电厂燃煤虚拟采样及发热量均值不确定度评定  被引量:3

Virtual Sampling of Fired Coal in Power Plant and Evaluation of Uncertainty of Mean Calorific Value

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作  者:刘福国 国钦光[3] 殷炳毅 王守恩 LIU Fu-guo;GUO Qin-guang;YIN Bing-yi;WANG Shou-en(State Grid Shandong Electric Power Research Institute,Jinan,Shandong 250003,China;Shandong Electric Power Research Institute,Jinan,Shandong 250003,China;Huadian Weifang Power Generation Co.,Ltd,Weifang,Shandong 261000,China)

机构地区:[1]国网山东省电力公司电力科学研究院,山东济南250003 [2]山东电力研究院,山东济南250003 [3]华电潍坊发电有限公司,山东潍坊261000

出  处:《计量学报》2021年第4期463-468,共6页Acta Metrologica Sinica

摘  要:检测发电厂效率时,由于锅炉燃煤发热量还未能实现广泛的连续测量,采用少量样品煤的实验室化验数据表示检测周期内燃煤的发热量会带来较大的测量误差。研究了入炉煤多次采样样品发热量平均值的不确定性,当发热量样本为正态分布,或求取平均值的样品个数大于30时,根据中心极限定理,可采用传统方法对样品均值的不确定度进行评定;当发热量样本为非正态分布,且求取平均值的样品个数小于30时,可采用挑选样抽法产生发热量的随机样本,进而得到发热量均值的虚拟样本,利用该样本进行非正态分布下发热量均值扩展不确定度计算。应用表明,该方法是合理的,满足发电机组效率检测不确定度分析的需要。The calorific value of coal fired in power plant has not been continuously measured in extensive pattern.In generator set efficiency measurement,the laboratory test results of a small amount of coal sample are used to express the calorific value of all coal fired during the measurement period,which brings about greater uncertainty in measurement.The uncertainty of mean calorific value of coal samples was studied.When the calorific sample belonged to normal distribution,or the number of samples for average value was more than 30,the uncertainty of mean calorific value could be evaluated by traditional methods according to the central limit theorem.When the calorific sample was in non-normal distribution,and the number of samples for average value was less than 30,random samples of calorific value could be produced by sampling inspection with screening,thereafter,the extended uncertainty under non-normal distribution was computed by virtual samples.The practical application showed that the method presented was reasonable and could meet the needs of uncertainty analysis in efficiency measurement of generating units.

关 键 词:计量学 煤热值 入炉煤样 虚拟采样 不确定度分析 挑选样抽法 

分 类 号:TB941[一般工业技术—计量学]

 

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