Improving total nitrogen removal using a neural network ammonia-based aeration control in activated sludge process

Aeration control is a way to have a wastewater treatment plant (WWTP) that uses less energy and produces higher effluent quality to meet state and federal regulations. The goal of this research is to develop a neural network (NN) ammonia-based aeration control (ABAC) that focuses on reducing total nitrogen and ammonia concentration violations by regulating dissolved oxygen (DO) concentration based on the ammonia concentration in the final tank, rather than maintaining the DO concentration at a set elevated value, as most studies do. Simulation platform used in this study is Benchmark Simulation Model No. 1, and the NN ABAC is compared to the Proportional-Integral (PI) ABAC and PI controller. In comparison to the PI controller, the simulation results showed that the proposed controller has a significant improvement in reducing the AECI up to 23.86%, improving the EQCI up to 1.94%, and reducing the overall OCI up to 4.61%. The results of the study show that the NN ABAC can be utilized to improve the performance of a WWTP’s activated sludge system

Predictive control of an activated sludge process for long term operation

The application of a multivariable predictive controller to an activated sludge process is discussed in this work. Emphasis is given to the model identification and the long term assessment of the controller efficiency in terms of economical and environmental performances. A recurrent neural network model is developed for the identification problem and the dynamic matrix control is chosen as suitable predictive control algorithm for controlling the nitrogen compounds in the bioreactor. Using the Benchmark Simulation Model No. 1 as virtual platform, different predictive controller configurations are tested and further improvements are achieved by controlling the suspended solids at the end of the bioreactor. Based on the simulation results, this work shows the potentiality of the dynamic matrix control that together with a careful identification of the process, is able to decrease the energy consumption costs and, at the same time, reduce the ammonia peaks and nitrate concentration in the effluent

Predicting wastewater treatment plant performance during aeration demand shifting with a dual-layer reaction settling model

Demand response (DR) programmes encourage energy end users to adjust their consumption according to energy availability and price. Municipal wastewater treatment plants are suitable candidates for the application of such programmes. Demand shedding through aeration control, subject to maintaining the plant operational limits, could have a large impact on the plant DR potential. Decreasing the aeration intensity may promote the settling of the particulate components present in the reactor mixed liquor. The scope of this study is thus to develop a mathematical model to describe this phenomenon. For this purpose, Benchmark Simulation Model No.1 was extended by implementing a dual-layer settling model in one of the aerated tanks and combining it with biochemical reaction kinetic equations. The performance of this extended model was assessed in both steady-state and dynamic conditions, switching the aeration system off for 1 hour during each day of simulation. This model will have applications in the identification of potential benefits and issues related to DR events, as well as in the simulation of the plant operation where aerated tank settling is implemented.Science Foundation IrelandESIPP UC

Benchmarking of Control Strategies for Wastewater Treatment Plants

Wastewater treatment plants are large non-linear systems subject to large perturbations in wastewater flow rate, load and composition. Nevertheless these plants have to be operated continuously, meeting stricter and stricter regulations. Many control strategies have been proposed in the literature for improved and more efficient operation of wastewater treatment plants. Unfortunately, their evaluation and comparison – either practical or based on simulation – is difficult. This is partly due to the variability of the influent, to the complexity of the biological and biochemical phenomena and to the large range of time constants (from a few minutes to several days). The lack of standard evaluation criteria is also a tremendous disadvantage. To really enhance the acceptance of innovative control strategies, such an evaluation needs to be based on a rigorous methodology including a simulation model, plant layout, controllers, sensors, performance criteria and test procedures, i.e. a complete benchmarking protocol.  This book is a Scientific and Technical Report produced by the IWA Task Group on Benchmarking of Control Strategies for Wastewater Treatment Plants. The goal of the Task Group includes developing models and simulation tools that encompass the most typical unit processes within a wastewater treatment system (primary treatment, activated sludge, sludge treatment, etc.), as well as tools that will enable the evaluation of long-term control strategies and monitoring tasks (i.e. automatic detection of sensor and process faults). Work on these extensions has been carried out by the Task Group during the past five years, and the main results are summarized in Benchmarking of Control Strategies for Wastewater Treatment Plants. Besides a description of the final version of the already well-known Benchmark Simulation Model no. 1 (BSM1), the book includes the Benchmark Simulation Model no. 1 Long-Term (BSM1_LT) – with focus on benchmarking of process monitoring tasks – and the plant-wide Benchmark Simulation Model no. 2 (BSM2).

Development and economic assessment of different WWTP control strategies for optimal simultaneous removal of carbon, nitrogen and phosphorus

This paper presents the comparison of four control strategies for the A²/O WWTP configuration for simultaneous C, N and P removal. The control strategies: (i) external COD-P control; (ii) external recycle flow-P control; (iii) nitrate control in the last anoxic reactor; (iv) ammonia control in the last aerobic reactor, were combined with other common control loops to build different control structures and were simulated in Matlab/Simulink under different influent conditions. A systematic approach was conducted with all the strategies to assess their potential effectiveness, according to the following steps: theoretical design, setpoint optimization and, finally, a detailed comparison of the control results against a reference operation and an optimized reference scenario. The optimization of the reference operation presented a 7% reduction of the total operational cost. The simulation results showed that some control strategies further reduced 3-7.5% the WWTP operational costs while the effluent quality is greatly improved

Towards a plant-wide Benchmark Simulation Model with simultaneous nitrogen and phosphorus removal wastewater treatment processes.

