| Summary of optimisation options and scenarios (SC)

| Summary of optimisation options and scenarios (SC)

Source publication
Article
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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,...

Contexts in source publication

Context 1
... options were grouped into three cumu- lative scenarios of increasing financial investment. An overview of the optimisation options and the scenarios is shown in Table 3. To guarantee the robustness of the control strategies, all scenarios were stress-tested by an artificial ammonia peak, which increased the influent ammonia con- centration from the average (∼40 mg N·L À1 ) to 80 mg N·L À1 for 4 hours, starting on the eighth day of the simulation. ...
Context 2
... SC2: aeration system upgrade Scenario SC2 upgrades the aeration system to overcome air- flow limitations in reactor AER3 by (i) reducing the number of diffusers in the first two reactors, (ii) increasing the number of diffusers in the last two reactors, and (iii) resizing the pipes and valves, as described in Table 3. According to model predictions, this allows the plant to operate with the manual valves fully open, which translates into reduced system pressure. ...

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Citations

... The interdependent relations between the aeration diffuser system and the biological treatment process can be investigated with existing models, combining models such as Activated Sludge Model No. 1 (ASM1) (Henze et al. 2000) with oxygen transfer models (Amaral et al. 2017;Arnell 2016;Juan-Garcia et al. 2018;Schraa et al. 2017). In this way, the link between the electricity usage and the effluent water quality can be systematically evaluated. ...
... The oxygen transfer models (Arnell 2016;Juan-Garcia et al. 2018;Schraa et al. 2017) were found to be very useul for the purpose of aiding the design of new aeration systems, resulting in significant energy savings. The aeration model should preferrably be formulated such that performance data from suppliers can easily be incorporated into the model. ...
... This approach was considered sufficient for the current scope and facilitated a general comparison. However, when modeling an existing WRRF, it could be preferrable to include the dynamics of blowers and piping systems (Amaral et al. 2017;Juan-Garcia et al. 2018;Schraa et al. 2017) to improve the realism and the accuracy of electricity usage estimations. Additionally, the dynamics of electricity cost should be considered because it has been shown that reductions in power use does not always lead to lower cost (Aymerich et al. 2015). ...
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The influence of aeration diffuser system design on electricity usage, effluent water quality, and life-cycle cost in biological wastewater treatment was investigated. A plant-wide model was implemented, and simulations were carried out with different process configurations and aeration systems. Model-aided design of new aeration diffuser systems could significantly decrease electricity usage and life-cycle cost while at the same time avoiding negative effects on the treatment performance. The optimum distribution of diffuser systems in tanks in series was found to be influenced by process configuration, volumetric loading rate, temperature, and the internal recirculation flow rate. Compared with a conventional design approach, increasing the number of diffusers, up to a critical point, led to higher energy efficiency and lower life-cycle cost. This was despite an increasing limitation of the minimum airflow rate, leading to dissolved oxygen levels significantly exceeding control targets. Aeration systems optimized by simulations were found to, independently of process configuration, exhibit 20% lower electricity usage and 16%–18% lower life-cycle costs compared with systems designed based on a more conventional approach typically applied in practice.The influence of aeration diffuser system design on electricity usage, effluent water quality, and life-cycle cost in biological wastewater treatment was investigated. A plant-wide model was implemented, and simulations were carried out with different process configurations and aeration systems. Model-aided design of new aeration diffuser systems could significantly decrease electricity usage and life-cycle cost while at the same time avoiding negative effects on the treatment performance. The optimum distribution of diffuser systems in tanks in series was found to be influenced by process configuration, volumetric loading rate, temperature, and the internal recirculation flow rate. Compared with a conventional design approach, increasing the number of diffusers, up to a critical point, led to higher energy efficiency and lower life-cycle cost. This was despite an increasing limitation of the minimum airflow rate, leading to dissolved oxygen levels significantly exceeding control targets. Aeration systems optimized by simulations were found to, independently of process configuration, exhibit 20% lower electricity usage and 16%–18% lower life-cycle costs compared with systems designed based on a more conventional approach typically applied in practice.
... For the optimization of the aeration process control, dynamic models for the aeration systems are needed. In addition to optimization solutions for energy efficiency and process performance, utilization of these models can offer a possibility for troubleshooting analysis and evaluation of the systems performance under different operating scenarios (Juan-García et al. 2018). Accurate models would then enable comparison of different blower technologies and configurations as well as the design of different control strategies for energy efficiency improvements. ...
