污水处理过程多变量优化控制方法研究

Research on Multivariate Optimal Control Method for Wastewater Treatment Process

为了解决污水处理过程的优化控制问题,提高出水水质达标率和降低能耗,提出了一种污水处理多变量优化控制方法。首先,通过分析污水处理过程参数与可控变量溶解氧与硝态氮的关系,建立能耗和出水水质模型;其次,提出一种动态惯性权重的多目标粒子群优化算法,该算法平衡了寻优过程中的局部搜索和全局搜索能力,同时提高了算法的收敛速度,获得最优的溶解氧和硝态氮的优化设定值;然后,基于多变量比例积分微分(PID)控制器实现最优设定值的跟踪控制;最后,将所提出的方法应用于基准仿真模型1(BSM1)。仿真结果表明,该方法可以达到准确优化控制,能够在保证出水水质达标的情况下,降低运行能耗。

In order to solve the optimal control problem of the wastewater treatment process(WWTP),improve effluent water quality to meet the standard rate and reduce energy consumption,a multivariate optimal control method for WWTP is proposed in this paper.First,by analyzing the relationship between the operation parameters and the controllable variables of dissolved oxygen and nitrate nitrogen,energy consumption and energy quality models are established using the radial basis function(RBF)neural network.Next,a multi-objective particle swarm optimization algorithm based on dynamic inertia weight is designed to balance the global exploration ability and the local exploitation ability of the optimization process and improve the convergence speed,which can obtain the optimal set-points of the dissolved oxygen and nitrate nitrogen.Then,a multivariate proportional-integral-differential(PID)controller is used to trace and control the optimal set-points.Finally,the proposed method is applied to the benchmark simulation model(BSM1),and the simulation results show that the proposed method can achieve accurate optimization control,and can reduce the operation energy consumption while ensuring the effluent water quality to meet the standard.