- -

Modelado y control de la producción de microalgas en fotobiorreactores industriales

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

Modelado y control de la producción de microalgas en fotobiorreactores industriales

Mostrar el registro sencillo del ítem

Ficheros en el ítem

dc.contributor.author Guzmán, J. L. es_ES
dc.contributor.author Acién, F. G. es_ES
dc.contributor.author Berenguel, M. es_ES
dc.date.accessioned 2021-02-02T12:58:52Z
dc.date.available 2021-02-02T12:58:52Z
dc.date.issued 2020-12-23
dc.identifier.issn 1697-7912
dc.identifier.uri http://hdl.handle.net/10251/160486
dc.description.abstract [EN] This manuscript presents a general overview of the microalgae production process from a modelling and control perspective. First, the main advantages and the potential of these microorganisms are motivated, describing the dierent type of reactors used for their cultivation. Afterwards, the process dynamics, which is very complex and variable due to diary and annual changes on ambient conditions, is analyzed and the main balance equations to describe the system behaviour are introduced. Then, dierent biological and structural models validated in industrial plants will be presented. Subsequently, the existing control problems in these systems are described, introducing a wide set of control algorithms that have been experimentally evaluated in industrial reactors. Finally, the most relevant aspects discussed along the paper are summarized. es_ES
dc.description.abstract [ES] Este artículo presenta una visión general sobre el proceso de producción de microalgas desde un punto de vista de modelado y control de procesos. En primer lugar se exponen las ventajas y el potencial de este tipo de microorganismos, así como los distintos tipos de reactores que se suelen utilizar para su producción. Posteriormente, se analiza el comportamiento dinámico de este tipo de procesos, el cual es muy complejo y cambiante debido a variaciones en las condiciones ambientales tanto diarias como anuales, y se presentan los distintos balances que permiten describir la evolución de las principales variables del sistema. Se exponen distintos tipos de modelos a nivel biológico y a nivel estructural que han sido validados a escala industrial. Tras analizar su comportamiento dinámico, se motivan los distintos problemas de control existentes en este tipo de sistemas y se resume una amplia batería de estrategias de control que han sido evaluadas con éxito en fotobiorreactores industriales. Finalmente, se concluye el trabajo con un balance de los aspectos más importantes expuestos a lo largo del mismo. es_ES
dc.description.sponsorship Este trabajo ha sido realizado parcialmente gracias al apoyo del Ministerio de Economía y Competitividad con el proyecto DPI2017-84259-C2-1- R y el Programa de Investigación e Innovación Horizonte 2020 de la Unión Europea en el marco del proyecto SABANA (No. 727874). es_ES
dc.language Español es_ES
dc.publisher Universitat Politècnica de València es_ES
dc.relation.ispartof Revista Iberoamericana de Automática e Informática industrial es_ES
dc.rights Reconocimiento - No comercial - Compartir igual (by-nc-sa) es_ES
dc.subject Microalgas es_ES
dc.subject Modelado es_ES
dc.subject Control es_ES
dc.subject Fotobioreactores es_ES
dc.subject Biotecnología es_ES
dc.subject Microalgae es_ES
dc.subject Modelling es_ES
dc.subject Photobioreactors es_ES
dc.subject Biotechnology es_ES
dc.title Modelado y control de la producción de microalgas en fotobiorreactores industriales es_ES
dc.title.alternative Modelling and control of microalgae production in industrial photobioreactors es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.4995/riai.2020.13604
