EASM1模型的建立及在城市污水生物添加强化脱氮中的应用
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摘要
数值模拟是研究活性污泥法处理城市污水这一复杂生化过程并对其进行控制的有效手段。本研究在国际水协会ASM1模型的基础上进行了扩展，增加了除磷功能，建立了具有除碳、脱氮、除磷功能的EASM1模型（Extention of ActivatedSludge Model No.1），利用欧盟基准BSM1（Benchmark Simulation Model No1）和国际水协会ASM2对EASM1模型进行了验证。
将EASM1模型分别应用于序批式工艺（SBR）和连续流工艺（A~2/O）的生物添加强化生物脱氮系统。依据生物添加的特征，提出了投加比a（投加流量与进水流量的比值）的概念，用于表征生物添加过程。模拟结果表明，在短污泥龄（SRT=6d）的条件下，投加比越大，硝化速率越大，氨氮转化率越高，生物添加强化效果越好。无生物添加时（a=0），硝化能力较差，经50天运行，氨氮去除率仅为17%，出水氨氮为35mg/L；当a=0.01时，经50天运行，氨氮去除率可达到80%以上，出水氨氮可降至5mg/L；当a=0.2时，仅经15天后，出水氨氮降至1mg/L以下。将模拟结果与实验结果进行对比，两者结果基本一致，说明本研究提出的拓展模型和模拟方法可较好地模拟活性污泥生物添加强化生物脱氮系统。
针对现有活性污泥模型的参数识别方法，如人工试错法、遗传算法等，算法复杂、收敛速度慢、准确率低，提出采用支持向量机法的模型参数识别方法。结果表明，选取5个敏感性较强参数（Y_H，μ_H，b_H，μ_a， k_h），选用支持向量机法时，平均相对误差为1.335%，其中Y_H为0.015%， H为2.76%，b_H为1.43%，μ_a为0.58%， k_h为1.89%，整体相对误差波动较小；当选用遗传算法时，平均相对误差为1.622%，其中Y_H为0.03%，μ_H为4.47%，b_H为1.47%，μ_a为0.46%，k_h为1.68%，整体相对误差波动较大，说明支持向量机法的平均识别准确率优于遗传算法。
借鉴现代控制理论，用状态空间法描述污水水质与控制参数之间的变化关系，借助变步长加速法进行寻优，从而达到对活性污泥系统进行基于模型的控制。以A~2/O中试系统为研究对象，以出水氨氮和硝氮为指标，其主要控制参数为污泥龄、曝气量和污泥回流比。在传统控制策略下，仅能凭经验对控制参数的变化量进行选择和控制，且无法预知控制结果。当污泥龄为15天，溶解氧为1.65mg/L，内回流比为50%时，出水氨氮为13.53mg/L，硝氮24.12mg/L，氨氮超过国家城镇污水处理厂污染物排放标准中的一级B标准。以活性污泥模型为基础，利用状态空间法和变步长加速法，选取出水氨氮及硝氮为控制变量，以溶解氧及内回流比为操作变量（污泥龄不变条件下），经模拟计算，确定溶解氧增量为1.84，内回流比增量为0.75。以模拟计算的参数对实际系统进行控制，2天后，出水氨氮由13.53减少至4.1mg/L左右，出水硝氮由24.12减少至9.4mg/L左右。以上结果表明当进水水质不变时，该控制方法可以实现对控制参数的定量操作及对污水处理系统进行定量控制。通过监测进水水质的变化，应用该方法还可实现对处理系统的前控制。
Simulation is an effective method for studying and coltrolling complicatedbiological process. A modified model named EASM1(Extented Activated SludgeModel No.1) was developed based on ASM1(Activated Sludge Model No.1) by addedphosphorus removal function and verified by using BSM1model (BenchmarkSimulation Model No1) and ASM2(Activated Sludge Model No.2) model. Finally, themodel was applied in bio-augmention process to enhance nitrogen removal in municipalwastewater treatment.
Although ASM1was used widely in the world, it just can be applied to simulatecarbon and nitrogen removal. Based on ASM1model EASM1have been develpoed byadded phosphorous removal, and applied to simulate sequencing batch reactor (SBR)and continuous flow system (A~2/O). According to the characteristics of bio-augmention,this article put forward the specific dosing value (the ratio of dosing flow and influentflow, notes for “a” in percentage), and used specific dosing value to bio-augmentprocess. The simulation results show that under short sludge age conditions (SRT=6d),the more specific dosing flow added, the higher nitrification rate increased. When nobiological dosing flow added (a=0), the system of nitration ration is low, for simulationof50days, ammonia nitrogen removal rate is only17%, ammonia nitrogenconcentration of effluent is35mg/L, When a=0.01, for simulation of50days, removalrate of ammonia nitrogen can achieve80%above, and the ammonia nitrogen of effluentcan plunge to5mg/L; When a=0.2, only for15days of simulation later, the ammonia nitrogen of effluent almost drop down to zero. Compared the simulation results withexperiment results of SBR and A~2/O peocesses, it was concluded that the EASM1model and simulation method is suitable for apply to bio-augmention process toenhance nitrogen removal.
