基于改进多目标布谷鸟算法的污水处理优化控制方法

针对如何确定污水处理优化控制中关键变量的最优设定值,以满足出水水质达标的同时尽可能降低能耗的问题,提出一种基于改进多目标布谷鸟算法的污水处理多目标优化控制方法.首先,通过对污水处理过程的分析,建立基于神经网络的污水处理能耗和出水水质模型;其次,利用改进多目标布谷鸟算法同时对污水处理能耗和出水水质模型进行优化,得到溶解氧和硝态氮浓度的优化设定值;最后,利用PID控制器对关键变量的最优设定值进行跟踪控制,实现污水处理过程的多目标优化控制.仿真实验结果表明,与其他几种方法相比,所提出的方法在保证出水水质参数达标的前提下,更好地降低了污水处理过程的能耗,实现节能降耗和保护环境的目的.

Optimizing control method for sewage treatment based on improved multi-objective cuckoo algorithm

Aimed at the problems such as how to determine the optimal setting value of key variables in the process of optimizing control of wastewater treatment process (WWTP) to achieve the standard of effluent water quality and at the same time toreduce the energy consumption (EC) as much as possible, a multi-objective optimizing control method is proposed based on improved multi-objective cuckoo search algorithm (IMOCS). First, theEC and EQ models are presented based on neural network and analysis of wastewater treatment process. Then, both the EC and EQ models are simultaneously optimized by means of improved multi-objective cuckoo search algorithm and the optimal setting values of concentration of dissolved oxygen(DO) and nitrate-level nitrogen are obtained. Finally, the PID controller is chosen to conduct the tracing control of the optimal setting value, so that the multi-objective optimizing control of WWTP is achieved. Based on the international benchmark simulation platform No.1, and compared with other methods, it is shown that the proposed method can reduce EQ better in the process of sewage treatment and protect the environment, going on the premise of assuring the achievement of standard of the parameters of effluent water quality.