A carbon oxidation factor regression model of coal-fired power plants in China. (20th January 2017) - Wu, Handong; Han, Wei; Wang, Dandan; Gao, Lin
Abstract: The carbon oxidation factor affects the accurate measurement of CO2 emissions from coal power plants greatly. In this study, a more precise carbon oxidation factor estimation model for coal-fired power plants is proposed based on 240 sets of operating data that were sampled from the main representative power plants in China. An experimental study based on a 300 MW subcritical power plant was carried out to prove the feasibility of the model from both the qualitative and quantitative perspectives. According to the qualitative analysis, the unit capacity, unit load and coal quality are the principal elements that affect predicted results. Specifically, the estimated value increases linearly with unit capacity, and shows better performance under lower unit loads, especially when inferior coal is burned. From the quantitative analysis, the predicted results from the model show a better correspondence to the actual carbon oxidation factor than do the international defaults. The relative errors between the modeling value and the actual value are less than 2% for the vast majority of conditions, whereas the error of the international defaults can reach 7%. In 2013, for example, the error causes an overestimation of approximately 86.4–302.3 million tonnes for CO2 emissions for the coal fired power generation sector. Highlights: A COF estimation model of CFPP in China is proposed. Unit capacity, unit load and coal quality are the principal elements affecting COF. An experimental study is carried out to validate this model. The prediction results could accord better with reality than IPCC defaults.