Prediction of calorific value of coal using real power plant data

摘要：

With the depletion of coal in the world,coal quality fluctuates and deviates greatly from the designed coal in many large scale coal-fired power plants.This increases the coal consumption while reduces the boiler combustion efficiency and stability.Thus,it is very important to conduct real-time measurement to the quality of the coal for optimizing the operation.The calorific value analysis is a significant part of the coal quality analysis,and regular proximate analysis method cant meet realtime control requirements.In this paper,an artificial neural network (ANN) model using real plant data for prediction of net calorific value of coal in a China power plant is reported.A 3-layer BP neural network has been adopted.The input parameters selection was optimized with a compromise between smaller number of parameters and higher level of accuracy through sensitivity analysis.The activation function selection was also discussed in details.The results indicate that when the pureline was selected as trie activation function for hidden layer and logsig was selected as the activation function for output layer,the prediction is most accurate.The results have shown good potential for predicting the net calorific value of coal using the real time data.This information will enhance the performance of the combustion control system for power utilities.

关键词： Artificial neural network Real power plant data Net calorific value

作者: Haiyu Liu Houzhang Tan Xiaohe Xiong Linzhi Yao Yanqing Niu Yang Liu Tongmo Xu

作者单位: School of Energy and Power Engineering,Xian Jiaotong University,Xian 710049,China School of Energy and Power Engineering,Xian Jiaotong University,Xian 710049,China CFD Centre/SPEME Taiyuan University of Technology,Taiyuan 030024,China CFD Centre/SPEME,University of Leeds,L.S2 JT,UK

会议类型: 国际会议

会议名称: The 7th International Symposium on Coal Combustion(第七届国际煤燃烧学术会议)

会议地点: 哈尔滨

会议语种:英文

页码: 480-484

在线出版日期: 2011-07-19（万方平台首次上网日期，不代表论文的发表时间）