Publication: Modelling of single and blended coal combustion for tangential-fired boiler using computational fluid dynamics
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Date
2021-11
Authors
Noor Akma Watie Mohd Noor, Cik
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Abstract
Deteriorating trend of coal supply quality has broadened the supply-demand gap, forcing coal power plants to diversify and strategize its fuel supply. The new developments in fuel supply result in power plants having to utilize off-design coals, often with compromising quality, which may result in unplanned outages due to slagging and fouling. Blending “good” and “bad” coal is a strategy which addresses the cost and security of supply, at a desired quality, to ensure the power plant operates at its desired efficiency and with minimal operational upsets. Previous reported experience in coal blending has shown that the combustion behaviour of coal blends is complex and still not well understood. The main issue with firing blended coals in power plants is the non-additive behaviour between the component coals. In this research, the performance of blended coal was investigated using computational fluid dynamic (CFD). Combustion of different coal blends are applied to a full-scale, tangential-fired boiler of a power plant. CFD models were built based on the design of the actual furnace in operation and the results are validated using measurements from the boiler and operational data. The data used for validation were flame temperature, furnace exit gas temperature (FEGT) and rear pass gas temperature. These are the main parameters that affect boiler performance. The model was then used to predict the behaviour of other parameters such as flame temperature, FEGT, velocity magnitude in the furnace and O2 and CO mass fraction. Two coals and their blends were studied: Malinau and MHU, both are sub-bituminous coals from Indonesia. For validation purposes, two coals were simulated and analysed: (i) Adaro as a designed coal and (ii) Tabang blend, the first blended coal used in this boiler. Good agreement was found for the comparison between predictions and temperature distribution through in-furnace temperature profiling measurements, excluding the flame temperatures which are 9.5% higher than the predicted value. Based on the validated model, the blended coal combustion performance prediction for Malinau and MHU was performed in the ratio of 50:50 by weight. The prediction shows that firing blends of Malinau and MHU can improve the combustion performance up to 13% as compared to firing single Malinau and MHU separately by analysing their temperature profiles and CO levels. The results show that coal blending combustion can be an effective way for improving combustion behaviour of non-preferred coals.
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Computational Fluid Dynamic