Coal combustion prediction analysis tool for ultra supercritical thermal power plant

Abstract

Coal remains a major source of energy in the power generation industry in Malaysia. However, coal usage results in serious ecological and environmental problems due to greenhouse gas (GHG) emissions. One of the main objectives of the coal combustion research is to develop techniques that may help power plant operators (PPO) to utilize coal cleanly and efficiently by adopting good coal blending practices. Currently, the emission mitigation and boiler cleanliness measures through the coal blending process are focusing more on laboratory-scale tests and not utilizing the actual plant data and behavior. This study aims to evaluate the effectiveness of the developed Coal Combustion Prediction Analysis Tool (CPAT) as a method to facilitate the PPO in predicting the impact of the individual or blended coal quality. It provides early predictions on the boiler combustion performance related to the coal quality and assists the PPO in preparing for the boiler process control optimization. The CPAT combustion model is related to the calculations of the boiler performance and emissions while the CPAT boiler cleanliness model is to compute the slagging and fouling indices. The former model was tested and validated using the actual plant data with the results showing that all the models have mean percentage errors of less than 1%, implying that the combustion model is accurate. The latter model was verified with the actual boiler process parameters and actual site observation for the slagging behaviour. The results show that it gives accurate indications of the slagging and fouling tendencies and helps the PPO to strategize the coal combustion plan. The effect of the coal blending ratios to the power plant performance and SOx emission is evaluated and the result shows that the CPAT is able to recommend the optimum blending ratio for optimum plant performance and SOx emission. Thus, the proposed CPAT is able to provide accurate predictions for the SOx emission to ensure SOx emissions of below 500 mg/Nm3 and reduce the overall auxiliary power consumption by 12 MWh, thereby improving the overall power plant efficiency and establishing the optimal operational regime. The optimization of coal blending helps to improve the power plant efficiency as well as reduce the GHG emissions for a boiler in a coal fired power plant (CFPP) in Malaysia.