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Relationship between manual air valve positioning, water quality and energy usage in activated sludge processes
Abstract
Diffused aeration is the most implemented method for oxygen transfer in municipal activated sludge systems and governs the economics of the entire treatment process. Empirical observations are typically used to regulate airflow distribution through the adjustment of manual valves. However, due to the associated degrees of freedom, the identification of a combination of manual valves that optimizes all performance criteria is a complex task. For the first time a multi-criteria optimization algorithm was used to minimize effluent constituents and energy use by parametrizing manual valves positions. Data from a full-scale facility in conjunction with specific model assumptions were used to develop a base-case facility consisting of a detailed air supply model, a bio-kinetic model and a clarification model. Compared to the base-case condition, trade-offs analysis showed potential energy savings of up to 13.6% and improvement of effluent quality for NH4+ (up to 68.5%) and NOx (up to 81.6%). Based on two different tariff structures of a local power utility, maximum costs savings of 12800 USD mo-1 to 19000 USD mo-1 were estimated compared to baseline condition.
... The flow rate and the corresponding pressure drop over the control valve depend on the valve opening and flow characteristics, three of which are mainly used: linear, quick opening and equal percentage (Seborg et al. 2010). Positions of each zones control valves define the distribution of the airflow along the treatment lane and with the valve characteristics it is possible to estimate the redistribution of the airflow as a function of the valve openings (Reifsnyder et al. 2020). Regardless of the control strategy used, the valves will highly influence the systems performance and energy consumption. ...
... This, in combination of the biological model, could offer the possibility for model predictive control of the DO profile that, instead of using multiple individual control loops, could establish optimal set of valve positions which minimize the aeration, while maintaining the treatment performance. This approach could also be valid for WWTPs that use manually controlled valves and the model could be used for multi-objective optimization as was done in the study by Reifsnyder et al. (2020). ...
Energy costs in the wastewater industry are increasing due to increasing trends in electricity rates and more stringent requirements for effluent quality. Wastewater aeration process is typically the largest energy consumer of the treatment plant and the optimization of the aeration process can offer significant savings for the wastewater treatment plants (WWTPs). Utilization of dynamic models can offer optimization solutions for improving the energy efficiency and process performance. In this work a simplified modelling approach emphasizing the control valves and the blowers is tested by developing aeration system models for two Finnish WWTPs. The developed model requires calibration of only a single parameter and the results from the simulations showed that reasonable estimations of the aeration systems energy demand could be made with a limited knowledge on the details of the physical system. The promising results highlight the strong influence of the control valve positioning to the whole system and indicate that airflow distribution along the system could be estimated simply from the positioning of the valves. The presented modelling approach allows the comparison between different blower and control valve alternatives during operation and for the process upgrades and offers prospect for improving the aeration operation control strategies. HIGHLIGHTS
An aeration system model based on valve positions was developed.;
The model only requires calibration of one parameter.;
Energy consumption can be estimated with only a limited information about the physical aeration system.;
Valve positions impact the system power consumption and the air distribution between and within aeration grids.;
Including valve positions opens possibilities to improve the aeration control strategies.;
... Wastewater treatment plants (WWTPs) protect aqueous environments and help to ensure adequate sanitation of normal human life in modern cities. In response to progressively stringent national and local government regulations on wastewater treatment, energy consumption thresholds, and resource recovery mandates [1][2][3]. To ensure the stable operation, WWTPs encounter challenges stemming from significant influent fluctuations and the inherent complexity of nonlinear treatment processes [4]. ...
Activated sludge models are increasingly being adopted to guide the operation of wastewater treatment plants. Chemical oxygen demand (COD) is an indispensable input for such models. To ensure that the activated sludge mathematical model can adapt to various water quality conditions and minimize prediction errors, it is essential to predict the parameters of the COD components in real-time based on the actual influent COD concentrations. However, conventional methods of determining the components' contributions are too intricate and time-consuming to be really useful. In this study, the chemical oxygen demand in the actual waste water treatment plant was disassembled and analyzed. The research involved determining the proportions of each COD component, assessing the reliability of the measurement parameters, and examining potential factors affecting measurement accuracy, including weather conditions, pipeline conditions, and residents' habits. Then, a backpropagation neural network was developed which can deliver real-time predictions for five important contributors to COD in real time. In addition, using the receiver operating characteristics curve and prediction accuracy to evaluate the performance of the prediction model. For all five components, which SS, XS, SI, XA, and XH, the prediction accuracy of model was more than 80 %. The maximum deviation values of these parameters fall within the range of the actual detected values, suggesting that the model's predictions align well with real-world observations, and demonstrated prediction performance adequate for practical application in wastewater treatment. This article can provide research basis for the engineering application of activated sludge model and help for the intelligent upgrading of waste water treatment plants.
... There is now a range of well established modelling approaches for the active sludge processes, such as the removal of micropollutants [11]. Recent applications of the ASM1 model include investigating the energy demands of a wastewater treatment plant [12,13] and to test a proposed algorithm to identify faulty ammonium detectors being used to control the operation of a wastewater treatment plant [14]. Variations on the ASM1 are still being developed, for example to include direct endogenous respiration [15]. ...
