Dynamic Models and Control Strategies for Wastewater Treatment Plants - An Overview (original) (raw)

Dynamic models and control strategies for wastewater treatment processes

Water Research, 1974

Consideration of dynamic behavior and the incorporation of modem 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 digested sludge. The effectiveness of the control strategy is dependent upon the type of forcing to which the digester is subjected.

Control Strategies of Wastewater Treatment Plants

The objective of the current study is to investigate various control strategies implemented to wastewater treatment plants. The paper starts with discussion in modeling part of wastewater system and continues with designation of control objectives and control parameters. Subsequently, the implementations of common control structures including feedback, feedforward-feedback, supervisory and hierarchical controls are explained. The study is exclusively emphasized on four control techniques. Model predictive control performs superior control in optimizing nitrogen removal based on predictions of future behavior of wastewater systems. The performances of PID control in dissolve oxygen and nitrate control is improved significantly with multivariable configuration. Similar results achieved by data-driven approach compared to default PI simulation. Finally, artificial neural networks are commonly suggested for modeling and prediction purposes. A study is emphasized on Benchmark Simulation Model No. 1. The paper serve as a reference and for future research improvements in developing new advanced control techniques for wastewater field that aims in achieving stringent effluent quality standards.

Improving Process Management in a Water Treatment Plant Using Control Modelling

IFIP Advances in Information and Communication Technology, 2016

This work presents a modelling and a simulation of a pH control for process management in a drinking water treatment plant. A range of historical data, or knowledge base, was used to define the behavior of each input and disturbances of the process, using the MATLAB/Simulink software. The present pH control modelling has been simulated and compared to some experimental tests, thus contributing to achieve and identify operational scenarios in a real water treatment plant. Therefore, the present results allows to predict not only the present scenarios but also new operational conditions, in order to estimate the better process parameters and reduce some costs related to raw materials, such as the lime consumption , in water treatment plants.

Wastewater Treatment Plant Operation: Simple Control Schemes with a Holistic Perspective

Sustainability, 2020

In this paper, a control approach for improving the overall efficiency of a wastewater treatment plant (WWTP) is presented. It consists of a cascaded control system that uses a global performance indicator as the controlled variable to drive the plant to operating conditions that satisfies trade-offs involved in the WWTP operation, improving the global performance of the plant. The selected global performance indicator is the N/E index that measures the ratio between the amount of nitrogenated compounds eliminated (kgN) and the energy (kWh) required to achieve that goal. This index links the variables of the activated sludge process with the energy consumed in the whole plant, thus the control strategy takes actions based on plantwide considerations. An external Proportional Integral (PI) controller changes the DO set point according to the N/E index and the basic dissolved oxygen (DO) control scheme in the activated sludge process follows this reference changes varying the aeration...

Control Strategies of a Wastewater Treatment Plant

IFAC-PapersOnLine, 2019

The paper deals with the control of a wastewater treatment plant designed for a 250,000 inhabitants city. In order to developed different control strategies a specific influent was defined. It is the influent from BSM1 calibrated according to the real data of the wastewaters collected from the wastewater treatment plant. Five control strategies were developed based on conventional controllers and compared to each other using the quality indicators specific to the wastewater treatment domain. Finally, an optimal setpoint-based control method has been developed which takes into consideration a criterion based on two very important factors in the case of a large-capacity wastewater treatment plant: the cost of the biological treatment and the effluent quality.

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.

Dynamic simulations of waste water treatment plant operation

Chemical Papers, 2011

Activated Sludge Model No. 1 (ASM1) was used to model the biological stage of an actual waste water treatment plant (WWTP). Some possibilities for the utilisation of simulation programs for WWTP operation are presented. Simulation calculations were performed taking the conditions of WWTP in Nové Zámky, the Slovak Republic, into consideration, where measurements of the diurnal variations in waste water flow and composition at the inlet and outlet were carried out. A calibrated model predicting the influence of changes in the waste water composition and the operational parameters on the effluent waste water quality and related operational costs is available. Values of the operational parameters (solids retention time, internal recirculation flow, dissolved oxygen concentration) for effective operation (effluent concentration values, oxygen consumption, charges, i.e. charges for waste water discharge into the recipient water body) of the WWTP were obtained by simulations. The presented results are for illustration purposes only and are not intended as instructions for the operation of a waste water treatment plant. They correspond to the calibrated mathematical model ASM 1 based on the results of experimental measurements and operational data, as well as on the technical and monitoring level of the WWTP.

Process control and optimization of wastewater treatment plants using simulation softwares: a review

International Journal of Advanced Technology and Engineering Exploration, 2016

Among various technologies available for potable water production, the treatment of wastewater is an established technology in several countries such as the USA, Persian Gulf and European countries [1]. On the basis of working energy principle, desalination processes are classified into two classes namely thermal processes which involves phase change due to addition of heat and also membrane processes that involve pressure energy. Further thermal processes can be classified into multi-effect evaporation (MEE), multi stage flash (MSF) and vapor-compression (VC) processes. Membrane processes can be classified into RO and electrodialysis (ED) processes. Among these different technologies for wastewater treatment, MSF processes has many features such as it is large scale operation and has ability to deliver good quality potable water [2]. Water treatment operation was started during early part of 20th century. Water treatment is a complex process which requires efficient and accurate control system in plant to maintain operation at optimum condition so that it will cause minimum product cost and prevention of scale formation. Control systems are of two types one is conventional strategies and other one is advanced control.