基于人工免疫算法的污水处理系统节能优化

Energy-Saving Optimization of Wastewater Treatment System Based on Artificial Immune Algorithm

针对污水生化处理过程节能优化控制中,如何确定控制变量最优设定值的关键问题,提出一种基于人工免疫算法的污水生化处理系统节能优化控制策略.在前置反硝化的活性污泥污水生化处理基准模型BSM1仿真平台上,建立好氧池溶解氧浓度和缺氧池硝酸氮浓度的PI控制器,提出以出水水质指标为约束条件、以鼓风能耗和泵送能耗最小为优化目标的控制方案.采用具有全局优化能力的人工免疫算法,计算控制器的最优设定值,让控制器跟随优化设定值对氧传递系数和内回流量进行控制.用3种不同天气条件下的入水数据进行仿真实验,结果证明了该算法的有效性和鲁棒性.

In this paper,an energy-saving optimization control strategy of the biochemical process of wastewater is proposed to determine the optimal setting values of the control variables based on the artificial immune algorithm.First,two PI controllers respectively for the dissolved oxygen concentration of the aerobic tank and the nitrate nitrogen concentration of the anoxic tank are established on the benchmark simulation platform BSM1,which is used in describing the biochemical treatment process of the pre-denitrification activated sludge wastewater system.Next,a control scheme is presented to meet the effluent standards with minimal aeration and pumping energy consumption.Then,the optimal setting values of the PI controllers are evaluated by using the artificial immune algorithm of global optimization,and both the oxygen transfer coefficient and the internal flow rate are controlled by making the controller follow the setting values.Finally,simulation experiments are conducted by using the data of the influent flow rate under three kinds of weather conditions.The results show that the proposed algorithm is effective and robust.