dc.relation.projectID info:eu-repo/grantAgreement/AEI//Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/DPI2017-84259-C2-1-R/ES/MODELADO Y CONTROL DEL PROCESO COMBINADO DE PRODUCCION DE MICROALGAS Y TRATAMIENTO DE AGUAS RESIDUALES CON REACTORES INDUSTRIALES/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/727874/EU/Sustainable Algae Biorefinery for Agriculture aNd Aquaculture/ es_ES
dc.rights.accessRights Abierto es_ES
dc.description.bibliographicCitation Guzmán, JL.; Acién, FG.; Berenguel, M. (2020). Modelado y control de la producción de microalgas en fotobiorreactores industriales. Revista Iberoamericana de Automática e Informática industrial. 18(1):1-18. https://doi.org/10.4995/riai.2020.13604 es_ES
dc.description.accrualMethod OJS es_ES
dc.relation.publisherversion https://doi.org/10.4995/riai.2020.13604 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 18 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 18 es_ES
dc.description.issue 1 es_ES
dc.identifier.eissn 1697-7920
dc.relation.pasarela OJS\13604 es_ES
dc.contributor.funder European Commission es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES
dc.description.references Acién, F. G., Camacho, F. G., Sánchez-Pérez, J. A., Fernández-Sevilla, J. M., Molina-Grima, E., 1997. A model for light distribution and average solar irradiance inside outdoor tubular photobioreactors for the microalgal mass culture. Biotechnology and Bioengineering 55, 701-714. https://doi.org/10.1002/(SICI)1097-0290(19970905)55:5<701::AID-BIT1>3.0.CO;2-F es_ES
dc.description.references Acién, F. G., Fernández-Sevilla, J. M., Molina-Grima, E., 2017. Microalgae: The basis of mankind sustainability. In: Case Study of Innovative Projects - Successful Real Cases. InTech, Ch. 7, pp. 123-140. https://doi.org/10.5772/67930 es_ES
dc.description.references Acién, F. G., García-Camacho, F., Sánchez-Pérez, J. A., Fernández-Sevilla, J. M., Molina-Grima, E., 1998. Modeling of biomass productivity in tubular photobioreactors for microalgal cultures: Effects of dilution rate, tube diameter, and solar irradiance. Biotechnology and Bioengineering 58, 605-616. https://doi.org/10.1002/(SICI)1097-0290(19980620)58:6<605::AID-BIT6>3.0.CO;2-M es_ES
dc.description.references Acién, F. G., Gómez-Serrano, C., Morales-Amaral, M. M., Fernández-Sevilla, J. M., Molina-Grima, E., 2016. Wastewater treatment using microalgae: how realistic a contribution might it be to significant urban wastewater treatment? Applied Microbiology and Biotechnology 100, 9013-9022. https://doi.org/10.1007/s00253-016-7835-7 es_ES
dc.description.references Barcelo-Villalobos, M., Acién, F. G., Guzmán, J. L., Fernández-Sevilla, J. M., Berenguel, M., 2019a. New strategies for the design and control of raceway reactors to optimize microalgae production. In: Handbook of Algal Technologies and Phytochemicals. Volume II: Phycoremediation, Biofuels and Global Biomass Production. CRC Press, Ch. 18, pp. 221-230. https://doi.org/10.1201/9780429057892-19 es_ES
dc.description.references Barcelo-Villalobos, M., Guzmán, J. L., Acién, F. G., 2019b. Nonlinear predictive control of a pH process. In: 2nd IWA Conference on Algal Technologies for Wastewater Treatment and Resource Recovery. Valladolid, Spain. es_ES
dc.description.references Barcelo-Villalobos, M., Guzmán, J. L., Martín-Cara, I., Sánchez, J. A., Acién, F. G., 2018. Analysis of mass transfer capacity in raceway reactors. Algal Research 35, 91-97. https://doi.org/10.1016/j.algal.2018.08.017 es_ES
dc.description.references Benemann, J. R., 2003. Biofixation of CO2 and greenhouse gas abatement with microalgae. In: 6th Asia-Pacific Conference on Algal Biotechnology. Makati City, Philippines. es_ES
dc.description.references Berenguel, M., Rodríguez, F., Acién, F. G., García, J. L., 2004. Model predictive control of pH in tubular photobioreactors. Journal of Process Control 14, 377-387. https://doi.org/10.1016/j.jprocont.2003.07.001 es_ES