We develop and investigate a model for sludge production in the activated sludge process when a biological reactor is coupled to a sludge disintegration unit (SDU). The model for the biological reactor is a slimmed down version of the activated sludge model 1 in which only processes related to carbon are retained. Consequently, the death-regeneration concept is included in our model which is an improvement on almost all previous models. This provides an improved representation of the total suspended solids in the biological reactor, which is the key parameter of interest. We investigate the steady-state behaviour of this system as a function of the residence time within the biological reactor and as a function of parameters associated with the operation of the SDU. A key parameter is the sludge disintegration factor. As this parameter is increased the concentration of total suspended solids within the biological reactor decreases at the expense increasing the chemical oxygen demand in the effluent stream. The existence of a maximum acceptable chemical oxygen demand in the effluent stream therefore imposes a maximum achievable reduction in the total suspended solids. This paper improves our theoretical understanding of the utility of sludge disintegration as a means to reduce excess sludge formation. As an aside to the main thrust of our paper we investigate the common assumption that the sludge disintegration processes occur on a much shorter timescale than the biological processes. We show that the disintegration processes must be exceptional slow before the inclusion of the biological processes becomes important.
... Wastewater treatment plants (WWTPs) are an important part of urban water infrastructure in pollutant reduction and public health protection. Currently WWTPs are facing increasingly stringent requirements on effluent quality, energy consumption, and resource recycling [1][2][3][4][5]. To meet these requirements, mathematical models have increasingly been employed to predict the efficiency of the WWTP and then provide suitable operation strategies, by establishing a quantitative response of WWTP influent parameters to effluent water quality. ...
To provide real-time prediction of wastewater treatment plant (WWTP) effluent water quality, a machine learning (ML) model was developed by combining an improved feedforward neural network (IFFNN) with an optimization algorithm. Data used as input variables of the IFFNN included hourly influent water quality parameters, influent flow rate and WWTP process monitoring and operational parameters. Additionally, input variables included historical effluent water quality parameters for future prediction. The model was demonstrated in a WWTP in Jiangsu Province, China, where prediction of effluent chemical oxygen demand (COD) and total nitrogen (TN) with large variations were tested. Relative to the traditional feedforward neural network (FFNN) model without considering historical effluent water quality parameter input, the IFFNN enhanced prediction performance by 52.3% (COD) and 72.6% (TN) based on the mean absolute percentage errors of test datasets, after its model structure was optimized with a genetic algorithm (GA). The problem of over-fitting could also be overcome through the use of the IFFNN, with the determination of coefficient increased from 0.20 to 0.76 for test datasets of effluent COD. The GA-IFFNN model, which was efficient in capturing complex non-linear relationships and extrapolation, could be a useful tool for real-time direction of regulatory changes in WWTP operations.
... The inclusion of aeration dynamics on process optimization has been largely overlooked . The integration of daily and seasonal oxygen transfer fluctuations can improve performance diagnostics (i.e., over-aeration and imbalanced flows) (Jiang et al., 2017;Reifsnyder et al., 2020;Schraa et al., 2017). Moreover, energy costs can vary significantly depending on plant size, location, time of the day, season, and so on, and so a detailed description of the site-specific tariffstructures is fundamental to perform accurate economic evaluations (Aymerich et al., 2015). ...
Aeration systems often lack the efficiency to maintain a desired residual dissolved oxygen (DO) concentration in the tank in part because little consideration is given to the dynamic daily and seasonal loading conditions. Although advanced aeration controllers exist, the majority of plants have DO set points typically based on common practice and literature values rather than site‐specific conditions, which can result in DO set points higher than those necessary to meet treatment objectives. DO set point reduction strategies have primarily been proposed through either static or dynamic simulations. In this study, the substantial improvements associated with DO set point reduction are demonstrated at full scale. A yearlong characterization of full‐scale aeration dynamics captured the effect of diurnal and seasonal fluctuations on oxygen transfer and energy demand and so facilitated the estimation of the potential savings of DO reduction strategies. Full‐scale validation provided direct evidence of DO reduction strategies inducing an overall enhancement of oxygen transfer efficiency along the different bioreactors, while confirming that energy savings as high as 20% were feasible. This study quantifies the influence of oxygen transfer efficiency on operating choices and site‐specific conditions (control strategy, loading conditions, and influent flow variability).
Practitioner points
We quantified the energy reduction and cost savings associated with a DO reduction in an aeration tank.
For each 0.2 mg/L of DO decreased, the average power demand reduction per unit water treated exceeded 17%.
Field measurements of dynamic alpha values eliminate the uncertainty in estimating aeration energy and cost savings from DO variations.
The installation of satellite water resource recovery facilities (WRRFs) has strengthened the ability to provide cheap and reliable recycled water to meet the increasing water demand of expanding cities. As a result, recent studies have attempted to address the problem of how to optimally integrate satellite systems with other sectors of the urban sphere, such as the local economy, the power supply, and the regional carbon footprint. However, such studies are merely based on the spatial domain, thus neglecting potential time-dependent strategies that could further improve the sustainability of metropolitan water systems. Therefore, in this study a new conceptual framework is proposed for the dynamic management of hybrid systems comprised of both centralized and satellite WRRFs. Furthermore, a novel set of integrated real-time control (RTC) strategies are considered to analyse three different scenarios: 1) demand response, 2) flow equalization of the centralized WRRF and 3) reduction of greenhouse gas emissions. Data from a case study in California is used to develop an integrated dynamic model of a system of 8 facilities. Our results show that by dynamically shifting the dry-weather influent wastewater flows between hydraulically connected WRRFs, a reduction in power demand (up to 25%), energy use (4%), operating costs (8.5%) and indirect carbon emissions (4.5%) can be achieved. Therefore, this study suggests that a certain degree of hydraulic interconnection coupled with dynamic load-shifting strategies, can broaden the operational flexibility and overall sustainability of hybrid WRRF systems.
