Optimization of Wastewater Treatment Plant Design using Process Dynamic Simulation: A Case Study from Kurdistan, Iraq

Satisfactory effluent characteristics are indispensable to evaluate the performance of any wastewater treatment plant (WWTP) design. Dynamic simulation software has a great role in pursuing this objective, in which an efficient and cost-effective design is constantly performed. In this study, a dynamic simulator sewage treatment operation analysis over time (STOAT) has been used under certain influent conditions to optimize design possibilities for modifying an existing primary WWTP College of Engineering Wastewater Treatment Plant (COEWWTP) at Erbil, Kurdistan, Iraq. The optimization was established on the basis of total suspended solids (TSS) and biochemical oxygen demand (BOD) characteristics in the effluent. Two alternative design schemes were proposed; trickling biofilter and aeration basin. In the dynamic simulation for the investigated design schemes, the predicted effluent profile showed that each of the existing and trickling biofilter processes has failed to correspond to the valid effluent limitation, whereas predicted results of the aeration basin exhibited an effluent profile that meets TSS and BOD allowable limits. Different simulation models have been implemented by STOAT to simulate treatment processes in studied design approaches: ASAL 1 model; BOD model; BOD semi-dynamic model; and SSED 1 model. This study offers an additional understanding of WWTP design and facilitates the application of dynamic simulators as tools for wastewater treatment development in Kurdistan

Multi-objective optimal control of small-size wastewater treatment plants

In this work, a multi-objective dynamic optimization of the operating strategy of a small-size wastewater treatment plant is carried out. In-situ incineration of the excess sludge produced for electricity production is investigated in order to reduce the operating costs. The trade-offs between the treatment quality and the operating costs are characterized. Compared to the literature, emphasis is put on a more rigorous formulation of the problem and an accurate modeling of the underlying phenomena so as to get physically relevant solutions. Thus, from a mathematical perspective, the problem is formulated so that the solution is less sensitive to the – arbitrarily chosen – plant initial conditions. Modeling of physical phenomena e.g. the detrimental effect of the concentration of suspended solids in the mixed liquor, on oxygen transfer rate, has been included in the model. Several constraints are added to the problem so as to maintain the optimal solutions within the limits of validity of the mathematical model. The results provided a clear picture about the trade-offs between the treatment quality and the exploitation costs. Sludge incineration was shown to be of a high energetic profit, but it does not allow the plant to be electrically autonomou

Joint Environmental and Economical Analysis of Wastewater Treatment Plants Control Strategies : a Benchmark Scenario Analysis

In this paper, a joint environmental and economic analysis of different Wastewater Treatment Plant (WWTP) control strategies is carried out. The assessment is based on the application of the Life Cycle Assessment (LCA) as a method to evaluate the environmental impact and the Benchmark Simulation Model No. 1 (BSM1). The BSM1 is taken as the benchmark scenario used to implement the control strategies. The Effluent Quality Index (EQI) and the Overall Cost Index (OCI) are two indicators provided by BSM1 and used to evaluate the plant's performance from the efluent quality and the economic points of view, respectively. This work conducts a combined analysis and assessment of ten different control strategies defined to operate a wastewater treatment plant. This analysis includes the usual economic and performance indexes provided by BSM1 joined with the LCA analysis that determines the environmental impact linked to each one of the considered control strategies. It is shown how to get an overall evaluation of the environmental effects by using a normalized graphical representation that can be easily used to compare control strategies from the environmental impact point of view. The use of only the BSM1 indexes provides an assessment that leads to a clustering of control strategies according to the cost/quality tradeoff they show. Therefore, regarding the cost/quality tradeoff, all strategies in the same group are almost equal and do not provide an indication on how to proceed in order to select the appropriate one. It is therefore shown how the fact of adding a new, complementary, evaluation (LCA based) allows either to reinforce a decision that could be taken solely on the basis of the EQI/OCI tradeoff or to select one control strategy among the others

Integration of set point optimization techniques into nonlinear MPC for Improving the operation of WWTPs