dc.description.references Bernard, O., 2011. Hurdles and challenges for modelling and control of microalgae for CO2 mitigation and biofuel production. Journal of Process Control 21, 1378-1389. https://doi.org/10.1016/j.jprocont.2011.07.012 es_ES
dc.description.references Borowitzka, M. A., 1999. Commercial production of microalgae: ponds, tanks, tubes and fermenters. Journal of Biotechnology 70 (1), 313 - 321, biotechnological Aspects of Marine Sponges. https://doi.org/10.1016/S0168-1656(99)00083-8 es_ES
dc.description.references Brindley, C., Jiménez-Ruíz, N., Acién, F. G., Fernández-Sevilla, J. M., 2016. Light regime optimization in photobioreactors using a dynamic photosynthesis model. Algal Research 16, 399-408. https://doi.org/10.1016/j.algal.2016.03.033 es_ES
dc.description.references Carreno-Zagarra, J. J., Guzmán, J. L., Moreno, J. C., Villamizar, R., 2019. Linear active disturbance rejection control for a raceway photobioreactor. Control Engineering Practice 85, 271-279. https://doi.org/10.1016/j.conengprac.2019.02.007 es_ES
dc.description.references Chen, C. Y., Yeh, K. L., Aisyah, R., Lee, D. J., Chang, J. S., 2011. Cultivation, photobioreactor design and harvesting of microalgae for biodiesel production: A critical review. Bioresource Technology 102, 71-81. https://doi.org/10.1016/j.biortech.2010.06.159 es_ES
dc.description.references Chen, J., Wang, Y., Benemann, J. R., Zhang, X., Hu, H., Qin, S., 2016. Microalgal industry in China: Challenges and prospects. Journal of Applied Phycology 28, 715-725. https://doi.org/10.1007/s10811-015-0720-4 es_ES
dc.description.references Chiaramonti, D., Prussi, M., Casini, D., Tredici, M. R., Rodolfi, L., Bassi, N., Zittelli, G. C., Bondioli, P., 2013. Review of energy balance in raceway ponds for microalgae cultivation: Re-thinking a traditional system is possible. Applied Energy 102, 101-111. https://doi.org/10.1016/j.apenergy.2012.07.040 es_ES
dc.description.references Concas, A., Pisu, M., Cao, G., 2010. Novel simulation model of the solar collector of BIOCOIL photobioreactors for CO2 sequestration with microalgae. Chemical Engineering Journal 157, 297-303. https://doi.org/10.1016/j.cej.2009.10.059 es_ES
dc.description.references Costache, T. A., Acién, F. G., Morales, M. M., Fernández-Sevilla, J. M., Stamatin, I., Molina-Grima, E., 2013. Comprehensive model of microalgae photosynthesis rate as a function of culture conditions in photobioreactors. Applied Microbiology and Biotechnology 97, 7627-7637. https://doi.org/10.1007/s00253-013-5035-2 es_ES
dc.description.references Cuaresma, M., Janssen, M., Valchez, C., Wijffels, R. H., 2011. Horizontal or vertical photobioreactors? how to improve microalgae photosynthetic efficiency. Bioresource Technology 102, 5129-5137. https://doi.org/10.1016/j.biortech.2011.01.078 es_ES
dc.description.references de Andrade, G. A., Berenguel, M., Guzmán, J. L., Pagano, D. J., Acién, F. G., 2016a. Optimization of biomass production in outdoor tubular photobioreactors. Journal of Process Control 37, 58-69. https://doi.org/10.1016/j.jprocont.2015.10.001 es_ES
dc.description.references de Andrade, G. A., Pagano, D. J., Guzmán, J. L., Berenguel, M., Fernández, I., Acién, F. G., 2016b. Distributed sliding mode control of pH in tubular ' photobioreactors. IEEE Transactions on Control Systems Technology 24, 1160-1173. https://doi.org/10.1109/TCST.2015.2480840 es_ES
dc.description.references de Godos, I., Mendoza, J. L., Acién, F. G., Molina, E., Banks, C. J., Heaven, S., Rogalla, F., 2014. Evaluation of carbon dioxide mass transfer in raceway reactors for microalgae culture using flue gases. Bioresource Technology 153, 307-314. https://doi.org/10.1016/j.biortech.2013.11.087 es_ES
