Author:
Yao Xuan,Zhang Man,Kong Hao,Lyu Junfu,Yang Hairui
Abstract
After the implementation of the ultra-low emissions regulation on the coal-fired power plants in China, the problem of the excessive ammonia-slipping from selective catalytic reduction (SCR) seems to be more severe. This paper analyzes the operating statistics of the coal-fired plants including 300 MW/600 MW/1000-MW units. Statistics data show that the phenomenon of the excessive ammonia-slipping is widespread. The average excessive rate is over 110%, while in the small units the value is even higher. A field test data of nine power plants showed that excessive ammonia-slipping at the outlet of SCR decreased following the flue-gas process. After most ammonia reduced by the dust collector and the wet flue-gas desulfurization (FGD), the ammonia emission at the stack was extremely low. At same time, a method based on probability distribution is proposed in this paper to describe the relationship between the NH3/NOX distribution deviation and the De–NOX efficiency/ammonia-slipping. This paper also did some original work to solve the ammonia-slipping problem. A real-time self-feedback ammonia injection technology using neural network algorithm to predict and moderate the ammonia distribution is proposed to decrease the NH3/NOX deviation and excessive ammonia-slipping. The technology is demonstrated in a 600-MW unit and works successfully. The excessive ammonia-slipping problem is well controlled after the implementation of the technology.
Subject
Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous)
Cited by
9 articles.
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