城市生活垃圾焚烧炉温控制的多目标优化设定方法

Multi-objective optimization setting method for temperature control of municipal solid waste incinerator

中文关键词  城市生活垃圾  炉温  多目标优化  海鸥优化算法  优化设定

英文关键词  municipal solid waste  furnace temperature  multi-objective optimization  seagull optimization algorithm  optimal setting

中文摘要

      为实现城市生活垃圾焚烧(MSWI)过程的炉温稳定并避免炉排温度过高的控制目标, 本文提出一种通过炉排温度和一次风温间接控制炉温的多目标优化设定方法. 通过融合分解与竞争策略, 将WS变换、双向学习、随机交叉、动态高斯变异引入到多目标海鸥优化算法(MOSOA)中, 得到一种改进的MOSOA(IMOSOA), 根据炉温的设定值、误差等信息对炉排温度和一次风温的设定值进行寻优. 实验结果表明IMOSOA的寻优能力显著增强, 在干扰影响下, 基于IMOSOA的多目标优化设定方法可实现MSWI过程炉温的控制目标, 能有效促进垃圾焚烧过程的平稳运行.

英文摘要

      To achieve the stability of the furnace temperature in the municipal solid waste incineration (MSWI) process and avoid excessively high grate temperature, a multi-objective optimization setting method is proposed in this paper, which indirectly controls the furnace temperature through the grate temperature and the primary air temperature. By introducing the weight shift (WS) transformation, bidirectional learning, random crossover and dynamic Gaussian mutation into themulti-objective seagull optimization algorithm (MOSOA), an improved MOSOA (IMOSOA) is obtained with integrating decomposition and competition strategies. The set value of grate temperature and the primary air temperature are optimized according to the set value of furnace temperature, the error and other information by IMOSOA. Experimental results show that the optimization capability of IMOSOA is significantly enhanced. Under the influence of disturbance, the furnace temperature control target of the MSWI process can be achieved through multi-objective optimization setting method based on the IMOSOA, and the smooth operation of the waste incineration process is also effectively promoted.