广东电力2017，Vol.30Issue(11)：22-27,6.DOI:10.3969/j.issn.1007-290X.2017.011.005
带校正的锅炉燃烧预测模型应用
Application of Boiler Combustion Prediction Model with Correction Element
摘要
Abstract
The optimization method based on combustion optimization adjustment test is not able to keep long-acting effect.In order to satisfy imperious demands for high-effective and low-emission combustion of the boiler,a prediction model was es-tablished by virtue of test data of combustion optimization performance and using artificial neural network so as to realize soft measurement on carbon content in fly ash and exhaust gas temperature as well as rectify measuring values.Meanwhile, the corrective data was input into a hybrid model for boiler heating efficiency and NOx emission prediction.By continuously expanding training data dimension and using particle swarm optimization algorithm,real-time optimization for operating pa-rameters was realized.Practice has proved this method can use real-time data of the distributed control system to correctly acquire an optimal combustion adjustment scheme for the boiler and greatly reduce NOx emission on the basis of reasonable variation of boiler efficiency.关键词
电站锅炉/燃烧优化/神经网络/粒子群算法/预测模型/校正/DCSKey words
utility boiler/combustion optimization/neural network/particle swarm optimization/prediction model/correc-tion/DCS(distributed control system)分类
能源科技引用本文复制引用
汤伟,王古月,李金..带校正的锅炉燃烧预测模型应用[J].广东电力,2017,30(11):22-27,6.基金项目
陕西省重点科技创新团队计划项目(2014KCT-15) （2014KCT-15）
