An effective integrated control with intelligent optimization for wastewater treatment process

Abstract

Abstract Wastewater treatment process (WWTPs) is an enormous and complex system, it involves multi-disciplines and multi-fields, which is a greatly challenge for industrial Information Integration Engineering (IIIE). In this paper, an integrated control framework for WWTPs is proposed using intelligent optimization to solve the problem of excessive pollutant and high energy consumption. It realizes the effective integration of data model, intelligent decision making, dynamic optimization and control. Firstly, a self-organization soft sensing method is adopted. It can predict the concentrations of ammonia nitrogen and total nitrogen in advance. And the early warning is provided for decision making. Secondly, for the complex dynamic characteristics of multi-performance indexes intercoupling in WWTPs, the dynamic multi-objective immune optimization algorithm is designed. And an optimized set point with high quality in real time is to be obtained. In addition, according to different over standard states, the intelligent decision scheme of WWTPs is designed. It can achieve the effective cooperation of over standard suppression and energy saving. Finally, BSM1 simulation model is used to verify the method. The experimental results show that the integrated framework can achieve the whole process of WWTPs real-time standards and can effectively reduce energy consumption, so it has competitive practical application prospect for IIIE.