John B. Copp

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). This title belongs to Scientific and Technical Report Series ISBN: 9781780401171 (eBook) ISBN: 9781843391463 (Print)

An ASM/ADM model interface for dynamic plant-wide simulation

Mathematical modelling has proven to be very useful in process design, operation and optimisation. A recent trend in WWTP modelling is to include the different subunits in so-called plant-wide models rather than focusing on parts of the entire process. One example of a typical plant-wide model is the coupling of an upstream activated sludge plant (including primary settler, and secondary clarifier) to an anaerobic digester for sludge digestion. One of the key challenges when coupling these processes has been the definition of an interface between the well accepted activated sludge model (ASM1) and anaerobic digestion model (ADM1). Current characterisation and interface models have key limitations, the most critical of which is the over-use of X(c) (or lumped complex) variable as a main input to the ADM1. Over-use of X(c) does not allow for variation of degradability, carbon oxidation state or nitrogen content. In addition, achieving a target influent pH through the proper definition of the ionic system can be difficult. In this paper, we define an interface and characterisation model that maps degradable components directly to carbohydrates, proteins and lipids (and their soluble analogues), as well as organic acids, rather than using X(c). While this interface has been designed for use with the Benchmark Simulation Model No. 2 (BSM2), it is widely applicable to ADM1 input characterisation in general. We have demonstrated the model both hypothetically (BSM2), and practically on a full-scale anaerobic digester treating sewage sludge.

Benchmark simulation models, quo vadis?

As the work of the IWA Task Group on Benchmarking of Control Strategies for wastewater treatment plants (WWTPs) is coming to an end, it is essential to disseminate the knowledge gained. For this reason, all authors of the IWA Scientific and Technical Report on benchmarking have come together to provide their insights, highlighting areas where knowledge may still be deficient and where new opportunities are emerging, and to propose potential avenues for future development and application of the general benchmarking framework and its associated tools. The paper focuses on the topics of temporal and spatial extension, process modifications within the WWTP, the realism of models, control strategy extensions and the potential for new evaluation tools within the existing benchmark system. We find that there are major opportunities for application within all of these areas, either from existing work already being done within the context of the benchmarking simulation models (BSMs) or applicable work in the wider literature. Of key importance is increasing capability, usability and transparency of the BSM package while avoiding unnecessary complexity.

Estimation of the active nitrifying biomass in activated sludge

Abstract An in situ nitrifier mass estimation technique was developed to estimate the nitrifier population within an activated sludge sample using dominant cultures of nitrifying organisms. This technique was applied to activated sludge samples from the Milton, Ontario Wastewater Treatment Plant and the results were compared to nitrifier population estimates calculated using the IAWPRC (now IAWQ) Activated Sludge Model No. 1 (ASM1). Several sets of nitrification model parameters were used, including values calculated in this investigation from dominant cultures of nitrifier organisms as well as the ASM1 default estimates. The trends in active nitrifier population measured by the in situ mass estimation technique (MET) were predicted by the model simulations when the parameter estimates developed in this study were used. There was good agreement and no statistical difference existed between the model estimates and the experimentally determined masses. The current ASM1 default parameters did not predict the trends in the active population as measured by MET.

Instrumentation, control and automation in wastewater - From London 1973 to Narbonne 2013

Key developments of instrumentation, control and automation (ICA) applications in wastewater systems during the past 40 years are highlighted in this paper. From the first ICA conference in 1973 through to today there has been a tremendous increase in the understanding of the processes, instrumentation, computer systems and control theory. However, many developments have not been addressed here, such as sewer control, drinking water treatment and water distribution control. It is hoped that this review can stimulate new attempts to more effectively apply control and automation in water systems in the coming years.

Rethinking wastewater characterisation methods for activated sludge systems – a position paper

Increasingly stringent effluent limits and an expanding scope of model system boundaries beyond activated sludge has led to new modelling objectives and consequently to new and often more detailed modelling concepts. Nearly three decades after the publication of Activated Sludge Model No1 (ASM1), the authors believe it is time to re-evaluate wastewater characterisation procedures and targets. The present position paper gives a brief overview of state-of-the-art methods and discusses newly developed measurement techniques on a conceptual level. Potential future paths are presented including on-line instrumentation, promising measuring techniques, and mathematical solutions to fractionation problems. This is accompanied by a discussion on standardisation needs to increase modelling efficiency in our industry.

Simulation of respirometry-based detection and mitigation of activated sludge toxicity

This paper presents the results of an evaluation of a toxicity mitigation control strategy using the IWA simulation benchmark (Respirometry in control of the activated sludge process: benchmarking control strategies, IWA Scientific and Technical Report #11, IWA, London, England, 2002; The COST simulation benchmark: description and simulator manual, Office for Official Publications of the European Community, Luxembourg, 2001, 154pp). The aim of the proposed strategy is to minimise the impact of a toxic influent shock load on process performance. To do this, the strategy depends on a respiration rate measurement to detect toxic events and uses an equalisation tank to store toxic influent. A defined control algorithm specific for the benchmark plant was developed and controls the reintroduction of the stored influent back into the process stream once the influent is deemed non-toxic. Implemented into the benchmark-defined nitrifying configuration, the evaluation required several alterations to the simulation benchmark including three model changes, the addition of a soluble unbiodegradable toxic state variable and the development of two toxic influent files. The results of the simulations indicate that the impact of the toxicant can be significantly mitigated through the use of off-line storage and reintroduction of suspected influent.

Advanced monitoring of water systems using in situ measurement stations: data validation and fault detection

In situ continuous monitoring at high frequency is used to collect water quality information about water bodies. However, it is crucial that the collected data be evaluated and validated for the appropriate interpretation of the data so as to ensure that the monitoring programme is effective. Software tools for data quality assessment with a practical orientation are proposed. As water quality data often contain redundant information, multivariate methods can be used to detect correlations, pertinent information among variables and to identify multiple sensor faults. While principal component analysis can be used to reduce the dimensionality of the original variable data set, monitoring of some statistical metrics and their violation of confidence limits can be used to detect faulty or abnormal data and can help the user apply corrective action(s). The developed algorithms are illustrated with automated monitoring systems installed in an urban river and at the inlet of a wastewater treatment plant.

Benchmarking the Evaluation of Control Strategies in Wastewater Treatment: The Four-Year Story of the Cost Benchmark

Abstract Within the framework of two COST Actions, a benchmark for wastewater treatment defined as a simulation model of the plant, plant layout, influent load, controllers, performance criteria and test procedures, has been developed to compare new control strategies and promote their application. This text describes the rationale and the milestones of the benchmark, its present state and the forthcoming developments.

Towards the automation of water quality monitoring networks

The implementations of water quality monitoring networks have a number of inherent engineering challenges and the automation of the data collection and analysis only adds to that complexity. This paper has been written to discuss the challenges and solutions that have been developed within the framework of an industrial/academic partnership. Water quality monitoring stations are important tools in the area of environmental water science; however, traditional monitoring station installations and their maintenance tend to require more effort than desirable. Common sensors are not easily integrated into fieldbus systems and the lack of storable meta data (status, calibration information, location,…) available from sensor devices in this field, requires additional effort on the part of the owner if a fully utilizable database of meaningful values is to be constructed. An approach is proposed to automate this effort by providing an electronic catalog of predefined devices that can be input by the user during setup or read from the sensor in real-time. Automated data evaluation, alarm triggering and real-time data ‘correction’ are all being developed with an aim to create fully documented long-term databases of usable and meaningful water quality data. And finally, to initiate improvements in the area of monitoring automation, some thoughts on the future of advanced fieldbus systems are presented.