Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6475496 | Fuel | 2017 | 11 Pages |
â¢Coal co-firing of coal mine residues was successfully performed in high percentages.â¢Thermal model for fouling thermal resistance estimation was developed and validated.â¢Deposit emissivity and flue gas temperature are the most influential parameters.â¢Cynara and coal mine residues significantly increase the fouling thermal resistance.â¢Poplar co-firing produces very similar fouling level to coal combustion.
Co-firing biomass or waste fuels with coal in conventional thermal plants is a promising way to reduce environmental impact of human activities with an acceptable economic investment. One of the main issues to be addressed is the worsening in ash fouling and the reduction of heat transfer rate. In the present paper, the deposits thermal resistance during direct combustion of different blends of coal and various native fuels is investigated by using a deposition probe, kept at 550 °C in order to emulate the conditions of superheaters of conventional power units. Two energy crops (Cynara cardunculus L. and Populus spp.), a forest residue (Pinus pinaster) and a waste coal (coal mine waste residues) were successfully tested in a semi-industrial scale pilot plant.A thermal model of the probe is presented to estimate heat transfer rate and thermal resistance of ash deposits. After the validation with experimental data, a sensitivity analysis allows to identify the deposit surface emissivity and the flue gas temperature as the most influential parameters. The heat uptake in air flow decreases with time for all the experimental tests in spite of the increase in flue gas and walls temperatures. Except for poplar blends, under similar operation conditions, a rise in the substitution percentage means faster decreasing rates in heat transfer and higher thermal resistance due to the ash deposits, especially for cynara and coal mine waste residues.The present work demonstrates the usefulness of thermal models to estimate the thermal resistance of ash deposits without the need of sophisticated instrumentation. Dedicated thermal models, similar to the developed one, could serve to design smart cleaning sequences to improve efficiency in power generation processes.