CAJ | 학술논문

对现有配煤掺烧系统仅计算混煤吨单价而忽略煤耗引起的燃料成本差异的问题进行了研究。采用基于神经网络建模预测飞灰含碳量的方法，计算掺烧（标）煤耗，进而得到单位发电燃料成本。该方法在湖南某电厂的实施结果表明：该模型预测准确性高，用于指导电厂实际掺配工作经济效益显著。
대현유배매참소계통부계산혼매둔단개이홀략매모인기적연료성본차이적문제진행료연구。채용기우신경망락건모예측비회함탄량적방법，계산참소（표）매모，진이득도단위발전연료성본。해방법재호남모전엄적실시결과표명：해모형예측준학성고，용우지도전엄실제참배공작경제효익현저。
This paper studied the existing problem that the blending coal system only calculated the mixed coal price while ignoring the difference in fuel costs caused by coal consumption. It used the method for predicting the fly ash carbon by neural network modeling, calculated blending (standard) coal consumption, and then got the unit cost of power generation fuel. Using this method results in the implementation of a power plant in Hunan show that:the model had high predictive accuracy, by using this method to guide the work of the actual blending coal had achieved the significant economic benefits.