It is more than 10 years since the publication of the Benchmark Simulation Model No 1 (BSM1) manual (Copp, 2002). The main objective of BSM1 was creating a platform for benchmarking carbon and nitrogen removal strategies in activated sludge systems. The initial platform evolved into BSM1_LT and BSM2, which allowed the evaluation of monitoring and plant-wide control strategies, respectively. The fact that the BSM platforms have resulted in 300+ publications demonstrates the interest for the tool within the scientific community. In this paper, an extension of the BSM2 is proposed. This extension aims at facilitating simultaneous carbon, nitrogen and phosphorus (P) removal process development and performance evaluation at a plant-wide level. The main motivation of the work is that numerous wastewater treatment plants (WWTPs) pursue biological phosphorus removal as an alternative to chemical P removal based on precipitation using metal salts, such as Fe or Al. This paper identifies and discusses important issues that need to be addressed to upgrade the BSM2 to BSM2-P, for example: 1) new influent wastewater characteristics; 2) new (bio) chemical processes to account for; 3) modifications of the original BSM2 physical plant layout; 4) new/upgraded generic mathematical models; 5) model integration; 6) new control handles/sensors; and 7) new extended evaluation criteria. The paper covers and analyzes all these aspects in detail, identifying the main bottlenecks that need to be addressed and finally discusses the aspects where scientific consensus is required

Model predictive control for the self-optimized operation in wastewater treatment plant : analysis of dynamic issues

[EN] This paper describes a procedure to find the best controlled variables in an economic sense for the activated sludge process in a wastewater treatment plant, despite the large load disturbances. A novel dynamic analysis of the closed loop control of these variables has been performed, considering a nonlinear model predictive controller (NMPC) and a particular distributed NMPC-PI control structure where the PI is devoted to control the process active constraints and the NMPC the self-optimizing variables. The well-known self-optimizing control methodology has been applied, considering the most important measurements of the process. This methodology provides the optimum combination of measurements to keep constant with minimum economic loss. In order to avoid non feasible dynamic operation, a preselection of the measurements has been performed, based on the nonlinear model of the process and evaluating the possibility of keeping their values constant in the presence of typical disturbances.[ES] Este trabajo describe un procedimiento eficiente para encontrar las mejores variables para el proceso de lodos activados en una planta de tratamiento de aguas residuales, a pesar de las grandes perturbaciones de carga. Se ha realizado un nuevo análisis dinámico del control en bucle cerrado de estas variables, considerando un controlador predictivo de modelo no lineal (NMPC) y una estructura de control NMPC-PI distribuida. Se ha aplicado la conocida metodología de control de auto-optimización, considerando las mediciones más importantes del proceso. Esta metodología proporciona la combinación óptima de mediciones para mantener constante con pérdidas económicas mínimas. Para evitar un funcionamiento dinámico no factible, se ha realizado una preselección de las mediciones, basándose en el modelo no lineal del proceso y evaluando la posibilidad de mantener constantes sus valores en presencia de perturbaciones típicas

New approach for regulation of the internal recirculation flow rate by fuzzy logic in biological wastewater treatments

Altres ajuts: Acord transformatiu CRUE-CSICMarian Barbu acknowledge the support of the project " EXPERT ", Contract no. 14PFE/17.10.2018.The internal recirculation plays an important role on the different biological processes of wastewater treatment plants because it has a great influence on the concentration of pollutants, especially nutrients. Usually, the internal recirculation flow rate is kept fixed or manipulated by control techniques to maintain a fixed nitrate set-point in the last anoxic tank. This work proposes a new control strategy to manipulate the internal recirculation flow rate by applying a fuzzy controller. The proposed controller takes into account the effects of the internal recirculation flow rate on the inlet of the biological treatment and on the denitrification and nitrification processes with the aim of reducing violations of legally established limits of nitrogen and ammonia and also reducing operational costs. The proposed fuzzy controller is tested by simulation with the internationally known benchmark simulation model no. 2. The objective is to apply the proposed fuzzy controller in any control strategy, only replacing the manipulation of the internal recirculation flow rate, to improve the plant operation.Therefore, it has been implemented in five operation strategies from the literature, replacing their original internal recirculation flow rate control, and simulation results are compared with those of the original strategies. Results show improvements with the application of the proposed fuzzy controller of between 2.25 and 57.94% in reduction of total nitrogen limit violations, between 55.22 and 79.69% in reduction of ammonia limit violations and between 0.84 and 38.06% in cost reduction of pumping energy