Model-Based Optimization of Microalgae Growth in a Batch Plant

Albarello, A.; Simionato, Diana; Morosinotto, Tomas; Bezzo, Fabrizio

doi:10.1021/acs.iecr.9b00270

Cited by 7 publications

(6 citation statements)

References 31 publications

(44 reference statements)

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“…Over the last decade, microalgae-based biomass has been globally studied because it is capable of producing several important biochemicals, such as lipids, proteins, carbohydrates, and pigments, amongst others. These biochemicals are used as feedstock in the manufacturing of value-added products for human consumption and animal feed, pharmaceutics, biofertilizers, pigments and cosmetics, and for the synthesis of antimicrobial, antiviral, and antibacterial products and medical research, to provide just a few examples from a whole spectrum of possible applications [4,5]. The aforementioned systems can even be used in wastewater treatment processes [6,7].…”

Section: Introductionmentioning

confidence: 99%

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Sensitivity, Equilibria, and Lyapunov Stability Analysis in Droop’s Nonlinear Differential Equation System for Batch Operation Mode of Microalgae Culture Systems

et al. 2021

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Microalgae-based biomass has been extensively studied because of its potential to produce several important biochemicals, such as lipids, proteins, carbohydrates, and pigments, for the manufacturing of value-added products, such as vitamins, bioactive compounds, and antioxidants, as well as for its applications in carbon dioxide sequestration, amongst others. There is also increasing interest in microalgae as renewable feedstock for biofuel production, inspiring a new focus on future biorefineries. This paper is dedicated to an in-depth analysis of the equilibria, stability, and sensitivity of a microalgal growth model developed by Droop (1974) for nutrient-limited batch cultivation. Two equilibrium points were found: the long-term biomass production equilibrium was found to be stable, whereas the equilibrium in the absence of biomass was found to be unstable. Simulations of estimated parameters and initial conditions using literature data were performed to relate the found results to a physical context. In conclusion, an examination of the found equilibria showed that the system does not have isolated fixed points but rather has an infinite number of equilibria, depending on the values of the minimal cell quota and initial conditions of the state variables of the model. The numerical solutions of the sensitivity functions indicate that the model outputs were more sensitive, in particular, to variations in the parameters of the half saturation constant and minimal cell quota than to variations in the maximum inorganic nutrient absorption rate and maximum growth rate.

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Section: Introductionmentioning

confidence: 99%

“…Dynamic models might be useful to accomplish those tasks and to achieve the optimal biomass-based production of valuable metabolites. Therefore, understanding the dynamic behavior of biomass can help reduce the gap between laboratory-scale observations and those at the industrial scale [5,11,12].…”

Section: Introductionmentioning

confidence: 99%

Sensitivity, Equilibria, and Lyapunov Stability Analysis in Droop’s Nonlinear Differential Equation System for Batch Operation Mode of Microalgae Culture Systems

et al. 2021

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“…Among both approaches, offline optimization based on models has made significant contributions to the field, as seen in its application in. 29,36 Therefore, in this paper, based on previous research, the procedure to identify the optimal y(t) of the culture is described in Section 2.1.…”

Section: Continuous Microalgae Modelsmentioning

confidence: 99%

“…The identification of these optimal points, when appropriately assessed, aids the economic viability and sustainability of the cultivation system. Among both approaches, offline optimization based on models has made significant contributions to the field, as seen in its application in 29,36 . Therefore, in this paper, based on previous research, the procedure to identify the optimal y(t) of the culture is described in Section 2.1.…”

Section: Continuous Microalgae Modelsmentioning

confidence: 99%

Active disturbance rejection control: an application to continuous microalgae photobioreactors

