Coal Combustion Prediction Analysis Tool for Ultra Supercritical Thermal Power Plant

Many developing countries are opting to rely on coal-fired power mainly due to the abundance of the resource and its economic viability, since the capital needed to build a new coal-fired power plant is not as large as a nuclear power plant. Compared to nuclear power, coal-fired power does not bear the risk of major catastrophe and therefore it will be relevant in the power industry for many years to come. However, the major drawback of coal-fired power plant is the fact that it is not a clean energy prospect and it is considered one of the main contributors to the world’s greenhouse gases. Coal combustion is usually associated with the emission of greenhouse gases such as CO, CO2, NOx, and SO2. One of the main objectives of coal combustion research is to develop techniques that will help power plant operators to utilize coal cleanly and efficiently by adopting coal blending practices. Currently, emission mitigation and boiler cleanliness issues through coal blending process are focusing more on laboratory scale tests and not utilizing actual plant data and behaviour. This study evaluates the effectiveness of the implementation of Coal Combustion Prediction Analysis Tool (CPAT) as a tool to facilitate power plant operator in predicting the impact of individual or blended coal quality. It will provide early predictions on boiler combustion performance related to the coal quality and it will assist the power plant operators preparing for boiler process control optimization. This study will also discuss slagging and fouling factor of different coal type, which are used in one coal-fired power plant in South East Asia.