This paper introduces the application of a fully dynamic air distribution model integrated with a biokinetic process model and a detailed process control model. By using a fully dynamic air distribution model, it is possible to understand the relationships between aeration equipment, control algorithms, process performance, and energy consumption, thus leading to a significantly more realistic prediction of water resource recovery facility (WRRF) performance. Consequently, this leads to an improved design of aeration control strategies and equipment. A model-based audit has been performed for the Girona WRRF with the goal of providing a more objective evaluation of energy reduction strategies. Currently, the Girona plant uses dissolved oxygen control and has been manually optimised for energy consumption. Results from a detailed integrated model show that the implementation of an ammonia-based aeration controller, a redistribution of the diffusers, and the installation of a smaller blower lead to energy savings between 12 and 21%, depending on wastewater temperature. The model supported the development of control strategies that counter the effects of current equipment limitations, such as tapered diffuser distribution, or over-sized blowers. The latter causes an intermittent aeration pattern with blowers switching on and off, increasing wear of the equipment.
Aeration accounts for a large fraction of energy consumption at conventional water reclamation plants (WRPs). Older plants were designed when control techniques were relatively primitive and energy consumption was less of a concern. As a result, although process operations at older WRPs can satisfy effluent permit requirements, they can operate with excess aeration. In this study, we developed a wastewater process model to evaluate possible aeration savings at the Metropolitan Water Reclamation District of Greater Chicago Calumet WRP, one of the oldest plants in Chicago. Based on subsets of influent characteristics, we identified eight steady-state scenarios. We also identified transient scenarios that included high probability perturbations and more challenging but lower probability conditions. Results indicate that the Calumet WRP frequently operates with excess aeration. Effluent D.O. is the limiting parameter with respect to aeration saving and permit requirements. In a typical storm event, aeration could be reduced by up to 50%; even under low probability, challenging perturbations, aeration can be decreased by 35% from current average levels and all permit requirements can be satisfied. Annual cost savings from cutting the aeration by 35% could be more than $1.2 M.
Rapid and important developments in the area of energy - water nexus over the last two to three years have been significant. This new edition of Water and Energy: Threats and Opportunities is timely and continues to highlight the inextricable link between water and energy, providing an up-to-date overview of the subject with helpful detailed summaries of the technical literature.
Water and Energy has been up-dated throughout and major changes are: new chapters on global warming and fossil fuels, including shale gas and fracking.the consequences of the Deepwater Horizon accident in the Mexican Gulf and the Niger Delta oil spills.New developments in hydropowercontinued competition between food, water and energy
Water and Energy Threats and Opportunities, 2e creates an awareness of the important couplings between water and energy. It shows how energy is used in all the various water cycle operations and demonstrates how water is used and misused in all kinds of energy production and generation.Population increase, climate change and an increasing competition between food and fuel production create enormous pressures on both water and energy availability. Since there is no replacement for water, water security looks more crucial than energy security. This is true not only in developing countries but also in the most advanced countries. For example, the western parts of the USA suffer from water scarcity that provides a real security threat.
Part One of the book describes the water-energy nexus, the conflicts and competitions and the couplings between water security, energy security, and food security.
Part Two captures how climate change, population increase and the growing food demand will have major impact on water availability in many countries in the world.
Part Three describes water for energy and how energy production and conversion depend on water availability. As a consequence, all planning has to take both water and energy into consideration. The environmental (including water) consequences of oil and coal exploration and refining are huge, in North America as well as in the rest of the world. Furthermore, oil leak accidents have hit America, Africa, Europe as well as Asia. The consequences of hydropower are discussed and the competition between hydropower generation, flood control and water storage is illustrated. The importance of water for cooling thermal power plants is described, as this was so tragically demonstrated at the Fukushima nuclear plants in 2011. Climate change will further emphasize the strong coupling between water availability and the operation of power plants.
Part Four analyses energy for water - how water production and treatment depend on energy. The book shows that a lot can be done to improve equipment, develop processes and apply advanced monitoring and control to save energy for water operations. Significant amounts of energy can be saved by better pumping, the reduction of leakages, controlled aeration in biological wastewater treatment, more efficient biogas production, and by improved desalination processes.
There are 3 PowerPoint presentations available for Water and Energy - threats and opportunities, 2e.
ISBN: 9781780406947 (eBook)
ISBN: 9781780406930 (Print)
Activated sludge systems have been applied for 100 years now. Over the course of the years,
researchers have developed various models to describe activated sludge processes. The main aim
has been to gain a better understanding of the conditions that favour the conversions of carbon,
nitrogen and phosphorus present in wastewater, and associated oxygen consumption and sludge
production. The current paper presents a reflection on the historical developments, state-of-the-art
of activated sludge modelling and future trends. Over the years, many wastewater research groups
have benefitted greatly from the development of activated sludge models (ASMs). On one hand,
modelling has been expanded through the development of novel theoretical concepts and their
application in new fields. On the other hand, models have been used for practical projects. Although,
scientists are still searching for the ideal model, one can say that ASMs are developed to the extent
that they can be applied in practice with confidence. New developments are expected to be seen
regarding plant-wide modelling, integration with other models at the (urban) system level,
organizational and computational infrastructure, and interface and communication with various
stakeholders and users.
This paper makes a critical review of the available techniques for analysing, completing and generating influent data for WWTP modelling. The solutions found in literature are classified according to three different situations from engineering practice: 1) completing an incomplete dataset about the quantity and quality of the influent wastewater; 2) translating the common quality measurements (COD, TSS, TKN, etc.) into the ASM family components (fractionation problem); 3) characterising the uncertainty in the quality and quantity of the influent wastewater. In the first case (Situation 1), generators based on Fourier models are very useful to describe the daily and weekly wastewater patterns. Another specially promising solution is related to the construction of phenomenological models that provide wastewater influent profiles in accordance with data about the catchment properties (number of inhabitant equivalents, sewer network, type of industries, rainfall and temperature profiles, etc.). This option has the advantage that using hypothetical catchment characteristics (other climate, sewer network, etc.) the modeller is able to extrapolate and generate influent data for WWTPs in other scenarios. With a much lower modelling effort, the generators based on the use of databases can provide realistic influent profiles based on the patterns observed. With regard to the influent characterisation (Situation 2), the WWTP modelling protocols summarise well established methodologies to translate the common measurements (COD, TSS, TKN, etc.) into ASM family components. Finally, some statistical models based on autoregressive functions are suitable to represent the uncertainty involved in influent data profiles (Situation 3). However, more fundamental research should be carried out to model the uncertainty involved in the underlying mechanisms related to the wastewater generation (rainfall profiles, household and industries pollutant discharges, assumed daily and weekly patterns, etc.). (C) 2014 Published by Elsevier Ltd.
