Forecast For Desulphurization Efficiency Of The CFB-FGD Process Based On Gray Theory

The technology of circulated fluidized bed for flue gas desulfurization (CFB-FGD) has low investment cost, high desulfurization efficiency, reliable operating condition, convenient maintenance and other advantages. Because of the CFB-FGD is a nonlinear, multi-variable and complicate system, its mechanism has not been completely mastered even now. The mathematics model doesn’t satisfy the actual need, so this thesis emphasizes on the modeling based on Gray Theory to solve above problems.Firstly, the process of the CFB-FGD is studied, and the factors which affect desulfurization efficiency are analyzed. Then, according to the method of gray relational analysis, the most important factors affecting the desulfurization efficiency are determined. It’s a scientific method to choose the input variables for forecasting model.Gray forecasting model can strengthen the system’s regularity and weaken the randomness. This method uses less data, forecast rapidly. So, we set up the gray forecasting model of the CFB-FGD system. The simulation result indicates that this model can forecast the development trend of desulfurization efficiency correctly, confirmed its applicability for CFB-FGD system. However, the model is lack of response to fluctuations in the data.In order to improve the forecast accuracy when data fluctuate, we introduce the gray-Markov model. At first, this method correctly forecasts the development trend of the data based on gray model. Then, it uses Markov method to modify the forecasting curve in order to improve its handling on the data fluctuations. The simulation result indicates that the gray-Markov model can forecast the fluctuations in the development of desulfurization efficiency. Compared to the gray model, it has higher forecasting accuracy.