dc.description.references Djema, W., Bernard, O., Giraldi, L., 2020. Separating two species of microalgae in photobioreactors in minimal time. Journal of Process Control 87, 120-129. https://doi.org/10.1016/j.jprocont.2020.01.003 es_ES
dc.description.references Dochain, D., 2000. State observers for tubular reactors with unknown kinetics. Journal of Process Control 10, 259-268. https://doi.org/10.1016/S0959-1524(99)00020-7 es_ES
dc.description.references Dochain, D., 2008. Bioprocess Control. John Wiley & Sons, Ltd. Doran, P. M., 1997. Bioprocess Engineering Principles. Elsevier Science & Technology Booksl. https://doi.org/10.1002/9780470611128 es_ES
dc.description.references Fernández, I., Acién, F. G., Berenguel, M., Guzmán, J. L., 2014a. First principles model of a tubular photobioreactor for microalgal production. Industrial & Engineering Chemistry Research 53, 11121-11136. https://doi.org/10.1021/ie501438r es_ES
dc.description.references Fernández, I., Acién, F. G., Berenguel, M., Guzmán, J. L., de Andrade, G. A., Pagano, D. J., 2014b. A lumped parameter chemical-physical model for tubular photobioreactors. Chemical Engineering Science 112, 116-129. https://doi.org/10.1016/j.ces.2014.03.020 es_ES
dc.description.references Fernández, I., Acién, F. G., Fernández, J. M., Guzmán, J. L., Magán, J. J., Berenguel, M., 2012. Dynamic model of microalgal production in tubular photobioreactors. Bioresource Technology 126, 172-181. https://doi.org/10.1016/j.biortech.2012.08.087 es_ES
dc.description.references Fernández, I., Acién, F. G., Guzmán, J. L., Berenguel, M., Mendoza, J. L., 2016a. Dynamic model of an industrial raceway reactor for microalgae production. Algal Research 17, 67-78. https://doi.org/10.1016/j.algal.2016.04.021 es_ES
dc.description.references Fernández, I., Berenguel, M., Guzmán, J. L., Acién, F. G., de Andrade, G. A., Pagano, D. J., 2016b. Hierarchical control for microalgae biomass production in photobiorreactors. Control Engineering Practice 54, 246-255. https://doi.org/10.1016/j.conengprac.2016.06.007 es_ES
dc.description.references Fernández, I., Guzmán, J. L., Acién, F. G., Berenguel, M., 2017. Dynamic modeling of microalgal production in photobioreactors. In: Prospects and Challenges in Algal Biotechnology. Springer, Ch. 7, pp. 49-87. https://doi.org/10.1007/978-981-10-1950-0 es_ES
dc.description.references Fernández, I., Pena, J., Guzmán, J. L., Berenguel, M., Acién, F. G., 2010. Modelling and control issues of pH in tubular photobioreactors. IFAC Proceedings Volumes 43, 186-191. https://doi.org/10.3182/20100707-3-BE-2012.0046 es_ES
dc.description.references García-Manas, F., Guzmán, J. L., Berenguel, M., Acién, F. G., 2019. Biomass estimation of an industrial raceway photobioreactor using an extended Kalman filter and a dynamic model for microalgae production. Algal Research 37, 103-114. https://doi.org/10.1016/j.algal.2018.11.009 es_ES
dc.description.references Guterman, H., Vonshak, A., Ben-Yaakov, S., 1990. A macromodel for outdoor algal mass production. Biotechnology and Bioengineering 35, 809-819. https://doi.org/10.1002/bit.260350809 es_ES
dc.description.references Hoyo, A., Guzmán, J., Acién, F. G., Moreno, J. C., 2019a. A graphical tool to simulate raceway photoreactors. In: 2nd IWA Conference on Algal Technologies for Wastewater Treatment and Resource Recovery. Valladolid, Spain. es_ES
dc.description.references Hoyo, A., Guzmán, J. L., Moreno, J. C., Berenguel, M., 2018. Control robusto con QFT del pH en un fotobiorreactor raceway. In: XXXVIII Jornadas de Automatica. Universidad de Oviedo, pp. 77-83. es_ES
dc.description.references Hoyo, A., Guzmán, J. L., Moreno, J. C., Berenguel, M., 2019b. Control predictivo lineal del pH en un fotobiorreactor raceway. In: XL Jornadas de Automatica. Universidade da Coruña, Servizo de Publicacións, pp. 414-420. https://doi.org/10.17979/spudc.9788497497169.414 es_ES
