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- 2017
基于Markov链的锅炉热负荷预测方法
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Abstract:
摘要： 基于Markov链的锅炉热负荷预测方法,提出多参数预测调控模型。根据室外温度,对日均供水温度进行Markov链预测,结合日均燃煤量、鼓风机频率、引风机频率等参数的状态空间,进行复合概率预测。具体应用时,将调控量的大概率最低值作为起点,根据监测量变化,优化调节。试验结果表明:在居民室温达标范围内,日均煤耗量较模型应用前降低约8%;日均供水温度降低约7%,燃煤投放准确率及调控精确率有效提升实现了锅炉热负荷的精细调控。
Abstract: The multi-parameter forecasting control model was proposed based on Markov chain of the forecasting method of coal-fired boiler heat load. In accordance with outdoor temperature, the average feed-water temperature was predicted. Then the compound probability was forecast with reference to the average daily fuel consumption, air-blower frequency and induced draft fan frequency. Conversely, the range of high probability was taken full advantage of to optimize the above mentioned three parameters.The experiment results showed that when the room temperature met the heating standards, the average daily fuel consumption was reduced by about 8 percent and the average daily feed-water about 7 percent after the forecasting control model was carried out,the accuracy of coal burning and operation control promoted effectively.This method provided a new way of the fine control of boil heat load
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