基于智能方法的静电除尘器供电电压优化控制

Optimized Control of the Working Voltage for Electrostatic Precipitator Based on Intellective Method

针对火电厂静电除尘器的粉尘排放浓度以及消耗电能等问题,提出一种提高和改善静电除尘器性能的整体优化控制方法。用最小二乘法辩识除尘器电晕功率模型,以神经网络模型来映射除尘器出口度,在此基础上,采用遗传算法GA实现了对电除尘器供电工作电压优化控制。结果证明,本文提出的优化控制方法,在保证了除尘效率的同时,又兼顾了电除尘器的节能问题。

For the problems of dust discharging concentration and power consumption in power plants, a new optimized control method was presented to improve the energy consuming pcrformance of the electrostatic precipitator, The corona power model was identified by least - square method and the outlet dust concentration was represented by the neural network model. Based on these models, the working voltage optimization was realized by CA. Simulation results show that this control method can ensure dedusting and energy - saving for the electrostatic precipitator.