Control Of Wastewater Treatment Plants Research Articles

Modélisation du comportement des matières en suspension à l'effluent d'un décanteur primaire lamellaire

Process modelling can prove a useful tool for the control of wastewater treatment plants. The objective of this research was to verify that a primary settling model developped for a conventional process is applicable to a process using lamellar settling. The lumped-parameter model examines the hydraulics of a system composed of stirred tank reactors in series and simulates suspended solid concentration of the effluent under various flow regimes. The model has been validated using data collected from a pilot lamella settler of a capacity of 15 m3 and operated over a wide range of flows (Hazen velocity between 0,43 and 2,59 m∙h−1). The prediction of the model was in agreement with the observed values both in terms of concentration and hydraulic behavior of effluent suspended solids (average relative error of 17%). How ever, less satisfactory was the model performance tested with the concentration data on settleable solids. Research is under way to study the different mechanisms of sedimentation going on in the settler. Key words: modelling, lamellar settling, settleable suspended solids.

Automatic tuning and gain scheduling for pH control

A framework is proposed for automatic tuning and gain scheduling in pH control. The nominal “tuning constants” and the “gain schedule” are found from one relay feedback experiment. The Gulaian—Lane titration curve model is modified so that the process titration curve is a linear combination of two base titration curves. The concept of selection of secondary measurements is extended for the selection of base titration curves. A criterion is also proposed whereby the base titration curve can be determined in an quantitative manner if prior knowledge about variations in the composition of the influent is available. With this model structure, the tuning constants and the gain schedule (from the estimated titration curve) can be determined from a relay feedback experiment. Simulation results show that a robust estimation of the process titration curve can be obtained even under severe process conditions. Furthermore, the proposed approach can overcome the realistic problem facing pH control in most wastewater treatment plants, that of rapid and large changes in influent composition, in a reliable manner.

Development of a real-time expert system for wastewater treatment plants control

A real-time expert system to control wastewater treatment plants is presented. The software has been developed in the G2 environment. It contains: an interface that permits on-line acquisition of plant data using G2 standard interface (GSI), a predictive control algorithm for dissolved oxygen (DO) control, and a graphical interface between the expert system and the operator. The dissolved oxygen control is performed using a non-linear predictive control algorithm, that has been developed to satisfy quality constraints whilst reducing energy demands. The algorithm uses data obtained from the plant by hardware sensors, and software which recursively estimates the oxygen uptake rate. All these elements are integrated in a knowledge base that includes a set of diagnosis, detection, prediction and operation rules, making the system capable of handling a wide number of usual (where predictive control can be useful) and unusual situations (where quantitative and qualitative information must be considered.

Strategy of stochastic real-time control of wastewater treatment plants

The paper describes fundamentals of stochastic real-time control (RTC) of wastewater treatment and disposal facilities operating under dynamic wet weather/dry weather conditions. Similar models are also applicable to the control of combined sewer overflows (CSO's). Objectives and goals, components, strategy, and operation of RTC systems are delineated. RTC systems can be incorporated into an expert system to assist the operator of wastewater treatment and disposal facilities, and/or into semior fully automated systems. The stochastic transfer functions used for prediction of the inputs and response of the system belong to the class of ARMA stochastic models. Neural network models are also applicable. Such models can be shown to be consistent with traditional deterministic transfer functions. A review of existing RTC systems concludes the paper.

Monitoring and control of biological removal of phosphorus and nitrogen by flow-injection analysers in a municipal pilot-scale waste-water treatment plant

A flow-injection system is used for monitoring and control of a biological waste-water treatment plant with biological removal of phosphate and nitrate. The waste-water treatment plant is an activated sludge type on a pilot scale, with municipal waste water as the influent. The flow-injection system monitors the concentrations of phosphate, ammonia and nitrate in four places: in the inlet, in the outlet of the anaerobic pretreatment tank, in one of the aeration tanks and in the outlet of the plant. Sampling is carried out via a cross-flow filter system, based on an ultra-filtration membrane. The analysers employ highly pulsating, single-piston liquid chromatographic pumps. Synchronization of injection time and pump pulses eliminates the need for pulse-damping devices and ensures high reproducibility. The chemical methods are based on classical colorimetric methods. The measurement system has been designed with emphasis on long-term stability, low reagent consumption and minimum maintenance. To maintain stable, low flow-rates, on-line degassing has been installed for each reagent. Further, on-line standard calibration is being used to compensate for drift in the sensitivity of the analysers. The system is controlled by a PC, programmed in ASYST. The calibrated data is fed to a programmable logic controller (PLC), which also controls the pilot plant. A supervisory PC, programmed in Factory Link, stores and presents data. The measurements will be used for studies of different control strategies for the plant, e.g., rule-based control.

The automatic control of wastewater treatment plants

Witney Sewage Treatment Works has been established as an evaluation and demonstration facility for automatic control equipment and techniques. Routine operation of the plant has been maintained by its automatic control system. Assessments of several of the main control functions have shown benefits which include cost savings, better operation and early warning of equipment failure. Further work is necessary to perfect the monitoring of the effluent quality. The evaluation of current instrumentation coupled with general operational experience are providing information for the UK Water Industry and contributing to the development of user specifications.