... Accurate models would then enable comparison of different blower technologies and configurations as well as the design of different control strategies for energy efficiency improvements. Juan-García et al. (2018) highlight the need for more detailed energy consumption models, as the simplified approaches that do not consider the equipment limitations overestimate the energy-saving potential. Amerlinck et al. (2016) also notes the issues of commonly used oversimplified energy consumption models and developed a dynamic model for predicting the energy costs of a diffused aeration system, based on the physical characteristics of the system, water depth and the airflow demand imposed by the control system. ...
... Amaral et al. (2017) state that the entire piping network should be modelled for accurate predictions of the dynamic process, but also state that potential simplifications should be studied. In contrast to the modelling approaches described in Juan-García et al. (2018), Amerlinck et al. (2016) and Amaral et al. (2017), Harja et al. (2016) used a very simplified approach for modelling the aeration distribution system, which was based only on the resistance coefficients of the pipelines and valve positioning to model the pressure system. For a complete model of an aeration system, the air supply system including the blowers needs to be modelled together with the oxygen transfer and demand in the bioreactors . ...
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... For instance, with respect to model-ling the aeration system and its energy consumption, Schraa et al. (2017) developed a fully dynamic model around the aeration header network to simulate the air distribution, and evaluated its limitations with various optimisation options and influent loadings [3]. Juan-Garcia et al. (2018) modified their study to the plant controlling systems by integrating a biokinetic model having oxygen uptake phenomena [4]. On the other hand, precise measurement of oxygen demand from the influent is still challenging because numerous influent sampling and analysis are needed to determine blower capac-ity which is the primary instrument of the air supply system. ...
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... In activate sludge systems manual air valves are used to ensure a correct distribution of the airflow to the various aerated zones. It is common praxis for manual valves to be adjusted empirically, through a trial and error approach, without fully considering the trade-offs occurring between effluent water quality, energy use and operating costs (Juan-García et al., 2018). Once the manual valves in the air supply system are set, these are seldom changed, with timescales that can range from months to years. ...
Conference Paper
The goal of this study is to analyze the impact on operating costs for different combinations of manual valve positions. In this study the set of optimal manual valve configurations are identified through the implementation of a multi-objective optimization algorithm. Data from a full-scale facility was used to develop a dynamic model of the air supply system. Furthermore, the costs implications following a change in the energy tariff structure are highlighted for four different manual valve combinations.
... The volume and the contaminant concentration are the critical parameters of pinch technology design. Some other quantitative methods, such as the mass balance model, the dynamic distribution model, and biokinetic process model, were commonly used in optimizing the wastewater recovery system (Juan-Garcia, Kiser, Schraa, Rieger, & Corominas, 2018;Sarpong, Gude, & Chitikela, 2018;Sarpong, Gude, & Magbanua, 2019). Comprehensive mathematical models, such as multiobjective optimization and scenario-based simulation (Borzooei et al., 2019), have also been used to optimize the wastewater treatment process and enhance the energy efficiency of the system. ...
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... However, detailed models of actual equipment components, such as diffusers, blowers, pipes and valves, have only been marginally implemented in simulation studies of air supply systems (Juan-García et al., 2018). In fact, the vast majority of dynamic simulation studies completed thus far assumes an ideal continuous supply of airflow capable of matching demand requirements, thus neglecting the physical and operational limitations of the air delivery components (Ingildsen et al., 2002;Zhu and Anderson, 2017). ...
... The operating boundaries of aeration equipment, such as blower turndown and maximum diffuser pressure drop, are critical for a realistic description of dynamic control strategies (Amaral et al., 2017). In fact, the simulation of control strategies that do not explicitly account for equipment specifications may limit accurate model prediction or even conceal the applicability of the control action itself (Juan-García et al., 2018). ...
... This has allowed describing more realistically the interactions occurring between the aeration system (oxygen supply side), the biological reactors (oxygen demand side), and the control system. More recently, the work from Juan- García et al. (2018) shows the use of a detailed air supply system model for the comparative analysis of various energy optimization strategies for a 55,000 m 3 d À1 (~14.5 MGD) capacity facility. ...
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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.
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