Aeration control at wastewater treatment plants based on ammonia as the controlled variable is applied for one of two reasons: (1) to reduce aeration costs, or (2) to reduce peaks in effluent ammonia. Aeration limitation has proven to result in significant energy savings, may reduce external carbon addition, and can improve denitrification and biological phosphorus (bio-P) performance. Ammonia control for limiting aeration has been based mainly on feedback control to constrain complete nitrification by maintaining approximately one to two milligrams of nitrogen per liter of ammonia in the effluent. Increased attention has been given to feedforward ammonia control, where aeration control is based on monitoring influent ammonia load. Typically, the intent is to anticipate the impact of sudden load changes, and thereby reduce effluent ammonia peaks. This paper evaluates the fundamentals of ammonia control with a primary focus on feedforward control concepts. A case study discussion is presented that reviews different ammonia-based control approaches. In most instances, feedback control meets the objectives for both aeration limitation and containment of effluent ammonia peaks. Feedforward control, applied specifically for switching aeration on or off in swing zones, can be beneficial when the plant encounters particularly unusual influent disturbances.
This review covers automatic control of continuous aeration systems in municipal wastewater treatment plants. The review focuses on published research in the 21st century and describes research into various methods to decide and control the dissolved oxygen (DO) concentration and to control the aerobic volume with special focus on plants with nitrogen removal. Important aspects of control system implementation and success are discussed, together with a critical review of published research on the topic. With respect to DO control and determination, the strategies used for control span from modifications and developments of conventional control methods which have been explored since the 1970s, to advanced control such as model-based predictive and optimal controllers. The review is supplemented with a summary of comparisons between control strategies evaluated in full-scale, pilot-scale and in simulations.
Aeration consumes about 60% of the total energy use of
a wastewater treatment plant (WWTP) and therefore is a major
contributor to its carbon footprint. Introducing advanced process
control can help plants to reduce their carbon footprint and at the
same time improve effluent quality through making available unused
capacity for denitrification, if the ammonia concentration is below
a certain set-point. Monitoring and control concepts are cost-saving
alternatives to the extension of reactor volume. However, they also
involve the risk of violation of the effluent limits due to measuring errors,
unsuitable control concepts or inadequate implementation of the
monitoring and control system. Dynamic simulation is a suitable tool
to analyze the plant and to design tailored measuring and control
systems. During this work, extensive data collection, modeling and fullscale
implementation of aeration control algorithms were carried out at
three conventional activated sludge plants with fixed pre-denitrification
and nitrification reactor zones. Full-scale energy savings in the range of
16–20% could be achieved together with an increase of total nitrogen
removal of 40%.
Surface water environment in China was degraded rapidly in the last two decades, resulting in increasingly tighten criteria issued for municipal wastewater treatment plants (WWTPs). This paper reviewed the recent advances of process design and operational optimization for nutrients removal. Three major processes, as anaerobic-anoxic-oxic (AAO) process, oxidation ditch (OD), and sequencing batch reactor (SBR) occupied 65% of WWTPs amounts and 54% of treatment volumes of China in 2006. However conservative process designs and operational faults often impaired the process performances and energy efficiency. Therefore, typical processes were modified, combined, and innovated to meet the requirements of the diverse influent characteristics and lower energy consumptions. Furthermore, operational optimization techniques by modeling, simulation, and real-time control were also developed and applied in China to improve the process operation. Although great efforts had been contributed to improve the WWTPs performances in China, attentions should be continuously paid to the introduction, instruction, and implementation of advanced techniques. At last, the technical demands and appropriated techniques of WWTPs in China were briefly discussed.
Aeration is the most energy intensive unit operation in municipal wastewater treatment, and fine-pore diffusers have been widely used to minimize power consumption. Unfortunately, fine-pore diffusers suffer from fouling and scaling problems, which cause a rapid decline in aeration performance and significant increase in power consumption. Diffusers must be cleaned periodically to reduce energy costs. The cleaning frequency of diffusers is site-specific and its effectiveness can be evaluated with oxygen transfer efficiency (OTE) testing. Off-gas testing is the best technique for measuring OTE in real-time. Fine-pore diffusers have low a factors that are further reduced at high loading rate. A time-series of off-gas measurements were conducted to demonstrate the value of real-time OTE data for developing energy-conserving operating strategies. The observations confirm the inverse correlation between OTE and airflow rate as well as the economic benefits of diffuser cleaning. In addition, mathematic models were applied to simulate the transient oxygen uptake rate (OUR) and show the impact of varying load on OTE and aeration cost, especially when faced with time-of-day power rates. Regular diffuser cleaning can reduce average power costs by 18% and various equalization alternatives can reduce power costs by 6 to 16%.
