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根据污水处理系统的出水水质要求和节能目标,提出一种自适应优化调度策略,利用有序样本聚类法,根据入水量的变化情况进行自适应分段,再采用具有全局搜索能力的人工免疫算法确定控制器参数在每段的最优设定值,对污水系统进行动态优化控制.在活性污泥污水生化处理基准模型(benchmark simulation model No.1,BSM1)上进行仿真实验,结果证明了该自适应优化策略在污水处理及节能降耗方面的有效性.
According to the effluent quality requirements and energy-saving goals of sewage treatment system, an adaptive optimal scheduling strategy is proposed. Using ordered sample clustering method, adaptive segmentation is carried out according to changes of water inflow, and artificial immune system with global search capability The algorithm determines the optimal setting of controller parameters in each section and dynamically optimizes the control of the wastewater system.A simulation experiment on the benchmark simulation model No. 1 (BSM1) The effectiveness of the adaptive optimization strategy in wastewater treatment and energy saving.