Prediction method of ash deposition based on combustion state of solid fuel

Abstract

In solid-fuel fired boilers, ash deposition on heat-transfer surfaces can cause operational problems. It is important to predict ash-deposition properties based on the ash composition of the solid fuel in advance. However, general prediction methods do not always agree with actual ash deposition under conditions of actual combustion. In this study, we first developed a new sampling system that can collect ash particles during the combustion of mixed bituminous coal samples in a boiler; the composition of the sampling ash was evaluated, and the composition that affect ash-deposition properties were identified. Next, the ash composition of the coal samples was evaluated as a mineral with CCSEM. These results were summarized in order to identify which mineral particles were strongly related to ash-deposition properties, and a new prediction method for ash deposition based on the actual combustion state was investigated. The main conclusions were drawn as follows: (1) Iron was condensed in the early-stage ash deposition of the secondary superheater tube area, and there were differences in the amount of iron between the sampling-ash deposition and the ash in the bituminous coal. (2) The amount of iron in the ash deposition could be predicted with high accuracy by using the amount of included iron oxide, pyrite, Fe-Si (iron silicate), and pyrrhotite. (3) The method developed in this study can be applied to boilers with various solid fuels such as coal, woody biomass, and/or waste. This will contribute to improving the prediction accuracy of ash-deposition properties.

Keywords

• solid fuel fired boiler
• ash deposition
• ash sampling
• mineral
• computer-controlled scanning electron microscopy (ccsem)
• predictive indices