Some existing methods of parameter identification which was applicated inactivated sludge model, such as artificial testing method, genetic algorithm, and so on.These methods have some disadvantages, such as algorithm complex, low speedconvergence and low accuracy. It was proposed the support vector machine (SVM)method of pattern recognition applied to activated sludge process. The simulationresults show that, the selection of five sensitivity parameters（Y_H，μ_H，b_H， a， k_h）,was choosed to support vector machine (SVM), the average relative error is1.335%, therelative error of five parameters are0.015%,2.76%,1.43%,0.58%,1.89%, and selectedwith the genetic algorithm method, the average relative error is1.622%, which relativeerror of parameters are0.03%,4.47%,1.47%,0.46%,1.68%, these compared resultshow that the accuracy of support vector machines method is more than geneticalgorithm.
For the control based on activated sludge model, which was used the state spacemethod and step acceleration algorithm to describe relationship between the control andwater quality, this article was put forward a kind of control algorithm based on activesludge model. Through analysed the simulation result which have been done theexperiment of A~2/O system, the ammonia nitrogen and nitrate nitrogen were selected astarget variables of effluent flow, dissolved oxygen and inside return sludge ratio wereslected as the control variables. Under the traditional strategy of control, it was couldnot select and confirm the controlled parameter by experience.When sludge age (SRT)is for15days, dissolved oxygen is0.65mg/L, the inside return sludge ratio is50%,ammonia nitrogen of effluent is13.53mg/L, nitrate nitrogen of effluent is24.12mg/L.Ammonia nitrogen and nitrate nitrogen are more than the B level of urban sewagedischarge standard. Through simulation of calculation, dissolved oxygen increment is1.84, the inside return sludge ratio of increment is0.75. After simulating of control,ammonia nitrogen was below4.1mg/L, and nitrate nitrogen of effluent was below9.4mg/L by contorl. The results show that this method can operate the control parameter quantitatively as influent is constant in the wastewater treatment system. Thoughmonitored the quality of influent, this method also achieved forward control inwastewater treatment system.
将EASM1模型分别应用于序批式工艺（SBR）和连续流工艺（A~2/O）的生物添加强化生物脱氮系统。依据生物添加的特征，提出了投加比a（投加流量与进水流量的比值）的概念，用于表征生物添加过程。模拟结果表明，在短污泥龄（SRT=6d）的条件下，投加比越大，硝化速率越大，氨氮转化率越高，生物添加强化效果越好。无生物添加时（a=0），硝化能力较差，经50天运行，氨氮去除率仅为17%，出水氨氮为35mg/L；当a=0.01时，经50天运行，氨氮去除率可达到80%以上，出水氨氮可降至5mg/L；当a=0.2时，仅经15天后，出水氨氮降至1mg/L以下。将模拟结果与实验结果进行对比，两者结果基本一致，说明本研究提出的拓展模型和模拟方法可较好地模拟活性污泥生物添加强化生物脱氮系统。
针对现有活性污泥模型的参数识别方法，如人工试错法、遗传算法等，算法复杂、收敛速度慢、准确率低，提出采用支持向量机法的模型参数识别方法。结果表明，选取5个敏感性较强参数（Y_H，μ_H，b_H，μ_a， k_h），选用支持向量机法时，平均相对误差为1.335%，其中Y_H为0.015%， H为2.76%，b_H为1.43%，μ_a为0.58%， k_h为1.89%，整体相对误差波动较小；当选用遗传算法时，平均相对误差为1.622%，其中Y_H为0.03%，μ_H为4.47%，b_H为1.47%，μ_a为0.46%，k_h为1.68%，整体相对误差波动较大，说明支持向量机法的平均识别准确率优于遗传算法。
借鉴现代控制理论，用状态空间法描述污水水质与控制参数之间的变化关系，借助变步长加速法进行寻优，从而达到对活性污泥系统进行基于模型的控制。以A~2/O中试系统为研究对象，以出水氨氮和硝氮为指标，其主要控制参数为污泥龄、曝气量和污泥回流比。在传统控制策略下，仅能凭经验对控制参数的变化量进行选择和控制，且无法预知控制结果。当污泥龄为15天，溶解氧为1.65mg/L，内回流比为50%时，出水氨氮为13.53mg/L，硝氮24.12mg/L，氨氮超过国家城镇污水处理厂污染物排放标准中的一级B标准。以活性污泥模型为基础，利用状态空间法和变步长加速法，选取出水氨氮及硝氮为控制变量，以溶解氧及内回流比为操作变量（污泥龄不变条件下），经模拟计算，确定溶解氧增量为1.84，内回流比增量为0.75。以模拟计算的参数对实际系统进行控制，2天后，出水氨氮由13.53减少至4.1mg/L左右，出水硝氮由24.12减少至9.4mg/L左右。以上结果表明当进水水质不变时，该控制方法可以实现对控制参数的定量操作及对污水处理系统进行定量控制。通过监测进水水质的变化，应用该方法还可实现对处理系统的前控制。
Simulation is an effective method for studying and coltrolling complicatedbiological process. A modified model named EASM1(Extented Activated SludgeModel No.1) was developed based on ASM1(Activated Sludge Model No.1) by addedphosphorus removal function and verified by using BSM1model (BenchmarkSimulation Model No1) and ASM2(Activated Sludge Model No.2) model. Finally, themodel was applied in bio-augmention process to enhance nitrogen removal in municipalwastewater treatment.