Sangregorio‐Soto,

Mazzanti,

Cortés‐Romero

et al. 2023

J of Chemical Tech & Biotech

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BACKGROUNDMathematical modelling is a widely employed approach for investigating the growth behaviour of microalgae. As a result, the development of model‐based controllers to regulate process variables has garnered increasing attention. However, despite the significant efforts invested in this area, control performance can be adversely affected by unmodelled dynamics and disturbances.RESULTSTwo active disturbance rejection controllers (ADRC) were designed to enable robust tracking of biomass concentration in continuous microalgae photobioreactors, with reduced reliance on the mathematical model of the system. The controllers were tuned to achieve a nonovershoot response and minimize settling time based on the culture's characteristics. Simulations were performed using optimal setpoints specific to each model. The results showcased a maximum output signal deviation of ±2.2%, ±7.8% and ± 7.62% for the Dunaliella tertiolecta, Isochrysis affinis galbana and Chlorella vulgaris models, respectively, regardless of the presence of simulated disturbances.CONCLUSIONSThe findings of this study significantly contribute to the advancement of the field of sustainable microalgae production. By introducing less dependent model‐based controllers, this research enhances the feasibility of implementing robust control strategies. These controllers require only knowledge of the equation system's order and the control gain function, simplifying the design process. This approach effectively addresses control performance degradation arising from unmodelled dynamics and disturbances. The ability to maintain desired process variables through ADRC controllers not only ensures improved control performance, but also supports the cultivation of specific microalgal species, when an accurate model is not available, thus promoting the overall progress and viability of microalgae biomass production. © 2023 Society of Chemical Industry.

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“…Moreover, microalgae cultures in photobioreactors (PBRs) are highly responsive to light intensity and require consistent light intensity to optimize biomass productivity and metabolic activity. Several types of PBRs have been developed so far, including bubble column, airlift reactor, flat-plate, stirred-tank, and tubular, among others [29,30]. There is a close relationship between light distribution, hydrodynamics, mass transfer, and growth kinetics that complicates the design process [31][32][33].…”

Section: Introductionmentioning

confidence: 99%

Dynamical Simulation, Sensitivity, and Productivity Analysis of a Light-Photoacclimation Model for Microalgae-Based Carbohydrate Production in Continuous Photobioreactors

et al. 2023

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The world’s human population is increasing as is the demand for new sustainable sources of energy. Accordingly, microalgae-based carbohydrates for biofuel production are being considered as an alternative source of raw materials for producing biofuels. Microalgae grow in photobioreactors under constantly changing conditions. Models improve our understanding of microalgae growth. In this paper, a photoacclimated model for continuous microalgae cultures in photobioreactors was used to study the time-varying behavior and sensitivity of solutions under optimal productivity conditions. From the perspective of dynamic simulation in this work, light intensity was found to play an influential role in modifying metabolic pathways as a cell stressor. Enhancing carbohydrate productivity by combining nutritional deficiency and light intensity regulation modeling strategies could be helpful to optimize the process for the highest yield in large-scale cultivation systems. Under the proposed simulation conditions, a maximum carbohydrate productivity of 48.11 gCm−3d−1 was achieved using an optimal dilution rate of 0.2625 d−1 and 350 μmolm−2s−1 of light intensity. However, it is important to note that, a particular set of manipulated inputs can generate multiple outputs at a steady state. A numerical solution of the sensitivity functions indicated that the model outputs were especially sensitive to changes in parameters corresponding to a minimum nitrogen quota, maximum nitrogen intake rate, dilution rate, and maximum nitrogen quota compared to to other model parameters.

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Model-Based Optimization of Microalgae Growth in a Batch Plant

Cited by 7 publications

References 31 publications

Sensitivity, Equilibria, and Lyapunov Stability Analysis in Droop’s Nonlinear Differential Equation System for Batch Operation Mode of Microalgae Culture Systems

Sensitivity, Equilibria, and Lyapunov Stability Analysis in Droop’s Nonlinear Differential Equation System for Batch Operation Mode of Microalgae Culture Systems

Active disturbance rejection control: an application to continuous microalgae photobioreactors

Dynamical Simulation, Sensitivity, and Productivity Analysis of a Light-Photoacclimation Model for Microalgae-Based Carbohydrate Production in Continuous Photobioreactors

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