Research On The Prediction Of SO₂ Emission From Thermal Power Industry

Coal is China's main fuel and energy, in recent years China's energy consumption of coal in the proportion of remains at over 70%. Related research data show that SO₂ emissions generated by coal accounts for a country's total SO₂ emissions by more than 90%, the coal consumed by thermal power industry have been an important part of the coal consumption in China. SO₂ emissions produced in the running of Thermal power industry have an important part of China's total SO₂ emissions. SO₂ on atmospheric environment and human health, building, water etc all aspects of social life are harmful, so how to control the emission of SO₂ becomes an important problem. The forecast of SO₂ emissions in thermal power industry is infrastructure work in conduct atmospheric pollution control.Due to the obvious diversity in production process, the technical level, desulfurization equipment power production level of technology, production scale, the boiler emission characteristics and other characteristics, it is difficult to estimate the SO₂ emission. There are more limitations in many SO₂ emission estimation methods.So this paper discusses SO₂ emission electric current, thermal power control technology and the SO₂ control regulations, According to the specific conditions of the SO₂ emissions in thermal power, proposed that using grey forecasting model and the BP neural network model to predict SO₂ emissions in thermal power is appropriate. With establish of two models, combine forecast model on the basis of gray neural network. Finally, using the statistical data, forecasted the China's future thermal power industry SO₂ emissions, through the forecast shows that this model is a more reasonable and scientific method for thermal power industry SO₂ emissions.