dc.description.references Ifrim, G. A., Titica, M., Barbu, M., Boillereaux, L., Cogne, G., Caraman, S., Legrand, J., 2013. Multivariable feedback linearizing control of Chlamydomonas reinhardtii photoautotrophic growth process in a torus photobioreactor. Chemical Engineering Journal 218, 191-203. https://doi.org/10.1016/j.cej.2012.11.133 es_ES
dc.description.references James, S. C., Boriah, V., 2010. Modeling algae growth in an open-channel raceway. Journal of Computational Biology 17, 895-906. https://doi.org/10.1089/cmb.2009.0078 es_ES
dc.description.references Jupsin, H., Praet, E., Vasel, J. L., 2003. Dynamic mathematical model of high rate algal ponds (HRAP). Water Science and Technology 48, 197-204. https://doi.org/10.2166/wst.2003.0120 es_ES
dc.description.references Lazar, C., Pintea, R., Keyser, R. D., 2007. Nonlinear predictive control of a pH process. Computer Aided Chemical Engineering 24, 829-834. https://doi.org/10.1016/S1570-7946(07)80161-1 es_ES
dc.description.references Li, J., Xu, N. S., Su, W. W., 2003. Online estimation of stirred-tank microalgal photobioreactor cultures based on dissolved oxygen measurement. Biochemical Engineering Journal 14, 51-65. https://doi.org/10.1016/S1369-703X(02)00135-3 es_ES
dc.description.references Malek, A., Zullo, L. C., Daoutidis, P., 2016. Modeling and dynamic optimization of microalgae cultivation in outdoor open ponds. Industrial Engineering Chemical Research 55, 3327-3337. https://doi.org/10.1021/acs.iecr.5b03209 es_ES
dc.description.references Marrafioti, G., Tebbani, S., Beauvois, D., Becerra, G., Isambert, A., Hovd, M., 2009. Unscented Kalman Filter state and parameter estimation in a photobioreactor for microalgae production. IFAC Proceedings Volumes 42, 804- 809. https://doi.org/10.3182/20090712-4-TR-2008.00131 es_ES
dc.description.references McGinn, P. J., MacQuarrie, S. P., Choi, J., Tartakovsky, B., 2017. Maximizing the productivity of the microalgae Scenedesmus AMDD cultivated in a continuous photobioreactor using an online flow rate control. Bioprocess Biosystems Engineering 40, 63-71. https://doi.org/10.1007/s00449-016-1675-9 es_ES
dc.description.references Mehar, J., Shekh, A., Nethravathy, M. U., Sarada, R., Chauhan, V. S., Mudliar, S., 2019. Automation of pilot-scale open raceway pond: A case study of CO2-fed pH control on Spirulina biomass, protein and phycocyanin production. Journal of CO2 utilization 33, 384-393. https://doi.org/10.1016/j.jcou.2019.07.006 es_ES
dc.description.references Mendoza, J. L., Granados, M. R., de Godos, I., Acién, F. G., Molina, E., Banks, C., Heaven, S., 2013a. Fluid-dynamic characterization of real-scale raceway reactors for microalgae production. Biomass and Bioenergy 54, 267-275. https://doi.org/10.1016/j.biombioe.2013.03.017 es_ES
dc.description.references Mendoza, J. L., Granados, M. R., de Godos, I., Acién, F. G., Molina, E., Heaven, S., Banks, C., 2013b. Oxygen transfer and evolution in microalgal culture in open raceways. Bioresource Technology 137, 188-195. https://doi.org/10.1016/j.biortech.2013.03.127 es_ES
dc.description.references Molina-Grima, E., Fernández-Sevilla, J. M., Sánchez-Pérez, J. A., García Camacho, F., 1996. A study on simultaneous photolimitation and photoinhibition in dense microalgal cultures taking into account incident and averaged irradiances. Journal of Biotechnology 45, 59-69. https://doi.org/10.1016/0168-1656(95)00144-1 es_ES
dc.description.references Munoz-Tamayo, R., Martinon, P., Bougaran, G., Mairet, F., Bernard, O., 2014. Getting the most out of it: Optimal experiments for parameter estimation of microalgae growth models. Journal of Process Control 24, 991-1001. https://doi.org/10.1016/j.jprocont.2014.04.021 es_ES