A detailed analysis of different types of gravity distribution devices, designed to split on-site wastewater effluent equally between percolation trenches, has been carried out both in the laboratory and also in the field under realistic loading conditions. Five different types of distribution device have been compared: a V-notch distribution box, stilling chamber box, T-splitters with and without baffles and tipping bucket device. The trials carried out in the laboratory with clean water showed that flow distribution for all devices was sensitive to both the off-level installation angles and variable flow rates, with the most stable performance achieved using the T-splitters with baffles and tipping bucket devices. In parallel to this, the on-site flow regime experienced at two sites was continuously monitored using a tipping bucket and data-logger over eighteen month periods, finding that the most common flow rates at the distribution unit were in the range of 0.1-2.5 L/min. The on-site performance of these devices receiving both septic tank and secondary treated effluent showed that significant solid deposition and biofilm development had severely affected the equal distribution between the trenches, hence highlighting the need for regular maintenance to ensure efficient performance over time after installation.
As the largest single energy-consuming component in most biological wastewater treatment systems, control of aeration is of great interest seen from an energy savings point of view. This paper suggests a simple way of using on-line ammonium measurements to control aeration in a pre-denitrification plant by controlling the dissolved oxygen setpoint. The controller works primarily by feed-forward based on an ammonium sensor located at the head of the aerobic process part. Using online in-situ sensor measurements directly from the process have the important advantage over effluent measurements that there is no or very short time delay for information. The controller has been implemented in a full-scale wastewater treatment plant for a period of 35 days. During the experiment two identical activated sludge lines were used. The controller was implemented in one line, while the other line worked as a reference for comparison. The preliminary results indicate that the described control strategy leads to energy savings for the aeration in the region of 5-15%, while maintaining approximately the same effluent quality as in the reference line. Even higher energy savings can probably be achieved by optimising the controller. An automatic procedure for updating the controller parameters based on dynamic effluent ammonium measurement has been tested.
A guideline for simulation studies of wastewater treatment plants is proposed. The aim of the HSG-guideline is to define a reference quality level that helps to make the results of simulation studies comprehensible and comparable and therefore increases the quality and reliability of mathematical modelling in wastewater treatment. The paper gives a summary of the HSG-guideline, written by a group of university members from Germany, Austria and Switzerland.
This paper discusses a methodology to estimate the costs and benefits of advanced control for wastewater treatment plants. The methodology has been applied to four wastewater treatment plants, representing four standard types of plants built in Flanders, Belgium. The paper outlines the methodology and illustrated results from one of the four design cases. General results are shown and contrasted with full-scale experience. The methodology appears to give realistic results and will be used for further refinement of default control algorithms for certain types of plants. A preliminary analysis indicates that on-line control can become cost-effective for plant sizes above 50,000 population equivalents.
In the last few decades, evolutionary algorithms have emerged as a revolutionary approach for solving search and optimization problems involving multiple conflicting objectives. Beyond their ability to search intractably large spaces for multiple solutions, these algorithms are able to maintain a diverse population of solutions and exploit similarities of solutions by recombination. However, existing theory and numerical experiments have demonstrated that it is impossible to develop a single algorithm for population evolution that is always efficient for a diverse set of optimization problems. Here we show that significant improvements in the efficiency of evolutionary search can be achieved by running multiple optimization algorithms simultaneously using new concepts of global information sharing and genetically adaptive offspring creation. We call this approach a multialgorithm, genetically adaptive multiobjective, or AMALGAM, method, to evoke the image of a procedure that merges the strengths of different optimization algorithms. Benchmark results using a set of well known multiobjective test problems show that AMALGAM approaches a factor of 10 improvement over current optimization algorithms for the more complex, higher dimensional problems. The AMALGAM method provides new opportunities for solving previously intractable optimization problems.
A model was developed for a water resources recovery facility (WRRF) activated sludge process (ASP) in Modified Ludzack-Ettinger (MLE) configuration. Amplification of air requirements and its associated energy consumptions were observed as a result of concurrent circadian variations in ASP influent flow and carbonaceous/nitrogenous constituent concentrations. The indirect carbon emissions associated with the ASP aeration were further amplified due to the simultaneous variations in carbon emissions intensity (kgCO2,eq(kWh)-1) and electricity consumption (kWh). The ratio of peak to minimum increased to 3.4 (for flow), 4.2 (for air flow and energy consumption), and 5.2 (for indirect CO2,eq emission), which is indicative of strong amplification. Similarly, the energy costs for ASP aeration were further increased due to the concurrency of peak energy consumptions and power demands with time of use peak electricity rates. A comparison between the results of the equilibrium model and observed data from the benchmark WRRF demonstrated under- and over-aeration attributed to the circadian variation in air requirements and limitations associated with the aeration system specification and design.
During the design of a water resource recovery facility (WRRF), it is becoming industry practice for process engineers to use simulation software to assist with the design of the plant and its aeration system. The aeration process is one of the key components of the activated sludge process, and as such, is one of the most important aspects of modeling wastewater treatment systems. A comprehensive aeration system model has been developed in SIMBA# that can model both the air supply and demand. The model includes sub-models for centrifugal and positive displacement blowers, pipes and fittings, valves, and diffusers. Both compressible and incompressible flow can be modelled. Oxygen transfer within aeration tanks is also included as part of the overall model. The aeration system model allows engineers to analyze aeration systems as a whole to determine biological air requirements, blower performance, air distribution, control valve impacts, and controller design and tuning. This will allow more detailed system-wide testing before commissioning.
During the design of a water resource recovery facility, it is becoming industry practice to use simulation software to assist with process design. Aeration is one of the key components of the activated sludge process, and is one of the most important aspects of modelling wastewater treatment systems. However, aeration systems are typically not modelled in detail in most wastewater treatment process modelling studies. A comprehensive dynamic aeration system model has been developed that captures both air supply and demand. The model includes sub-models for blowers, pipes, fittings, and valves. An extended diffuser model predicts both oxygen transfer efficiency within an aeration basin and pressure drop across the diffusers. The aeration system model allows engineers to analyse aeration systems as a whole to determine biological air requirements, blower performance, air distribution, control valve impacts, controller design and tuning, and energy costs. This enables engineers to trouble-shoot the entire aeration system including process, equipment and controls. It also allows much more realistic design of these highly complex systems.
