Cost reduction of the wastewater treatment plant operation by MPC based on modified ASM1 with two-step nitrification/denitrification model

Babes-Bolyai University, Faculty of Chemistry and Chemical Engineering, 11 Arany Janos, 400028 Cluj-Napoca, Romania
Computers & Chemical Engineering (Impact Factor: 2.78). 11/2011; 35:2469-2479. DOI: 10.1016/j.compchemeng.2011.03.031
Source: DBLP


The Activated Sludge Model No. 1 (ASM1) considers that nitrification and denitrification are single step processes and nitrite nitrogen (NO2–N), which is an intermediate for the two processes, is not accounted for. The first part of this paper presents the development of an enhanced ASM1 with two step nitrification/denitrification processes and its implementation in the Benchmark Simulation Model No.1 wastewater treatment plant (WWTP). The secondary settler was considered to be reactive in order to achieve a better fit between the simulation model and the behavior of the real WWTP. The second part presents the investigation of Model Predictive Control approach for the advanced control of the WWTP. Two control strategies are implemented for the wastewater treatment plant and they are analyzed from the perspective of the benefits brought to the WWTP operation. The proposed control strategy shows a reduction of the operational costs and the improvement of the effluent quality index.

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    • "More recently, Stare et al. [10], Holenda et al. [11], Shen et al. [12] and Ostace et al. [13] compared and tested different MPC configurations . Lately, the BSM1 has been used for testing a nonlinear multiobjective model-predictive control scheme [14]. "
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    ABSTRACT: In this work, we discuss the application of multivariable predictive control for the activated sludge process in a full-scale municipal wastewater treatment plant. Emphasis is given to the selection of a control configuration that contributes to minimising the economic costs while improving the removal efficiency of the nitrogen compounds. For this task, a simple dynamic matrix control algorithm is favoured for con- trolling the nitrogen concentrations at the end of the biological process. The behaviour of the activated sludge process is reproduced in a commercial simulator that acts as a real-time testing platform and that is also used for identifying the multivariable input–output models for the predictive controller. For demonstrating the effectiveness of the proposed approach, different control configurations are considered and compared against the aeration control strategies currently used at the plant. Based on the simulation results, this work shows the potentiality of the dynamic matrix control which is able to decrease the energy consumption costs and, at the same time, reduce the ammonia peaks and nitrate concentration in the effluent.
    Journal of Process Control 08/2015; 35:89-100. DOI:10.1016/j.jprocont.2015.08.005 · 2.65 Impact Factor
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    • "The high capital and operational costs associated to these facilities (Vanrolleghem et al., 1996; Liu et al., 2011; Rodriguez-Garcia et al., 2011) have fostered the use of simulation models to optimise their performance , and in this sense, the ASM family models (Henze et al., 2000) have become a standard. In the last years, many publications have illustrated the usefulness of simulation models for WWTP design (Bixio et al., 2002; Benedetti et al., 2010; Rivas et al., 2008); operation (Ostace et al., 2011) and control (Ayesa et al., 2006; Nopens et al., 2010; Flores-Alsina et al., 2008; Yong et al., 2006). "
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    ABSTRACT: 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.
    Environmental Modelling and Software 10/2014; 60:188–201. DOI:10.1016/j.envsoft.2014.05.008 · 4.42 Impact Factor
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    • "Since NO and N 2 O accumulation are negligible in sewers (Abdul-Talib et al. 2002), the pathway of heterotrophic denitrification utilizing acetate is generally simplified as Equations 1–3 (Ni & Yu 2008; Ostace et al. 2011). However, chemical nitrate addition for sulfide control induces autotrophic denitrification in sewers. "

    Water Practice & Technology 05/2013; 8(1):33-40. DOI:10.2166/wpt.2013.005
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