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A HYBRID GA FOR NOX EMISSION MODELLING IN POWER GENERATION PLANTS
Jian-xun Peng, Steve Thompson, Kang Li
School of Mechanical and Manufacturing Engineering
Queen’s University of Belfast, Ashby Building, Stranmillis, Rd.
Belfast BT9 5AH, U.K.
Email: j.peng@qub.ac.uk, steve.thompson@qub.ac.uk, k.li@qub.ac.uk
This paper reviews a grey-box (GB) modelling method that uses genetic algorithms (GA). The GA-GB modelling framework is used for finding NOx emission from coal-fired power generation boilers using operator controlled variables. The main contribution of this paper is the inclusion of a distributed elitist scheme within the GA. This enables a local gradient-based optimisation routine to be incorporated within the GA. The new hybrid GA-GB modelling procedure is shown to be able to produce NOx models having similar performance to those of the original method but requires less computational effort.
Keywords: Power station control, Modelling, Genetic algorithms, Gradient methods, Identification
Session slot T-Fr-M21: Posters of Mining, Power Systems and Fault Detection/Area code 7c : Power Plants and Power Systems
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