Research On The Energy-saving Optimization Strategy Of Wastewater Treatment Process Based On Kinetic-molecular Theory Optimization Algorithm

With the government's emphasis on environmental protection and emission reduction,the energy-saving optimization of wastewater treatment is becoming more and more important.Researching the energy-saving optimization strategy of wastewater treatment,it can reduce the operating energy consumption of sewage treatment under the condition of meeting the effluent quality requirement.It has important practical significance for sewage treatment plant to optimize the control strategy,reducing the costs and improving the efficiency of wastewater treatment.Based on the bechmark simulated model NO.1(BSM1),in order to reduce the energy consumption of sewage treatment,the dynamic optimization of the setting values of dissolved oxygen concentration and nitrate nitrogen concentration which are two important factors for the sewage treatment process are carried out.Firstly,the basic process of sewage treatment and activated sludge wastewater treatment process are introduced.The activated sludge benchmark simulation BSM1 platform is built by MATLAB.The accuracy and effectiveness of the constructed platform are verified,which provide basis for subsequent research.Secondly,based on the BSM1 platform and the effluent water quality standard,the optimization model of sewage treatment is established by using the energy consumption and penalty items of sewage treatment.According to the change of the inflow water flow,the optimization period of “day” is selected,and the improved optimization model is solved by the improved memory kinetic molecular theory optimization algorithm.The PI controller's set value of BSM1 are obtained,which realize the dynamic optimization of the set values and reduce the energy consumption of sewage treatment.In the improved algorithm,the algorithm mutation rate is redesigned,and the algorithm's population diversity is increased.At the same time,the guidance phase is added,so that the algorithm's optimization path is increased to prevent falling into local optimum.The simulation is carried out in three different weather conditions respectively.Compared with the traditional optimization strategy,the optimization strategy of the dissertation is more effective in reducing the energy consumption under the condition of meeting the effluent quality requirement.Finally,in order to improve the optimization strategy,the dissertation proposes an adaptive time-division optimization strategy for wastewater treatment process,which divides the time period of wastewater treatment process.The dependency criterion of the traditional ordered clustering method is changed by introducing the autocorrelation coefficient.Using the improved clustering of ordinal samples method,the influent flow and the influent components of the sewage treatment are clustered to obtain the corresponding segmentation points.Then the improved memory kinetic molecular theory optimization algorithm is used to optimize and find the optimal setting value of the PI controller of dissolved oxygen and nitrate nitrogen concentration for the corresponding time period.Compared with the traditional optimization strategy and equal time optimization strategy,the energy consumption of sewage treatment is further reduced and the optimization strategy is more perfect.