基于改进简化粒子群算法的活性污泥过程建模
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摘要
提出一种改进简化粒子群算法,并应用于某氧化沟工艺的活性污泥1号模型(activated sludge model No.1,ASM1)与活性污泥3号模型(activated sludge model No.3,ASM3),对模型进行参数优化,提高模型准确性,并比较模型校正后的准确度。改进简化粒子群算法在简化粒子群算法基础上,对决策变量进行单维度搜索,提高算法的全局搜索能力。利用典型测试函数与基本粒子群算法、简化粒子群算法以及帝国竞争算法进行对比,其结果表明,该算法在函数优化上具有较明显优势。将改进简化粒子群算法应用到ASM1和ASM3模型中,其结果表明,该算法在模型参数优化上具有良好效果,模型对比上得到较清晰结果。
An improved simplified particle swarm optimization algorithm(ISPSO)was applied to improve the accuracy,optimize the parameters and analyze the feasibility of activated sludge model No.1(ASM1)and activated sludge model No.3(ASM3)for the Orbal process.Based on simplified particle swarm optimization algorithm(SPSO),single dimensional search was used to enhance the global searching ability.ISPSO algorithm was compared with imperial competition algorithm(ICA),particle swarm optimization algorithm(PSO),SPSO algorithm and ISPSO algorithm with 7 typical test functions.Results demonstrate that ISPSO has better performance.ASM1 and ASM3 model were applied to ISPSO algorithm.Application shows good results in model optimization and a distinct conclusion in model comparison is obtained.
An improved simplified particle swarm optimization algorithm(ISPSO)was applied to improve the accuracy,optimize the parameters and analyze the feasibility of activated sludge model No.1(ASM1)and activated sludge model No.3(ASM3)for the Orbal process.Based on simplified particle swarm optimization algorithm(SPSO),single dimensional search was used to enhance the global searching ability.ISPSO algorithm was compared with imperial competition algorithm(ICA),particle swarm optimization algorithm(PSO),SPSO algorithm and ISPSO algorithm with 7 typical test functions.Results demonstrate that ISPSO has better performance.ASM1 and ASM3 model were applied to ISPSO algorithm.Application shows good results in model optimization and a distinct conclusion in model comparison is obtained.
引文
[1]Yang T,Zhang L,Chadli M.Fuzzy modeling of activated sludge wastewater treatment processes and predictive control of dissolved oxygen[C]//IEEE International Symposium on Industrial Electronics.Taiwan:IEEE,2013:1-6.
[2]Lamia M,Tarek K M.Dynamic model prediction control for an activated sludge model based on a T-S multi-model[C]//Proceedings of the 3rd International Conference on Control,Engineering&Information Technology.Tlemcen:IEEE,2015:1-6.
[3]XU Yufeng.The investigation of pollutant removal and sludge reduction by activated sludge under low oxygen concentration[D].Chongqing:Chongqing University,2014(in Chinese).[徐宇峰.低氧活性污泥法除污及污泥减量研究[D].重庆:重庆大学,2014.]
[4]HUANG Tai’an,SHENG Jiagen,XU Hongyang,et al.Improved simplified particle swarm optimization[J].Computer Simulation,2013,30(2):327-330(in Chinese).[黄太安,生佳根,徐红洋,等.一种改进的简化粒子群算法[J].计算机仿真,2013,30(2):327-330.]
[5]Wu X,Xu K,Wang Z,et al.Optimized capacity configuration of an integrated power system of wind,photovoltaic and energy storage device based on improved particle swarm optimizer[C]//IEEE Conference on Energy Internet and Energy System Integration.Beijing:IEEE,2017:1-6.
[6]Fathy A,Rezk H.Parameter estimation of photovoltaic system using imperialist competitive algorithm[J].Renewable Energy,2017,111:307-320.
[7]Gao F,Nan J,Li S,et al.Modeling and simulation of a biological process for treating different COD:N ratio wastewater using an extended ASM1 model[J].Chemical Engineering Journal,2018,332:671-681.
[8]Man Z,Gong J,Yang C,et al.Simulation of the performance of aerobic granular sludge SBR using modified ASM3 model[J].Bioresour Technol,2013,127(1):473-481.
[9]Wu X,Yang Y,Wu G,et al.Simulation and optimization of a coking wastewater biological treatment process by activated sludge models(ASM)[J].Journal of Environmental Management,2016,165(2):235-242.