Although ASM1was used widely in the world, it just can be applied to simulatecarbon and nitrogen removal. Based on ASM1model EASM1have been develpoed byadded phosphorous removal, and applied to simulate sequencing batch reactor (SBR)and continuous flow system (A~2/O). According to the characteristics of bio-augmention,this article put forward the specific dosing value (the ratio of dosing flow and influentflow, notes for “a” in percentage), and used specific dosing value to bio-augmentprocess. The simulation results show that under short sludge age conditions (SRT=6d),the more specific dosing flow added, the higher nitrification rate increased. When nobiological dosing flow added (a=0), the system of nitration ration is low, for simulationof50days, ammonia nitrogen removal rate is only17%, ammonia nitrogenconcentration of effluent is35mg/L, When a=0.01, for simulation of50days, removalrate of ammonia nitrogen can achieve80%above, and the ammonia nitrogen of effluentcan plunge to5mg/L; When a=0.2, only for15days of simulation later, the ammonia nitrogen of effluent almost drop down to zero. Compared the simulation results withexperiment results of SBR and A~2/O peocesses, it was concluded that the EASM1model and simulation method is suitable for apply to bio-augmention process toenhance nitrogen removal.
Some existing methods of parameter identification which was applicated inactivated sludge model, such as artificial testing method, genetic algorithm, and so on.These methods have some disadvantages, such as algorithm complex, low speedconvergence and low accuracy. It was proposed the support vector machine (SVM)method of pattern recognition applied to activated sludge process. The simulationresults show that, the selection of five sensitivity parameters（Y_H，μ_H，b_H， a， k_h）,was choosed to support vector machine (SVM), the average relative error is1.335%, therelative error of five parameters are0.015%,2.76%,1.43%,0.58%,1.89%, and selectedwith the genetic algorithm method, the average relative error is1.622%, which relativeerror of parameters are0.03%,4.47%,1.47%,0.46%,1.68%, these compared resultshow that the accuracy of support vector machines method is more than geneticalgorithm.
For the control based on activated sludge model, which was used the state spacemethod and step acceleration algorithm to describe relationship between the control andwater quality, this article was put forward a kind of control algorithm based on activesludge model. Through analysed the simulation result which have been done theexperiment of A~2/O system, the ammonia nitrogen and nitrate nitrogen were selected astarget variables of effluent flow, dissolved oxygen and inside return sludge ratio wereslected as the control variables. Under the traditional strategy of control, it was couldnot select and confirm the controlled parameter by experience.When sludge age (SRT)is for15days, dissolved oxygen is0.65mg/L, the inside return sludge ratio is50%,ammonia nitrogen of effluent is13.53mg/L, nitrate nitrogen of effluent is24.12mg/L.Ammonia nitrogen and nitrate nitrogen are more than the B level of urban sewagedischarge standard. Through simulation of calculation, dissolved oxygen increment is1.84, the inside return sludge ratio of increment is0.75. After simulating of control,ammonia nitrogen was below4.1mg/L, and nitrate nitrogen of effluent was below9.4mg/L by contorl. The results show that this method can operate the control parameter quantitatively as influent is constant in the wastewater treatment system. Thoughmonitored the quality of influent, this method also achieved forward control inwastewater treatment system.
引文
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