木质生物质理化性质指标预测模型建立及应用

Prediction Model Development and Application for Physical and Chemical Properties Indices of Woody Biomass

为分析生物质燃料的基础理化性质指标间的相关性,同时为生物质电厂提供一种简易便捷的燃料高位发热量和元素分析指标预测方法,利用皮尔逊相关分析法,分析了生物质电厂燃料的高位发热量、元素分析以及工业分析等各指标间的相关性;在此基础上,以发热量和元素分析指标为因变量,工业分析指标为自变量,建立起具有定量关系的多元线性回归预测模型;利用误差分析方法,对所建立的回归方程预测效果进行评估。结果表明,在各变量适用范围内,多元线性回归方程预测值与实测值较为接近,误差较小,可为木质生物质燃料的高位发热量和元素分析等指标的确定提供依据和参考。

In order to analyze the correlation between basic physical and chemical property indices of biomass fuels, and propose a simple and convenient prediction method of fuel＇s gross calorific value and elemental analysis indices for biomass power plants, the correlation among each index of woody biomass fuels by using the method of Pearson correlation analysis, such as gross calorific value, elemental analysis, industrial analysis. Based on the results of the correlation analysis, the multivariate linear regression models were built with calorific value and elemental analysis as dependent variables, while industrial analysis as independent variable. Finally, the prediction effects of the regression models were evaluated by the error analysis. The results show that within the applicable ranges of the variable values, the difference between the predicted values gained from the multiple linear regression models and the measured values is small, leading to the tiny prediction errors. Therefore, the prediction results of the multiple linear regression models can be utilized as references or basis to determine the gross calorific value and elemental analysis of wooden biomass fuel.