NDLI: Use of differential evolution in low NOx combustion optimization of a coal-fired boiler

Content Provider	IEEE Xplore Digital Library
Author	Ligang Zheng Yugui Zhang Shuijun Yu Minggao Yu Junbang Chen
Copyright Year	2010
Description	Author affiliation: School of Safety Science and Engineering and Key Lab of Gas Geology and Gas Control, Henan Polytechnic University, Jiaozuo 454000, China (Ligang Zheng; Yugui Zhang; Shuijun Yu; Minggao Yu) \|\| China United Engineering Corporation, Hangzhou 310022, China (Junbang Chen)
Abstract	The present work focuses on low NOx emissions combustion modification of a 300MW dual-furnaces coal-fired utility boiler through a combination of support vector regression (SVR) and a novel and modern differential evolution optimization technique (DE). SVR, used as a more versatile type of regression tool, was employed to build a complex model between NOx emissions and operating conditions by using available experimental results in a case boiler. The trained SVR model performed well in predicting the NOx emissions with an average relative error of less than 1.14% compared with the experimental results in the case boiler. The optimal ten inputs (namely operating conditions to be optimized by operators of the boiler) of NOx emissions characteristics model were regulated by DE so that low NOx emissions were achieved, given that the boiler load is determined. Two cases were optimized in this work to check the possibility of reducing NOx emissions by DE under high and low boiler load. The time response of DE was typical of 20 sec, at the same time with the better quality of optimized results. Remarkable good results were obtained when DE was used to optimize NOx emissions of this boiler, supporting its applicability for the development of an advanced on-line and real-time low NOx emissions combustion optimization software package in modern power plants.
Starting Page	4395
Ending Page	4399
File Size	316898
Page Count	5
File Format	PDF
ISBN	9781424459582
e-ISBN	9781424459612
DOI	10.1109/ICNC.2010.5583524
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-08-10
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines support vector regression differential evolution combustion optimization boiler Chromium Predictive models Boilers Combustion Optimization Load modeling
Content Type	Text
Resource Type	Article

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