Aeration is an essential component of aerobic biological wastewater treatment and is the largest energy consumer at most water resource recovery facilities. Most modelling studies neglect the inherent complexity of the aeration systems used. Typically, the blowers, air piping, and diffusers are not modelled in detail, completely mixed reactors in a series are used to represent plug-flow reactors, and empirical correlations are used to describe the impact of operating conditions on bubble formation and transport, and oxygen transfer from the bubbles to the bulk liquid. However, the mechanisms involved are very complex in nature and require significant research efforts. This contribution highlights why and where there is a need for more detail in the different aspects of the aeration system and compiles recent efforts to develop physical models of the entire aeration system (blower, valves, air piping and diffusers), as well as adding rigour to the oxygen transfer efficiency modelling (impact of viscosity, bubble size distribution, shear and hydrodynamics). As a result of these model extensions, more realistic predictions of dissolved oxygen profiles and energy consumption have been achieved. Finally, the current needs for further model development are highlighted.
The present paper describes a study on the feasibility of coupling rigorous dynamic modelling (DM) and its extended boundaries through life cycle assessment (LCA) with an efficient multi-objective optimization (EMOO) tool. The combined framework (DM-LCA-EMOO) was then applied to a real-world dynamic system: the wastewater treatment. To give a global view of all environmental, economic and technological performance, three objectives were considered: Effluent Quality Index (EQI), Operational Cost Index (OCI) and environmental impacts quantified through Life Cycle Impact Assessment (LCIA). Legally imposed constraints, including total nitrogen, total phosphorus, total chemical oxygen demand, total suspended solids and ammonium ion were also taken into account. Given the contradictory nature of objectives, the presence of constraints and the time-consuming simulation-based calculations, an efficient multi-objective optimization framework, namely Archive-based Multi-Objective Evolutionary Algorithm with Memory-based Adaptive Partitioning of search space (AMOEA-MAP) was used. The practicality of such a combined DM-LCA-EMOO tool for the evaluation of wastewater management and treatment was then addressed and demonstrated through a case application.
In response to strong growth in energy intensive wastewater treatment, public agencies and industry began to explore and implement measures to ensure achievement of the targets indicated in the 2020 Climate and Energy Package. However, in the absence of fundamental and globally recognized approach evaluating wastewater treatment plant (WWTP) energy performance, these policies could be economically wasteful. This paper gives an overview of the literature of WWTP energy-use performance and of the state of the art methods for energy benchmarking. The literature review revealed three main benchmarking approaches: normalization, statistical techniques and programming techniques, and advantages and disadvantages were identified for each one. While these methods can be used for comparison, the diagnosis of the energy performance remains an unsolved issue. Besides, a large dataset of WWTP energy consumption data, together with the methods for synthesizing the information, are presented and discussed. It was found that no single key performance indicators (KPIs) used to characterize the energy performance could be used universally. The assessment of a large data sample provided some evidence about the effect of the plant size, dilution factor and flowrate. The technology choice, plant layout and country of location were seen as important elements that contributed to the large variability observed.
At wastewater treatment plants (WWTPs) aeration is the largest energy consumer. This high energy consumption requires an accurate assessment in viewof plant optimization. Despite the ever increasing detail in processmodels, models for energy production still lack detail to enable a global optimization of WWTPs.Anewdynamicmodel for amore accurate predictionof aerationenergy costs inactivated sludge systems, equipped with submerged air distributing diffusers (producing coarse or fine bubbles) connected via piping to blowers, has been developed and demonstrated. This paper addresses themodel structure, its calibration and application to theWWTP ofMekolalde (Spain). The newmodel proved to give anaccurate predictionof the real energy consumptionby the blowers and captures the trendsbetter than the constant average power consumption models currently being used. This enhanced prediction of energy peak demand, which dominates the price setting of energy, illustrates that the dynamic model is preferably used in multi-criteria optimization exercises for minimizing the energy consumption.
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 autonomous.
Through a specific 'demand-side management' strategy known as the energy unit, both electric utilities and waste-water treatment plants could reap huge savings. With this, utilities are able to avoid the expense of planning, permitting, and constructing large new power-generation facilities, while wastewater facilities can identify ways to slice their energy use. In fact, for wastewater plants that are already on-line, an energy audit and subsequent retrofit may be the best way to reduce energy consumption.
The objective of this paper is to demonstrate the importance of incorporating more realistic energy cost models (based on current energy tariff structures) into existing water resource recovery facilities (WRRFs) process models when evaluating technologies and cost-saving control strategies. In this paper, we first introduce a systematic framework to model energy usage at WRRFs and a generalized structure to describe energy tariffs including the most common billing terms. Secondly, this paper introduces a detailed energy cost model based on a Spanish energy tariff structure coupled with a WRRF process model to evaluate several control strategies and provide insights into the selection of the contracted power structure. The results for a 1-year evaluation on a 115,000 population-equivalent WRRF showed monthly cost differences ranging from 7 to 30% when comparing the detailed energy cost model to an average energy price. The evaluation of different aeration control strategies also showed that using average energy prices and neglecting energy tariff structures may lead to biased conclusions when selecting operating strategies or comparing technologies or equipment. The proposed framework demonstrated that for cost minimization, control strategies should be paired with a specific optimal contracted power. Hence, the design of operational and control strategies must take into account the local energy tariff.
