃煤电站机组历史数据中提取得到的稳定运行工况下的数据,通过模糊聚类方法进行离散化,利用粗糙集方法进行属性约简,并从约简后的结果提取其中重要的决策规则,并采用置信度和支持度作为评价指标,获得目标参数的优化区间,给出可行的烟气含氧量的优化调整方案。
The power plant boilers have been facing the requirement of reducing the operating costs. Boiler efficiency, as one of the important parameters reflecting the economic operation of power plant unit, has attracted wide attention. Due to the complicated structure and operating conditions of the boiler system, in order to reduce the operation cost, a lot of operation parameters are often required to be adjusted when the load of the unit is changed, which is difficult to monitor and adjust on site. Using rough set method to find out the implied relationship between the data, the parameters that affect boiler efficiency are reduced, so as to determine the target optimization parameters. Based on the data of stable operating conditions extracted from the historical data of a 600 MW coal-fired power plant unit, the data were discretized by fuzzy clustering method, the attribute reduction was made by using the rough set method, and the important data were extracted from the result after reduction The decision-making rules are adopted, and the confidence interval and the support degree are used as the evaluation index to obtain the optimization interval of the target parameters, and the feasible adjustment scheme of flue gas oxygen content is given.