The Optimization Of Soot Blowing On The Heating Surface Of Coal-fired Power Station Boilers

With the deepening of energy saving and emission reduction,China’s requirements for energy consumption and pollutant emissions are also getting higher and higher.Coal-fired power generation is the main source of power supply in China,and the pressure of energy saving and emission reduction is also huge.The combustion process of coal-fired boilers will produce ash pollution,which will eventually adhere to the heating surface in the form of ash deposit or slagging,which will reduce the heat transfer efficiency of boilers and increase the resistance of exhaust and flue gas pipelines.If this is not controlled,it will lead to problems such as reducing furnace efficiency and increasing coal consumption,which will affect the economic operation of boilers.The usual way to solve this problem is to soot the heating surface,but not timely soot blowing and excessive soot blowing will cause unnecessary waste of energy.In order to solve this problem,this study establishes a soot-blowing optimization model based on data statistics,incremental distribution and residual time,and proposes corresponding soot-blowing optimization strategies to improve the energy efficiency of coal-fired power plants.The research work in this paper is mainly divided into the following aspects:(1)Firstly,the problem of on-line monitoring of key parameters of boiler heating surface is studied.The pollution rate(FF)is used to characterize the influence of clean state of heating surface on heat transfer of boiler heating surface.An on-line monitoring model of clean state of boiler economizer heating surface is established,which realizes on-line real-time acquisition of boiler thermal efficiency and lays a foundation for subsequent optimization work.(2)In view of the unreasonable way of soot blowing on the heating surface of the boiler at present,the boiler efficiency and steam loss caused by soot blowing are weighed.Based on the economic benefit of the boiler,an optimization model of soot blowing on the heating surface based on data statistics is established.From the statistical point of view,the data distribution of multiple data sets at the same measuring point is analyzed.Combining with the optimization model of heating surface,the optimum soot blowing period of boiler economizer is obtained.(3)Improve the soot blowing model and data analysis method on the basis of the foregoing.The incremental distribution of the same measuring point at different time is obtained by analyzing the pollution rate of multiple groups under the same working condition,and the expected value is obtained according to the distribution curve.The heating state of the heating surface in the future is predicted by the known initial cleaning state.By analyzing the trend of pollution rate and combining with soot blowing optimization model,a soot blowing optimization strategy based on incremental distribution is proposed.(4)The problem of residual time prediction and optimal decision-making of preventive soot blowing is further studied,and an optimization strategy of soot blowing for Coal-fired Utility Boilers Based on residual time prediction is proposed.An optimization model is established with the prediction interval,the soot blowing threshold as the optimization variables and the minimum average soot blowing cost as the objective.The optimal monitoring period and the soot blowing threshold of the boiler are obtained,and the average cost rate of the long-term operation of the boiler is lowest.