热力发电
熱力髮電
열력발전
THERMAL POWER GENERATION
2015年
4期
112-115
,共4页
燃煤锅炉%NOx排放%预测%神经网络%遗传算法
燃煤鍋爐%NOx排放%預測%神經網絡%遺傳算法
연매과로%NOx배방%예측%신경망락%유전산법
coal-fired boiler%NOx emission%neural network%genetic algorithm
应用Matlab 神经网络工具箱对某燃煤电站锅炉 NOx 排放特性进行神经网络建模.仿真结果表明,该模型具有良好的准确性和泛化能力,模型平均相对误差为1．37％,具有较高的准确性.基于该N Ox 排放预测模型,结合遗传算法对燃煤锅炉的 N Ox 排放进行优化,按照优化结果推荐的运行参数,在相同的运行负荷工况下,其 NOx 排放浓度由优化前的456．2 mg/m3降为323．9 mg/m3,下降幅度达到了29％,效果显著.
應用Matlab 神經網絡工具箱對某燃煤電站鍋爐 NOx 排放特性進行神經網絡建模.倣真結果錶明,該模型具有良好的準確性和汎化能力,模型平均相對誤差為1．37％,具有較高的準確性.基于該N Ox 排放預測模型,結閤遺傳算法對燃煤鍋爐的 N Ox 排放進行優化,按照優化結果推薦的運行參數,在相同的運行負荷工況下,其 NOx 排放濃度由優化前的456．2 mg/m3降為323．9 mg/m3,下降幅度達到瞭29％,效果顯著.
응용Matlab 신경망락공구상대모연매전참과로 NOx 배방특성진행신경망락건모.방진결과표명,해모형구유량호적준학성화범화능력,모형평균상대오차위1．37％,구유교고적준학성.기우해N Ox 배방예측모형,결합유전산법대연매과로적 N Ox 배방진행우화,안조우화결과추천적운행삼수,재상동적운행부하공황하,기 NOx 배방농도유우화전적456．2 mg/m3강위323．9 mg/m3,하강폭도체도료29％,효과현저.
The Matlab neural network toolbox was applied to establish the prediction model for NOx emis-sion in a coal-fired power plant boiler.The simulation results show that this forecast model has well accura-cy and generalization ability,its average relative error is 1 .3 7%,which means the high accuracy.On the ba-sis of this NOx emission prediction model,the NOx emission was optimized by genetic algorithm.According to the recommended operating parameters,after the optimization,the NOx emission decreased from 456.2 mg/m3 to 323.9 mg/m3 under the same operation load conditions,reduced by 29%,which is dramatic.