dc.description.references Norsker, N. H., Barbosa, M. J., Vermue, M. H., Wijffels, R. H., 2011. Microalgal production - a close look at the economics. Biotechnology Advances 29, 24-27. es_ES
dc.description.references https://doi.org/10.1016/j.biotechadv.2010.08.005 es_ES
dc.description.references Oblak, S., Skrjanc, I., 2010. Continuous-time Wiener-model predictive control of a pH process based on a PWL approximation. Chemical Engineering Science 65, 1720-1728. https://doi.org/10.1016/j.ces.2009.11.008 es_ES
dc.description.references Oswald, W. J., Golueke, C. G., 1968. Large-scale production of algae. In: Single-Cell Protein. The MIT Press, pp. 271-305. es_ES
dc.description.references Patti, M. A., Feroldi, D., Zumoffen, D., 2019. Control predictivo aplicado a un proceso de producción continua de biodiesel. Revista Iberoamericana de Automática e Informática Industrial 16, 296-307. https://doi.org/10.4995/riai.2019.10696 es_ES
dc.description.references Pawlowski, A., Guzmán, J. L., Acién, F. G., Berenguel, M., Dormido, S., 2017. Event-based control systems for microalgae culture in industrial reactors. In: Prospects and Challenges in Algal Biotechnology. Springer, Ch. 7, pp. 1-48. https://doi.org/10.1007/978-981-10-1950-0 es_ES
dc.description.references Pawlowski, A., Guzmán, J. L., Berenguel, M., Acién, F. G., 2019. Control system for pH in raceway photobioreactors based on Wiener models. IFACPapersOnLine 52, 928-933, 12th IFAC Symposium on Dynamics and Control of Process Systems, including Biosystems DYCOPS 2019. https://doi.org/10.1016/j.ifacol.2019.06.181 es_ES
dc.description.references Pawlowski, A., Mendoza, J. L., Guzmán, J. L., Berenguel, M., Acién, F. G., Dormido, S., 2014. Effective utilization of flue gases in raceway reactor with event-based pH control for microalgae culture. Bioresource Technology 170, 1-9. https://doi.org/10.1016/j.biortech.2014.07.088 es_ES
dc.description.references Pawlowski, A., Mendoza, J. L., Guzmán, J. L., Berenguel, M., Acién, F. G., Dormido, S., 2015. Selective pH and dissolved oxygen control strategy for a raceway reactor within an event-based approach. Control Engineering Practice 44, 209-218. https://doi.org/10.1016/j.conengprac.2015.08.004 es_ES
dc.description.references Peng, L., Lan, C. Q., Zhang, Z., 2013. Evolution, detrimental effects, and removal of oxygen in microalga cultures: A review. Environmental Progress & Sustainable Energy 32, 982-988. https://doi.org/10.1002/ep.11841 es_ES
dc.description.references Pires, J. C. M., Alvim-Ferraz, M. C. M., Martins, F. G., 2017. Photobioreactor design for microalgae production through computational fluid dynamics: A review. Renewable and Sustainable Energy Reviews 79, 248-254. https://doi.org/10.1016/j.rser.2017.05.064 es_ES
dc.description.references Posten, C., 2009. Design principles of photo-bioreactors for cultivation of microalgae. Engineering in Life Sciences 9, 165-177. https://doi.org/10.1002/elsc.200900003 es_ES
dc.description.references Putt, R., Singh, M., Chinnasamy, S., Das, K. C., 2011. An efficient system for carbonation of high-rate algae pond water to enhance CO2 mass transfer. Bioresource Technology 102, 3240-3245. https://doi.org/10.1016/j.biortech.2010.11.029 es_ES
dc.description.references Richmond, A., 2004. Principles for attaining maximal microalgal productivity in photobioreactors: an overview. Hydrobiologia 512, 33-37. https://doi.org/10.1023/B:HYDR.0000020365.06145.36 es_ES
dc.description.references Rodríguez-Blanco, T., Sarabia, D., de Prada, C., 2018. Optimizacion en tiempo real utilizando la metodología de adaptacion de modificadores. Revista Iberoamericana de Automatica e Informatica Industrial 15, 133-144. https://doi.org/10.4995/riai.2017.8846 es_ES