Recursive Identification and Adaptive Forecasting of Wastewater Flows

In the control of wastewater pumping stations and treatment plants. the forecasting of sewage flows will allow better management of the sewer system by reducing overflows and operational cost. Wastewater flows normally exhibit a diurnal flow pattern with large variations in daily mean and are affected by rapid rainfall infiltration and the slower groundwater infiltration. These factors have to be taken into consideration in the prediction method.A direct k-step adaptive predictor is used to forecast the wastewater flow. The parameters of the multi-input/single output ARMAX model are recursively estimated at each time step by the method of extended least squares; a forecast of the wastewater flow k-step ahead is then made on the basis of the updated model. This method is illustrated for a sewage catchment in Melbourne. Australia which has a sewer system separate from the stormwater system.The model uses the measured sewer flow as outputs and rainfall intensities and/or flow pattern as inputs. Prefiltering and averaging of the data prior to identification reduces the error in the estimation of the fast response peaks in wet conditions. Under normal flow conditions where the rate of increase in sewer flow is slow. the adaptive predictor is robust. In wet conditions. the estimation of the size and occurrence of the fast response peak was found to be dependent on the structure of the model.

Field Verification of On-Line Instrumentation at a Municipal Wastewater Treatment Plant

As part of a full-scale project to demonstrate the advantages of using automated process control in wastewater treatment plants, on-line sensors used in various control loops were calibrated and/or verified during control system commissioning and startup. The on-line measurements included liquid flow rates, air flow rates, suspended solids concentrations, and dissolved oxygen concentrations. The methods used to confirm instrument performance are presented along with results that show that several instruments were found to operate outside the manufacturers' written specifications. In addition, on-line methods which can help determine when recalibrations are required, and thereby help to reduce maintenance costs and ensure reliability, are also presented.

Operational estimation and prediction of nitrification dynamics in the activated sludge process

This paper examines the feasibility and discusses the potential of applications of on-line real-time state estimation and prediction in operational control of the activated sludge process. In particular, the dynamics of nitrification are considered with reference to the activated sludge unit at the Norwich Sewage Works in eastern England. A recursive estimation algorithm, the extended Kalman filter, is applied both for reconstructing operating information on the variations in nitrifying bacterial population concentrations and for making predictions of process performance under assumed scenarios for the short-term future operating conditions of the plant. Time-series field data from the Norwich Works are used for the former analysis. Considerations of uncertainty and the possibility of rapid major perturbations in performance, for example, due to spillages of toxic substances or the loss of solids over the clarifier weir, are of special importance to the discussion. The paper is introduced and concluded with some more general comments on the roles of operator experience and decision-making and man-machine interaction in wastewater treatment plant control.

Application of a bioluminescence ATP assay in brewery wastewater treatment studies

AbstractThe importance of having a rapid method for determining the viable biomass in activated‐sludge wastewater treatment plants (WWTP) for process control and development is well recognized. The firefly bioluminescence ATP assay has been proposed for this purpose. Such an assay using partially purified firefly luciferase and synthetic firefly luciferin for the bioluminescence reaction, a liquid scintillation counter in the out‐of‐coincidence mode as luminescence detector, and a sludge ATP extraction technique involving dimethyl sulfoxide at room temperature is described. Experiments with several pure bacteria cultures were done to demonstrate the feasibility of applying this assay to activated sludge to activated sludge WWTP investigation and control. The ATP content of samples taken from various points in a 350000 gal/day brewery activated‐sludge WWTP was monitored for 4.5 months. Good linear correlation between ATP and mixed‐liquor suspended solids, return sludge suspended solids, and effluent suspended solids were observed. Percentage viabilities of the various sludge samples were derived from the ATP results.

Modelling and Adaptive Control of Urban Wastewater Treatment Plants

In this paper a Kinetic model for an activated sludge wastewater treatement plant based on the Monod single strain bacterial growth process is developed. In accounting for the unpredictable temporal variations in influent mass flow-rate and concentration, the consequent equations are shown to be nonlinear stochastic differential equations of the Ito type. Various effluent control strategies, including proportional and adaptive are investigated using a first order simulation algorithm for multivariable nonlinear stochastic Ito equations

Dynamic models and control strategies for wastewater treatment processes

Consideration of dynamic behavior and the incorporation of modern control systems can lead to substantial improvements in the performance of wastewater treatment plants. Other potential benefits include increased productivity, greater reliability, lower operational costs, more stable operation and faster start-ups. Several powerful tools are available for the study of dynamic behavior. Included among these are dynamic mathematical models, computer simulation, transient response analysis and process stability evaluation. Simple examples illustrating the theory and use of these tools are presented. The development of a control strategy is intimately related to the dynamic behavior of a process. Some of the basic questions which must be answered in developing a control strategy are: (1) What information should be collected? (2) How should the information be transmitted? (3) How should the information be processed? (4) What control actions should be taken? A wide variety of control algorithms are available for the processing of information for control. A discussion of several of these, on-off, PID. ratio, cascade, and feedforward, is presented and an example is given for the application of on-off control to a biological CFSTR. Digital computers are also being increasingly used for control of wastewater treatment plants and a discussion of computer control systems is presented. Examples of dynamic models and control strategies for two wastewater treatment processes, the step feed activated sludge process and the anaerobic digester, are presented and discussed, In addition, dynamic modeling and computer simulations are used to indicate those design and operational factors for the anaerobic digester which are effective in improving process stability. An effective control strategy for the activated sludge process is that provided by the step feed process which permits changing the points at which wastewater is added along the length of the reactor. Example control strategies for the anaerobic digester include the addition of base and the recirculation of the digested sludge. The effectiveness of the control strategy is dependent upon the type of forcing to which the digester is subjected.