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Other Power and Storage Technologies (Electric power conversion)
Fossil Fuels: Oil Gas and Coal (Coal, Coal combustion)
Energy Resources Research Unit
University of Leeds
Project Contact, Babcock International Group plc
Project Contact, Scottish Power Ltd
Project Contact, E.ON UK (formerly PowerGen)
Project Contact, Eastern Generation Ltd
Project Contact, ABB Limited
Project Contact, Alstom Power Ltd
Project Contact, University of Nottingham
With the use of combustion modification-based techniques for NOx reduction in pulverised coal-fired plant, the carbon-in-ash has increased significantly in almost all cases, adversely affecting combustion efficiency and hence generation efficiency. An unacceptable increase in carbon-in-ash level has also affected the marketability of fly ash for use in making building material, thus creating a disposal problem. In addition, the efficient operation of electrostatic precipitators c >an be compromised by the high carbon content of the dust. Carbon levels are likely to increase further if future legislation imposes increasingly stringent NOx targets.
With the issue gaining importance both in the UK and overseas, the aim of the advanced coal combustion modelling project is to develop and validate an improved combustion model for predicting the combustion efficiency in pf fired utility boilers. The model techniques will be able to:
- predict carbo >n burnout in new boiler and firing system designs
- identify the impact of different coals on existing boiler and firing system designs
A number of key plant parameters and processes affect the carbon-in-ash including fuel grindability, reactivity, mill performance, classifier performance and fuel supply (both around the furnace and within flames). A significant amount of development work is required to understand the interaction of these processes and their impact on unburned carbon in full-scale industrial plant. More accurate ways to predict char burnout and process parameters will be identified and incorporated in the m >odel. The feasibility of using these more precise computer sub-models for the development of the predictive techniquewill be investigated.
There is a need, for overseas plant in particular, to provide rapid but accurate predictions of combustion efficiency over a wide range of coals and plant types. This will enable operators to respond to opportunities for purchasing coal for plant supply within the short timescale (1-3 days) necessary to exploit such opportunities.
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