[EN] Optimization and control strategies are necessary to keep wastewater treatment plants (WWTPs) operating in the best possible conditions, maximizing effluent quality with the minimum consumption of energy. In this work, a benchmarking of different hierarchical control structures for WWTPs that combines static and dynamic Real Time Optimization (RTO) and non linear model predictive control (NMPC) is presented. The objective is to evaluate the enhancement of the operation in terms of economics and effluent quality that can be achieved when introducing NMPC technologies in the distinct levels of the multilayer structure. Three multilayer hierarchical structures are evaluated and compared for the N-Removal process considering the short term and long term operation in a rain weather scenario. A reduction in the operation costs of approximately 20% with a satisfactory compromise to Effluent Quality is achieved with the application of these control scheme.[ES] Las estrategias de optimización y control son necesarias para que las plantas de tratamiento de aguas residuales funcionen en las mejores condiciones posibles, maximizando la calidad de los efluentes con el mínimo consumo de energía. En este trabajo, se presenta un benchmarking de diferentes estructuras de control jerárquico para WWTP que combina Optimización en tiempo real estática y dinámica (RTO) y control predictivo modelo no lineal (NMPC). El objetivo es evaluar la mejora de la operación en términos de economía y calidad del efluente que se puede lograr al introducir las tecnologías NMPC en los distintos niveles de la estructura multicapa. Se evalúan y comparan tres estructuras jerárquicas multicapa para el proceso considerando la operación a corto y largo plazo en un escenario de lluvia. Con la aplicación de este esquema de control se logra una reducción de los costos de operación de aproximadamente el 20% con un compromiso satisfactorio a la calidad del efluente

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

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

A plant-wide model describing GHG emissions and nutrient recovery options for water resource recovery facilities

Acord transformatiu CRUE-CSICAltres ajuts: Borja Solís is grateful for the PIF PhD grant funded by Universitat Autònoma de Barcelona.In this study, a plant-wide model describing the fate of C, N and P compounds, upgraded to account for (on-site/off-site) greenhouse gas (GHG) emissions, was implemented within the International Water Association (IWA) Benchmarking Simulation Model No. 2 (BSM2) framework. The proposed approach includes the main biological N2O production pathways and mechanistically describes CO2 (biogenic/non-biogenic) emissions in the activated sludge reactors as well as the biogas production (CO2/CH4) from the anaerobic digester. Indirect GHG emissions for power generation, chemical usage, effluent disposal and sludge storage and reuse are also included using static factors for CO2, CH4 and N2O. Global and individual mass balances were quantified to investigate the fluxes of the different components. Novel strategies, such as the combination of different cascade controllers in the biological reactors and struvite precipitation in the sludge line, were proposed in order to obtain high plant performance as well as nutrient recovery and mitigation of the GHG emissions in a plant-wide context. The implemented control strategies led to an overall more sustainable and efficient plant performance in terms of better effluent quality, reduced operational cost and lower GHG emissions. The lowest N2O and overall GHG emissions were achieved when ammonium and soluble nitrous oxide in the aerobic reactors were controlled and struvite was recovered in the reject water stream, achieving a reduction of 27% for N2O and 9% for total GHG, compared to the open loop configuration

Model-based automatic tuning of a filtration control system for submerged anaerobic membrane bioreactors (AnMBR)

This paper describes a model-based method to optimise filtration in submerged AnMBRs. The method is applied to an advanced knowledge-based control system and considers three statistical methods: (1) sensitivity analysis (Morris screening method) to identify an input subset for the advanced controller; (2) Monte Carlo method (trajectory-based random sampling) to find suitable initial values for the control inputs; and (3) optimisation algorithm (performing as a supervisory controller) to re-calibrate these control inputs in order to minimise plant operating costs. The model-based supervisory controller proposed allowed filtration to be optimised with low computational demands (about 5min). Energy savings of up to 25% were achieved when using gas sparging to scour membranes. Downtime for physical cleaning was about 2.4% of operating time. The operating cost of the AnMBR system after implementing the proposed supervisory controller was about 0.045/m3, 53.3% of which were energy costs.This research work has been supported by the Spanish Ministry of Science and Innovation (MICINN, Projects CTM2008-06809CO2-01/02 and FPI grant BES-2009-023712) and the Spanish Ministry of Economy and Competitiveness (MINECO, Projects CTM2011-28595-0O2-01/02), jointly with the European Regional Development Fund (ERDF) and Generalitat Valenciana GVAACOMP2013/203, which are gratefully acknowledged.Robles Martínez, Á.; Ruano García, MV.; Ribes Bertomeu, J.; Seco Torrecillas, A.; Ferrer, J. (2014). Model-based automatic tuning of a filtration control system for submerged anaerobic membrane bioreactors (AnMBR). Journal of Membrane Science. 465:14-26. https://doi.org/10.1016/j.memsci.2014.04.012S142646

溶存酸素自動計測システムを用いる三槽式活性汚泥法の最適化と省エネルギー化

筑波大学 (University of Tsukuba)201