Dissertation > Environmental science, safety science > Processing and comprehensive utilization of waste > General issues > Exhaust gas processing and utilization > Smoke and dust

Predicting Model of Coal Fired Fly Ash Resistivity

Author LiXiaoYing
Tutor ZuoKePing
School Zhejiang University
Course Environmental Science
Keywords fly ash resistivity electrostatic precipitation model ash composition particles
CLC X701.2
Type Master's thesis
Year 2011
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China is world’s biggest producer and consumer of coal. The consumption of coal in China occupies over 70% of the total internal premary energy consumption. The main coal consumption way in China is coal-fired power. The particles discharged from coal-fired power station may cause atmospheric pollution and human health hazard. Electrostatic precipitator (ESP) is the primary particle collection apparatus used in coal-fired power station, however, most of the ESPs in China can not meet the emission standard, so the collection efficiency must be enhanced.Fly ash resistivity represents the electrical properties of ash. It is one of the critical parameters influencing the collecting efficency of ESP. The sulphur content in Chinese coal is usually very low, so the fly ash resistivity is rather high and back-corona occurs frequently, which decreases the collecting efficiency. To provide basis for ESP designing, This paper analyses the factors influencing the resistivity and builds a new resistivity model which is suitable to predict resistivity of Chinese fly ash in operating condition.This paper first evaluates available resistivity models with three typical ash samples. The comparison shows that those models hardly match each other when considering ash effects on the resistivity. For the ash sample from their own database, the predicting accuracy is very high, in the temperature range of 120-250℃, The deviation of calculated and experimental values is lower than 2.38%of experimental value, howower, for other ash samples, the deviation is over a magnitude.We analyses resistivity in term of ash composion based on a new built resistivity—ash properties database. The results show that only Li2O plus Na2O and Fe2O3 have obvious effects on the maximum resistivity. The order of sensitivity intensity is Li2O plus Na2O> Fe2O3. The relationship can be expressed by: lgρmax=-1.210lgAls-0.782lgAi+γ.Effects of gaseous water concentration and field strength are also experimentally investigated. The relationship between the maximum resistivity and gaseous water concentration can be expressed by:lgρmax=(0.131Alithium+sodium-0.142)W+C1. And the relationship between the maximum resistivity and field strength can be expressed by: lgρmax=-0.051E+C2. A new simplifying model is proposed for approximating the maximum ash resistivity in terms all the factors as: lgρmax=-1.210lgAlithium+sodium-782lgAlron+(0.132Alithium+sodium-0.141)W-0.051E+11.40685The accuracy of the new model is evaluated using 10 ash samples. The deviation is in the range of 0.15-13.34% of experimental value, the average value is 6.068%.

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