dc.description.references Rodríguez-Miranda, E., Acién, F. G., Guzmán, J. L., Berenguel, M., Visioli, A., 2019. Modelo de temperatura para reactores abiertos de microalgas. In: XL Jornadas de Automatica. Universidade da Coruña, Servizo de Publicacións, pp. 582-588. https://doi.org/10.17979/spudc.9788497497169.582 es_ES
dc.description.references Rodríguez-Miranda, E., Beschi, M., Guzmán, J. L., Berenguel, M., Visioli, A., 2019. Daytime/nighttime event-based PI control for the pH of a microalgae raceway reactor. Processes 7, 1-16. https://doi.org/10.3390/pr7050247 es_ES
dc.description.references Rodríguez-Miranda, E., Guzmán, J. L., Aci en, F. G., Berenguel, M., Visioli, A., 2020. Temperature regulation for microalgae raceway reactors based on liquid level optimization. Algal ResearchEn revision. es_ES
dc.description.references Romero-García, J. M., Guzmán, J. L., Moreno, J. C., Acién, F. G., Fernández-Sevilla, J. M., 2012. Filtered Smith Predictor to control pH during enzymatic hydrolysis of microalgae to produce L-aminoacids concentrates. Chemical Engineering Science 82, 121-131. https://doi.org/10.1016/j.ces.2012.07.024 es_ES
dc.description.references Senthil-Kumar, A., Ahmad, Z., 2012. Model predictive control (MPC) and its current issues in chemical engineering. Chemical Engineering Communications 199, 472-511. https://doi.org/10.1080/00986445.2011.592446 es_ES
dc.description.references Sompech, K., Chisti, Y., Srinophakun, T., 2014. Design of raceway ponds for producing microalgae. Biofuels 3, 387-397. https://doi.org/10.4155/bfs.12.39 es_ES
dc.description.references Stepan, D., Shockey, R., Dorn, T. M. R., 2002. Carbon Dioxide Sequestering using Microalgae Systems. US Department of Energy, Pittsburgh, PA, USA. es_ES
dc.description.references Tang, D., Han, W., Li, P., Miao, X., Zhong, J., 2011. CO2 biofixation and fatty acid composition of Scenedesmus obliquus and Chlorella pyrenoidosa in response to different CO2 levels. Bioresource Technology 102, 3071-3076. https://doi.org/10.1016/j.biortech.2010.10.047 es_ES
dc.description.references Tebbani, S., Lopes, F., Becerra-Celis, G., 2015. Nonlinear control of continuous cultures of Porphyridium purpureum in a photobioreactor. Chemical Engineering Science 123, 207-219. https://doi.org/10.1016/j.ces.2014.11.016 es_ES
dc.description.references Tebbani, S., Titica, M., Caraman, S., Boillereaux, L., 2013. Estimation of Chlamydomonas reinhardtii growth in a torus photobioreactor. IFAC Proceedings Volumes 46, 72-77, 12th IFAC Symposium on Computer Applications in Biotechnology. https://doi.org/10.3182/20131216-3-IN-2044.00053 es_ES
dc.description.references van Esbroeck, E., 2018. Temperature control of microalgae cultivation under variable conditions. MSc Thesis: Biobased Chemistry and Technology - Wageningen University. es_ES
dc.description.references Wang, Z., Wen, X., Xu, Y., Ding, Y., Geng, Y., Li, Y., 2018. Maximizing CO2 biofixation and lipid productivity of oleaginous microalga Graesiella sp.WBG1 via CO2-regulated pH in indoor and outdoor open reactors. Science of the Total Environment 619-620, 827-833. https://doi.org/10.1016/j.scitotenv.2017.10.127 es_ES
dc.description.references Weissman, C. J., Goebel, R. P., Benemann, J. R., 1988. Photobioreactor design: Mixing, carbon utilization, and oxygen accumulation. Biotechnology and Bioengineering 31, 336-344. https://doi.org/10.1002/bit.260310409 es_ES
dc.description.references Xin, L., Hong-ying, H., Ke, G., Ying-xue, S., 2010. Effects of different nitrogen and phosphorus concentrations on the growth, nutrient uptake, and lipid accumulation of a freshwater microalga Scenedesmus sp. Bioresource Technology 101, 5494-5500. https://doi.org/10.1016/j.biortech.2010.02.016 es_ES


Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem