Analysis Of Carbon Quota Calculation Method And Predictive Model Of Carbon Dioxide Emissions From Coal-fired Power Plant

Fast development of economic globalization and increasing living quality contribute to growing energy consumption all over the world, as well as strengthened greenhouse effect. CO₂ is the greenhouse gas with the largest emission amount and much attention has been paid on its quota calculation. Large amount of CO₂ is emitted in electric power industry, whose carbon emissions are still evaluated by empirical formula calculation without comprehensive consideration of coal property, load rate and practical device characteristics. Also, different calculation methods of carbon emission quota affect the cost of carbon trading. The coal-fired plant is taken as study subject in this paper and the effect of different carbon emission quota calculation methods on quota amount is analyzed comparatively and the effect of coal property and operating parameters on CO₂ emission is studied. By applying training methods based on support vector machine, a prediction model of CO₂ emission in coal-fired power plant is established and the model is applied for the analysis on the influence relation of coal property and operating parameters on CO₂ emission.The trading mechanism of seven domestic carbon emission trading pilots is analyzed comparatively considering coverage, inclusion criteria, allocation method and transaction model, etc. The accounting method of quota amount is mainly analyzed. Taking one power plant as an example, calculation applying quota accounting method of different experimental cities is conducted and the practical quota amount is analyzed comparatively. Results show that only the carbon emission quota of this power plant in 2014 calculated through calculation methods applied in Tianjin and Chongqing is larger than the actual quota of this plant in 2014,while the quota calculated through other methods are smaller than that. The actual quota deviation rate of method in Shanghai is the largest, followed by Chongqing, Hubei Province, Beijing, Guangdong Province and Tianjin successively.Taking Wanglong power plant for example, 200 sets of sample were selected, including coal quality, load, air distribution and other parameters which affect carbon dioxide emissions. The influence of coal quality and the wind on the emissions of carbon dioxide is studied mainly. The study is focused on the volatile matter and calorific value of the coal, which have a greater impact on carbon dioxide emissions. It is studied that the effect of wind coal ratio on the carbon dioxide emissions, for two load segments of 20%-50% and 50%-100%. As well, the effect of the temperature of the first and secondary air on the carbon dioxide emissions is studied under the load 25%-35%、55%-65%、75%-85% and 85%-95%.Inappropriate data was rejected and 150 sets of samples were selected out of the remained 170 sets. The decision function is obtained by training calculation based on support vector machine. The relation model of coal property and operating parameters with CO₂ emission is established, finally realizing the prediction on CO₂ emission in coal-fired power plant. In addition, 20 sets of data were selected for contrast verification of fuzzy precision. Results indicate that the deviation of predicted value and actual value can be controlled within 10% by the model established in this paper.The prediction model is applied to power plants in Guangzhou Wanglong. The carbon dioxide emissions are predicted under three different common wind conditions and coal quality for the load of 50%, 70%, 90%, respectively. The difference between cost of carbon emissions under the different coal quality and wind conditions is analyzed.