Simulated Wastewater Treatment Plant Research Articles

Fault Detection and Diagnosis using Multivariate Statistical Techniques in a Wastewater Treatment Plant.

Abstract Abstract In this paper Principal Components Analysis (PCA) is used for detecting faults in a simulated wastewater treatment plant (WWTP). Diagnosis tasks are treated using Fisher discriminant analysis (FDA). Both techniques are multivariate statistical techniques used in multivariate statistical process control (MSPC) and fault detection and isolation (FDI) perspectives. PCA reduces the dimensionality of the original historical data by projecting it onto a lower dimensionality space. It obtains the principal causes of variability in a process. If some of these causes change, it can be due to a fault in the process. FDA provides an optimal lower dimensional representation in terms of a discriminant between classes of data, where, in this context of fault diagnosis, each class corresponds to data collected during a specific and known fault. A discriminant function is applied to diagnose faults using data collected from the plant.

Support Vector Machines for Environmental Informatics: Application to Modelling the Nitrogen Removal Processes in Wastewater Treatment Systems

In order to meet the new stringent environmental regulations, it is necessary to investigate the adaptive and optimal control strategies for the biological wastewater treatment processes. Nitrogen removal is one of the essential concerns in wastewater treatment. Nitrogen removal is a nonlinear, dynamic, and time variant complex process as complicated activities of microbial metabolism are involved. The mechanistic models for nitrogen removal are complicated and still uncertain to some extent. A new machine learning approach, Support Vector Machine (SVM) was proposed as black-box modeling technique to model the biological wastewater treatment processes. LS-SVM, a simplified formulation of SVM, has been applied in this study to predict the concentration of nitrate and nitrite (NO) in the Mixed Liquor (ML) of wastewater treatment plant. Nonlinear Autoregressive model with Exogenous inputs (NARX model) can be employed with LS-SVM to extract useful information and improve the prediction performance. In this paper, the premium wastewater treatment plant simulation and optimization software, GPS-X, is used to create virtual plant layout and simulated data. The simulation results indicate that the proposed method has good generalization performance, especially when the input is fluctuated without a usual pattern. We conclude that LS-SVM with NARX modelling could be used as an alternative approach to predict the behaviour of wastewater treatment systems by further studying some essential issues such as the tuning of memory order and training data size.

Simulation of the Impact of Higher Ammonia Recycle Loads Caused by Upgrading Anaerobic Sludge Digesters

Abstract Upgrading conventional single-stage mesophilic anaerobic digestion to an advanced digestion technology can increase sludge stability, reduce pathogen content, increase biogas production, and also increase ammonia concentrations recycled back to the liquid treatment train. Limited information is available to assess whether the higher ammonia recycle loads from an anaerobic sludge digestion upgrade would lead to higher discharge effluent ammonia concentrations. Biowin, a commercially available wastewater treatment plant simulation package, was used to predict the effects of anaerobic digestion upgrades on the liquid train performance, especially effluent ammonia concentrations. A factorial analysis indicated that the influent total Kjeldahl nitrogen (TKN) and influent alkalinity each had a 50-fold larger influence on the effluent NH3 concentration than either the ambient temperature, liquid train SRT or anaerobic digestion efficiency. Dynamic simulations indicated that the diurnal variation in effluent NH3 concentration was 9 times higher than the increase due to higher digester VSR. Higher recycle NH3 loads caused by upgrades to advanced digestion techniques can likely be adequately managed by scheduling dewatering to coincide with periods of low influent TKN load and ensuring sufficient alkalinity for nitrification.

Application of the IWA Anaerobic Digestion Model (ADM1) for simulating full-scale anaerobic sewage sludge digestion

A steady-state implementation of the IWA Anaerobic Digestion Model No. 1 (ADM1) has been applied to the anaerobic digesters in two wastewater treatment plants. The two plants have a wastewater treatment capacity of 76,000 and 820,000 m3/day, respectively, with approximately 12 and 205 dry metric tons sludge fed to digesters per day. The main purpose of this study is to compare the ADM1 model results with full-scale anaerobic digestion performance. For both plants, the prediction of the steady-state ADM1 implementation using the suggested physico-chemical and biochemical parameter values was able to reflect the results from the actual digester operations to a reasonable degree of accuracy on all parameters. The predicted total solids (TS) and volatile solids (VS) concentration in the digested biosolids, as well as the digester volatile solids destruction (VSD), biogas production and biogas yield are within 10% of the actual digester data. This study demonstrated that the ADM1 is a powerful tool for predicting the steady-state behaviour of anaerobic digesters treating sewage sludges. In addition, it showed that the use of a whole wastewater treatment plant simulator for fractionating the digester influent into the ADM1 input parameters was successful.

PROCESS SIMULATOR FOR WASTEWATER TREATMENT PLANT

Dynamic models and process simulators can be very useful in creation of effective control systems for wastewater treatment processes. They also allow seizing procedures of designing of technological processes, helping to estimate and to pick up successfully technological parameters, which influence stability and efficiency of processes. Modern wastewater treatment is a quite complex process, which includes several treatment steps before the water is released to the recipient. The typical process of wastewater treatment includes four stages: mechanical treatment, biological treatment, chemical treatment, and sludge treatment. In this paper the separate models for each wastewater treatment stage are combined to form a complex dynamic model for simulation of wastewater treatment plant. Important data from Kaunas wastewater treatment plant are collected to facilitate the identification of mathematical models parameters.

Biological nutrient removal model No.1 (BNRM1)

This paper presents the results of the work carried out by the CALAGUA Group on Mathematical Modelling of Biological Treatment Processes: the Biological Nutrient Removal Model No.1. This model is based on a new concept for dynamic simulation of wastewater treatment plants: a unique model can be used to design, simulate and optimize the whole plant, as it includes most of the biological and physico-chemical processes taking place in all treatment operations. The physical processes included are: settling and clarification processes (flocculated settling, hindered settling and thickening), volatile fatty acids elutriation and gas-liquid transfer. The chemical interactions included comprise acid-base processes, where equilibrium conditions are assumed. The biological processes included are: organic matter, nitrogen and phosphorus removal; acidogenesis, acetogenesis and methanogenesis. Environmental conditions in each operation unit (aerobic, anoxic or anaerobic) will determine which bacterial groups can grow. Thus, only the model parameters related to bacterial groups able to grow in any of the operation units of a specific WWTP will require calibration. One of the most important advantages of this model is that no additional analysis with respect to ASM2d is required for wastewater characterization. Some applications of this model have also been briefly explained in this paper.

Modeling Of Waste Water Treatment Plant With Regression Trees

Simulation of wastewater treatment plants (WWTP) is a difficult task, due to the complex and mostly dynamic behaviour of the WWTP system. Regression trees are presented as an useful simulation/modelling tool for making predictions on WWTP operation given measured data at the input. Crucial step in the construction of such models is data preparation. Two data sets measured on two different WWTP are used in this paper. Both data bases are composed of data that are usually measured on a WWTP and characterise the WWTP operation. The main difference between them is in data presentation. In the first data set (WWTP1) data are presented as a one-day situation of the plant operation, i.e. daily averaged values of the measured data (attributes) are given. Second data set (WWTP2) is composed of actual values of the attributes measured in one hour intervals. Regression tree models, that predict outflow attributes according to inflow attributes are constructed for both data sets and compared in their performance. Assumption that data presentation and further preparation have a big influence on the results was confirmed. Program package WEKA, which includes most of popular machine learning algorithms, was used for constructing the models.

CONTROL STRATEGY EVALUATION FOR COMBINED N AND P REMOVAL USING A BENCHMARK WASTEWATER TREATMENT PLANT

The COST wastewater treatment plant simulation benchmark is a useful example for evaluation of control strategies aiming at improving biological nitrogen removal. In the SMAC project the phosphorus removal process based on the ASM2d model was added as an extension to the existing benchmark wastewater treatment plant. This results in an example for evaluation of control strategies for combined nitrogen and phosphorus removal from wastewater a necessity in the frame of the SMAC project. The phosphorus removal treatment plant is illustrated via a case study where the addition of extra carbon source and metal salts for improving phosphorus removal are considered.

Modeling of a reactive primary clarifier

Even though many models have been proposed for primary clarification, none is directly compatible with the ASM1. The objective of this paper is to present the development of a reactive primary clarifier model to be used in a wastewater treatment plant simulator (WEST). A model simulating COD behavior has been developed based on the Takacs model, and was tested with full-scale data. Particulate effluent COD was well described but problems occurred predicting the underflow suspended solids concentration. The model had to be upgraded with a residence time and a flocculation term to simulate the behavior of soluble COD. An ammonification term was added to the model, resulting in an improved model fit on effluent ammonium.

On-line simulation of wastewater treatment plants

A software system to support the operation of municipal or industrial wastewater treatment plants is introduced. The demands on and solutions for this system, with respect to control and observer design, software implementation as well as the operator interface, are worked out. Results of a project to develop a model based operation support system for wastewater treatment plants are presented. Possible applications to train operators, to design software sensors and to enable prognosis are explained. The test case - a full scale WWTP - is introduced. Finally, a prototype of a technical environment for on-line simulations and remote operation is presented.

A dynamic solids inventory model for activated sludge systems

Clarifier hydrodynamics plays an important role in the activated sludge process. Attention has long been focused on the biological behavior of the aeration basin in the secondary treatment system. One-dimensional settler models or empirical relationships have typically been coupled in wastewater treatment plant simulation systems to represent the clarifier. The research on the hydrodynamic aspects of the process are currently restricted to a clarifier uncoupled from the aeration basin. In this paper, a dynamic model of the activated sludge process is presented in which balanced emphasis is put on the hydrodynamic aspect of the system. The model integrates a biological reaction submodel for an aeration basin with a two-dimensional hydrodynamic solids transport submodel for the secondary clarifier. A verification of the model is carried out against a set of field data and shows good agreement. The model has been used to investigate the response and the interdependency of the aerator and clarifier in the activated sludge system.

Methodology for the development of a wastewater treatment plant simulator

A methodology for the modelling of wastewater treatment plants by activated sludge is proposed. It takes into account the strong coupling between hydrodynamics and biological reactions. Hydrodynamical modelling makes use of residence time distributions obtained by tracing the different units (primary settler, aeration tank and secondary clarifier) with lithium chloride. The biological model is based on IAWPRC Task Group Model 1. Simulated time and space profiles are in good agreement with experimental data, taken on an existing full-scale plant.

OPTIMIZING OPERATION OF WASTEWATER TREATMENT PLANTS BY OFFLINE AND ONLINE COMPUTER SIMULATION

Computer simulation of activated sludge plant for nitrogen removal has become a reliable tool to predict the behaviour of the plant Models including biological phosphorus removal still require some practical experience but they should be available soon. This will offer an even wider range than today's work with nitrogen removal. One major benefit of computer simulation of wastewater treatment plants (WTP) is the optimization of operation. This can be done offline if hydrographs of a plant are collected and computer work is done with “historical” analysis. With online simulation the system is fed with hydrographs up to the actual time. Prognosis can be done from the moment of the computer work based on usual hydrographs. The work of the authors shows how accuratly a treatment plant can be described, when many parameters are measured and available as hydrographs. A very careful description of all details of the special plant is essential, requiring a flexible simulation tool. Based on the accurate simulation a wide range of operational decisions can be evaluated. It was possible to demonstrate that the overall efficiency in nitrogen removal and energy consumption of ml activated sludge plant can be improved.

Dynamic Models for Clarifiers of Activated Sludge Plants with Dry and Wet Weather Flows

Dynamic simulation of wastewater treatment plants becomes more realistic, if models of primary and secondary clarification are implemented. A simple model of the primary clarifier can describe dynamics of buffered influent or sludge water concentrations. Different changes in ratios of particulate fractions of COD depending on influent flows are modelled as well. Processes in activated sludge plants are affected by the replacement of sludge to the clarifier and by the loss of solids through the effluent. These effects are very strong at combined water flows. The two models best applicable as of yet did not meet measured values for effluent solids. One of them describes thickening and storage of sludge quite well. The developed two component model presented here is able to represent the behaviour of secondary clarifiers at dry and wet weather flows.

Computer simulation of wastewater treatment plant

The computer simulation of wastewater treatment systems is finding increasingly wide application. Simulation studies of complete municipal waste treatment plants have been successfully accomplished. This paper describes an attempt to simulate the operation of the Kitchener, Ontario, Waste Treatment plant taking data from the last six months of 1975. It is shown that, provided some parameter values are taken from the actual plant, it is possible to closely match the mean monthly performance of the system. Steady-state mathematical models of the major waste treatment units are presented together with a discussion of the structure and operation of the SEPSIM computer program. Detailed cost relationships for a complete municipal waste treatment plant are also shown.