T-S模糊模型的FGD系统pH值建模研究

Research on the pH Value Modeling of FGD System Based on T-S Fuzzy Model

目前,湿法石灰石-石膏烟气脱硫系统(即FGD系统)在火电厂脱硫系统中占绝大比例。FGD系统采用化学方法除掉烟气中的二氧化硫的方式,其中pH值是一个重要的参数,关系到化学反应的指示值。对此,应用T-S模糊神经网络模型以吸收塔pH值为对象进行数学建模,并且针对广东省能源集团有限公司珠海发电厂装机容量700WM的1#机组脱硫吸收塔pH值实时数据信号进行仿真处理。通过对该模型参数的预测学习以及与实际输出的对比,得到符合条件的仿真模型。模型预测结果能够反映机组真实情况,有进一步研究的价值。

At present, wet limestone-gypsum flue gas desulfurization system (FGD system) accounts for most of the desulfurization systems in thermal power plants. FGD system uses chemical method to remove sulfur dioxide from flue gas. Among them, pH is an important parameter, which is related to the indicator value of chemical reaction. In this regard, T-S fuzzy neural network model is applied to carry out mathematical modeling with the pH value of absorption tower as the object, and the real-time data signal of pH value of desulfurization absorption tower of unit 1 with the installed capacity of 700WM in Zhuhai Power Station of Guangdong Energy Group Company Limited. is simulated. Through the prediction learning of the model parameters and the comparison with the actual output, the simulation model conforming to the conditions is obtained. The model prediction results can reflect the real situation of the unit, which has the value of further research.