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This study investigates the potential of control strategy optimisation for the reduction of operational greenhouse gas emissions from wastewater treatment in a cost-effective manner, and demonstrates that significant improvements can be realised. A multi-objective evolutionary algorithm, NSGA-II, is used to derive sets of Pareto optimal operational and control parameter values for an activated sludge wastewater treatment plant, with objectives including minimisation of greenhouse gas emissions, operational costs and effluent pollutant concentrations, subject to legislative compliance. Different problem formulations are explored, to identify the most effective approach to emissions reduction, and the sets of optimal solutions enable identification of trade-offs between conflicting objectives. It is found that multi-objective optimisation can facilitate a significant reduction in greenhouse gas emissions without the need for plant redesign or modification of the control strategy layout, but there are trade-offs to consider: most importantly, if operational costs are not to be increased, reduction of greenhouse gas emissions is likely to incur an increase in effluent ammonia and total nitrogen concentrations. Design of control strategies for a high effluent quality and low costs alone is likely to result in an inadvertent increase in greenhouse gas emissions, so it is of key importance that effects on emissions are considered in control strategy development and optimisation.
Wastewater treatment plant design and operation involve multiple objective functions, which are often in conflict with each other. Traditional optimization tools convert all objective functions to a single objective optimization problem (usually minimization of a total cost function by using weights for the objective functions), hiding the interdependencies between different objective functions. We present an interactive approach that is able to handle multiple objective functions simultaneously. As an illustration of our approach, we consider a case study of plant-wide operational optimization where we apply an interactive optimization tool. In this tool, a commercial wastewater treatment simulation software is combined with an interactive multiobjective optimization software, providing an entirely new approach in wastewater treatment. We compare our approach to a traditional approach by solving the case study also as a single objective optimization problem to demonstrate the advantages of interactive multiobjective optimization in wastewater treatment plant design and operation.
In 1983 IAWPRC formed a task group to facilitate the application of practical models to the design and operation of biological wastewater treatment systems. This paper presents an outline of the model developed for single-sludge system performing carbon oxidation, nitrification and denitrification. The model includes seven fundamental processes: aerobic growth of heterotrophic biomass, anoxic growth of heterotrophic biomass, aerobic growth of autotrophic biomass, decay of heterotrophic biomass, decay of autotrophic biomass, hydrolysis or entrapped particulate organic matter, and hydrolysis of entrapped organic nitrogen. The model is presented in the form of a matrix which utilized stoichiometric coefficients to couple the components in the model with the process rate expressions acting upon them.
Application of instrumentation, control and automation (ICA) is a reasonable way to improve the operation of wastewater treatment plant (WWTP), which has been realized in China but is still underway. A survey was carried out in Taihu Lake basin to investigate the current situation of ICA application. The survey focuses on control variable monitoring, instrument maintenance, control strategies, control manners and facility types. Survey results show that the process variables have not been adequately monitored and used for process control. The instruments are lack of sufficient maintenance, which causes control systems unreliable or left unused. Set-point control strategies are widely adopted and implemented mainly relies on manual on-site manners. On/off controllers predominate in treatment units. The survey results can be used as a reference to understand and help increase the ICA levels in WWTPs of China.
Because the aeration system in an activated sludge wastewater treatment plant typically represents more than 50% of total plant energy requirements, designers and operators can substantially reduce overall plant energy costs by using accurate oxygen transfer information to make the aeration system as energy efficient as possible.
This paper presents data from 65 off‐gas analysis tests performed at 21 wastewater treatment plants. The effect of various factors on oxygen transfer was evaluated by comparing pairs of tests in which all factors but one were held relatively constant. Factors evaluated were diffuser type, diffuser layout, diffuser age, solids retention time, and level of nitrification. Flexible membrane diffusers had more than a 30% higher oxygen transfer efficiency than coarse bubble diffusers. Grid layouts had higher oxygen transfer efficiencies than spiral roll layouts. Flexible membrane diffusers that were 3.5 years old had a 20% lower oxygen transfer efficiency than new flexible membrane diffusers. Systems at low solids retention times that were not nitrifying had lower oxygen transfer efficiencies than nitrifying systems at high solids retention times. For some wastewater systems, use of this information on solids retention time in plant design and operation can decrease overall energy costs despite the additional oxygen required to meet the nitrogenous oxygen demand.
A dynamic model of the clarification-thickening process is presented. Based on the solids flux concept and on a mass balance around each layer of a one-dimensional settler, this model can simulate the solids profile throughout the settling column, including the underflow and effluent suspended solids concentrations under steady-state and dynamic conditions. The model makes use of a special settling velocity equation designed to simulate the settling velocity of dilute and more concentrated suspensions. The model can be applied to both primary and secondary settlers to simulate dynamic and steady-state conditions. Examples based on full-scale and pilot-scale experimental data taken from the literature serve to illustrate the application of the model to secondary settlers. Results of the analysis confirm that the model can serve to predict the effluent and underflow suspended solids concentrations under a variety of conditions.
