Abstract
Non-linear methods have been utilised in modelling the processes on a flue-gas oxygen-content control system of a power plant. The ultimate objective is to reduce NOx and CO emissions by enhancing the control system. By investigating the flue-gas emission control strategy, the major factors affecting the flue-gas emissions have been determined. A simulator has been constructed, and it emulates a real process automation system and its physical processes. The process models of the simulator are: a flue-gas oxygen-content model, a secondary air flow model, a primary air flow model and a fuel feeding screw model (a fuel flow). The effort has been focused on two plant models: the flue-gas oxygen-content model and the secondary air flow model. Combustion is a non-linear, timevariant, multi-variable process with a variable delay. The secondary air model is a non-linear, timeinvariant (in principle), multi-variable system. Both phenomenological modelling (mass and energy calculations) and black-box modelling (neural networks) have been utilised in the Wiener/Hammerstein structures. It is possible to use a priori knowledge in model modifying, and therefore the model of flue-gas oxygen-content can be tuned on site. The simulator with precalculated parameters was tested in a full-scale power plant and a pilot-scale circulating fluidised bed boiler. The results in the power plant were remarkable since NOx emissions decreased significantly without increasing CO emissions.
| Identifer | oai:union.ndltd.org:oulo.fi/oai:oulu.fi:isbn951-42-8241-8 |
| Date | 25 October 2006 |
| Creators | Leppäkoski, K. (Kimmo) |
| Publisher | University of Oulu |
| Source Sets | University of Oulu |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/doctoralThesis, info:eu-repo/semantics/publishedVersion |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess, © University of Oulu, 2006 |
| Relation | info:eu-repo/semantics/altIdentifier/pissn/0355-3213, info:eu-repo/semantics/altIdentifier/eissn/1796-2226 |
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