[10]Du X,Wang J,Jegatheesan V,et al.Parameter estimation of activated sludge process based on an improved cuckoo search algorithm[J].Bioresource Technology,2017,249:447-456.
[11]Wang R R,Cao L L,Liu M D.Activated sludge model parameters calibration based on multi-objective PSO[C]//International Conference on Environmental Engineering and Computer Application,2015:133-138.
[12]Zhou X,Han Y,Guo X.Enhanced total nitrogen removal performance in a modified Orbal oxidation ditch system with internal nitrate recycle[J].Chemical Engineering Journal,2013,228(7):124-131.
[13]CHEN Wenliang,LV Xiwu,YAO Chonghua.Sensitivity analysis of ASM1parameters under different influent conditions[J].Environmental Pollution&Control,2013,35(8):59-63(in Chinese).[陈文亮,吕锡武,姚重华.不同进水条件下ASM1模型参数的灵敏度分析[J].环境污染与防治,2013,35(8):59-63.]
[14]WANG Ruirong.Activated sludge model parameters calibration based on multi-objective particle swarm optimization[D].Shanghai:East China University of Science and Technology,2014(in Chinese).[王瑞荣.基于多目标粒子群优化的活性污泥模型参数校正[D].上海:华东理工大学,2014.]
[2]Lamia M,Tarek K M.Dynamic model prediction control for an activated sludge model based on a T-S multi-model[C]//Proceedings of the 3rd International Conference on Control,Engineering&Information Technology.Tlemcen:IEEE,2015:1-6.
[3]XU Yufeng.The investigation of pollutant removal and sludge reduction by activated sludge under low oxygen concentration[D].Chongqing:Chongqing University,2014(in Chinese).[徐宇峰.低氧活性污泥法除污及污泥减量研究[D].重庆:重庆大学,2014.]
[4]HUANG Tai’an,SHENG Jiagen,XU Hongyang,et al.Improved simplified particle swarm optimization[J].Computer Simulation,2013,30(2):327-330(in Chinese).[黄太安,生佳根,徐红洋,等.一种改进的简化粒子群算法[J].计算机仿真,2013,30(2):327-330.]
[5]Wu X,Xu K,Wang Z,et al.Optimized capacity configuration of an integrated power system of wind,photovoltaic and energy storage device based on improved particle swarm optimizer[C]//IEEE Conference on Energy Internet and Energy System Integration.Beijing:IEEE,2017:1-6.
[6]Fathy A,Rezk H.Parameter estimation of photovoltaic system using imperialist competitive algorithm[J].Renewable Energy,2017,111:307-320.
[7]Gao F,Nan J,Li S,et al.Modeling and simulation of a biological process for treating different COD:N ratio wastewater using an extended ASM1 model[J].Chemical Engineering Journal,2018,332:671-681.
[8]Man Z,Gong J,Yang C,et al.Simulation of the performance of aerobic granular sludge SBR using modified ASM3 model[J].Bioresour Technol,2013,127(1):473-481.
[9]Wu X,Yang Y,Wu G,et al.Simulation and optimization of a coking wastewater biological treatment process by activated sludge models(ASM)[J].Journal of Environmental Management,2016,165(2):235-242.
[10]Du X,Wang J,Jegatheesan V,et al.Parameter estimation of activated sludge process based on an improved cuckoo search algorithm[J].Bioresource Technology,2017,249:447-456.
[11]Wang R R,Cao L L,Liu M D.Activated sludge model parameters calibration based on multi-objective PSO[C]//International Conference on Environmental Engineering and Computer Application,2015:133-138.
[12]Zhou X,Han Y,Guo X.Enhanced total nitrogen removal performance in a modified Orbal oxidation ditch system with internal nitrate recycle[J].Chemical Engineering Journal,2013,228(7):124-131.
[13]CHEN Wenliang,LV Xiwu,YAO Chonghua.Sensitivity analysis of ASM1parameters under different influent conditions[J].Environmental Pollution&Control,2013,35(8):59-63(in Chinese).[陈文亮,吕锡武,姚重华.不同进水条件下ASM1模型参数的灵敏度分析[J].环境污染与防治,2013,35(8):59-63.]
[14]WANG Ruirong.Activated sludge model parameters calibration based on multi-objective particle swarm optimization[D].Shanghai:East China University of Science and Technology,2014(in Chinese).[王瑞荣.基于多目标粒子群优化的活性污泥模型参数校正[D].上海:华东理工大学,2014.]
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