This review paper focuses on modelling of wastewater treatment plants (WWTP). White-box modelling is widely applied in this field, with learning, design and process optimisation as the main applications. The introduction of the ASM model family by the IWA task group was of great importance, providing researchers and practitioners with a standardised set of basis models. This paper introduces the nowadays most frequently used white-box models for description of biological nitrogen and phosphorus removal activated sludge processes. These models are mainly applicable to municipal wastewater systems, but can be adapted easily to specific situations such as the presence of industrial wastewater. Some of the main model assumptions are highlighted, and their implications for practical model application are discussed. A step-wise procedure leads from the model purpose definition to a calibrated WWTP model. Important steps in the procedure are: model purpose definition, model selection, data collection, data reconciliation, calibration of the model parameters and model unfalsification. The model purpose, defined at the beginning of the procedure, influences the model selection, the data collection and the model calibration. In the model calibration a process engineering approach, i.e. based on understanding of the process and the model structure, is needed. A calibrated WWTP model, the result of an iterative procedure, can usually be obtained by only modifying few model parameters, using the default parameter sets as a starting point. Black-box, stochastic grey-box and hybrid models are useful in WWTP applications for prediction of the influent load, for estimation of biomass activities and effluent quality parameters. These modelling methodologies thus complement the process knowledge included in white-box models with predictions based on data in areas where the white-box model assumptions are not valid or where white-box models do not provide accurate predictions. Artificial intelligence (AI) covers a large spectrum of methods, and many of them have been applied in applications related to WWTPs. AI methodologies and white-box models can interact in many ways; supervisory control systems for WWTPs are one evident application. Modular agent-based systems combining several AI and modelling methods provide a great potential. In these systems, AI methods on one hand can maximise the knowledge extracted from data and operator experience, and subsequently apply this knowledge to improve WWTP control. White-box models on the other hand allow evaluating scenarios based on the available process knowledge about the WWTP. A white-box model calibration tool, an AI based WWTP design tool and a knowledge representation tool in the WWTP domain are other potential applications where fruitful interactions between AI methods and white-box models could be developed.
The aim of this work was the improvement of a WWTP control system using a model-based setpoint optimisation. For this purpose, an anaerobic/anoxic/aerobic (A2/O) pilot WWTP was simulated using the IWA ASM2d model under different influent conditions. Several control strategies for an efficient biological C/N/P removal were evaluated in this WWTP: i) open loop; ii) dissolved oxygen control in the aerated reactors; iii) maximum performance of nutrient removal; iv) optimised fixed setpoints for the controlled variables; v) daily optimised setpoints; vi) two different sets of optimised setpoints for weekdays and weekends and vii) hourly optimised setpoints. A single cost function based on the operating costs by converting the effluent quality into monetary units was chosen for evaluating the plant performance (i.e. the control loops setpoints were optimised to obtain low effluent N and P discharges with the minimum costs). Setpoint optimisation was shown as a good tool to improve the performance of the system. In this case study, control strategy (vi) was selected as the best choice considering the trade-off cost-benefit. The optimised control system resulted in around a 45% decrease of operational costs with respect to the open loop scenario, a significant improvement of the effluent quality and a drastic decrease of the time above discharge limits.
This paper introduces a model library based on the simulation environment MATLAB/SIMULINK which allows the simulation of the aeration system of an wastewater treatment plant (WWTP). The model library presented covers all parts of an aeration system starting with the compressor set over the common air rail, flow resistances through pipes, controllable valves, aeration membranes and ending last not least with the controllers involved. The main objective of the development of the simulation system is the design, test and the support of the installation of more predictable and efficient control concepts for the aeration system in WWTPs. An example is given to demonstrate the application of the simulation system and to promote a control scheme with a flexible reference value for the pressure at the common air rail based on a most open valve (MOV) concept.
In this paper, a simulation benchmark of a pre-denitrifying activated sludge process is utilized in order to evaluate a supervisory aeration volume control strategy. The aeration volume control strategy has also been evaluated in a pilot plant at Hammarby Sjöstad in Stockholm, Sweden. The main idea has been to let the dissolved oxygen (DO) concentration in some of the aerated compartments be determined by a higher level controller driven by the DO concentration in other compartments. In this way, only sensors for measuring the DO concentrations are needed for the decision of time varying DO set-points. The high reliability of such sensors implies robust input values for the proposed control strategy. Moreover, it is known that the respiration rate is affected by the content of substrate and nitrogen in the compartments; therefore, the suggested manipulations of the DO set-points are indirectly determined by the current load into the plant. Compared to constant DO control and a supervisory DO set-point control strategy based on ammonium measurements in the last aerobic compartment, the suggested aeration volume control strategy could reduce the effluent nitrate and ammonium concentrations significantly without increasing the aeration energy.
Aeration is the most energy-intensive operation in wastewater treatment, amounting to 45-75% of plant energy costs. Fine-pore diffusers are today almost ubiquitous in municipal wastewater aeration, due to their advantageous aeration efficiency (mass of oxygen transferred per unit energy required). Nevertheless, older municipal treatment facilities and many industrial treatment plants are still equipped with coarse-bubble or surface aerators. Fine-pore diffusers are subject to two major disadvantages: a) fouling, if not cleaned periodically; b) decrease in oxygen transfer efficiency caused by dissolved surfactants. Coarse-bubble and surface aerators are typically not subject to the traditional problems affecting fine-pore diffusers. Nonetheless, they achieve oxygen transfer at the expense of increased energy intensity. The increased biomass concentration associated with high mean cell retention time (MCRT) operations has a beneficial effect on aeration. Nutrient-removing selectors are able to further increase aeration efficiency, as they sorb and utilize the readily available substrate which otherwise would accumulate at bubble surfaces and dramatically decrease aeration efficiency. We summarise here our 30-year long experience in aeration research, and results obtained with clean- and process-water tests are used to show the beneficial effects of high MCRT operations, the beneficial effect of selectors, and the decline of aeration efficiency due to dissolved surfactants.
Aeration control system design: a practical guide to energy and process optimization
- T E Jenkins
Jenkins, T.E., 2014. Aeration control system design: a practical guide to energy and
process optimization. https://doi.org/10.1016/j.eswa.2017.09.035.
Energy Conservation in Water and Wastewater Treatment Facilities, WEF Manual of Practice
- Wef
WEF, 2009. Energy Conservation in Water and Wastewater Treatment Facilities,
WEF Manual of Practice. McGraw-Hill, Inc., New York, NY [WWW Document].