Meteorological Data-Based Optimal Control Strategy for Microalgae Cultivation in Open Pond Systems

Outdoor biofuel production from microalgae is a complex dynamical process submitted to climatic variations. Controlling and optimizing such a nonlinear process strongly influenced by weather conditions is therefore tricky, but it is crucial to make this process economically sustainable. The strategy...

Full description

Bibliographic Details
Main Authors: Riccardo De-Luca, Fabrizio Bezzo, Quentin Béchet, Olivier Bernard
Format: Article
Language:English
Published: Hindawi-Wiley 2019-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2019/4363895
id doaj-5d609f6e315b42adb2bde51c66887a82
record_format Article
spelling doaj-5d609f6e315b42adb2bde51c66887a822020-11-25T00:48:18ZengHindawi-WileyComplexity1076-27871099-05262019-01-01201910.1155/2019/43638954363895Meteorological Data-Based Optimal Control Strategy for Microalgae Cultivation in Open Pond SystemsRiccardo De-Luca0Fabrizio Bezzo1Quentin Béchet2Olivier Bernard3CAPE-Lab Computer-Aided Process Engineering Laboratory, Department of Industrial Engineering, Università di Padova, Via Marzolo 9, 35131 Padova, ItalyCAPE-Lab Computer-Aided Process Engineering Laboratory, Department of Industrial Engineering, Università di Padova, Via Marzolo 9, 35131 Padova, ItalyBIOCORE, INRIA, Université Côte d’Azur, BP 93, 06902 Sophia-Antipolis Cedex, FranceBIOCORE, INRIA, Université Côte d’Azur, BP 93, 06902 Sophia-Antipolis Cedex, FranceOutdoor biofuel production from microalgae is a complex dynamical process submitted to climatic variations. Controlling and optimizing such a nonlinear process strongly influenced by weather conditions is therefore tricky, but it is crucial to make this process economically sustainable. The strategy investigated in this study uses weather forecast coupled to a detailed predictive model of algal productivity for online optimization of the rates of fresh medium injection and culture removal into and from the pond. This optimization strategy was applied at various climatic conditions and significantly increased productivity compared to a standard operation with constant pond depth and dilution rate, by up to a factor of 2.2 in a Mediterranean climate in summer. A thorough analysis of the optimizer strategy revealed that the increase of productivity in summer was achieved by finding a trade-off between algal concentration to optimally distribute light and pond temperature to get closer to optimal growth temperature. This study also revealed that maintaining the temperature as high as possible is the best strategy to maximize productivity in cold climatic conditions.http://dx.doi.org/10.1155/2019/4363895
collection DOAJ
language English
format Article
sources DOAJ
author Riccardo De-Luca
Fabrizio Bezzo
Quentin Béchet
Olivier Bernard
spellingShingle Riccardo De-Luca
Fabrizio Bezzo
Quentin Béchet
Olivier Bernard
Meteorological Data-Based Optimal Control Strategy for Microalgae Cultivation in Open Pond Systems
Complexity
author_facet Riccardo De-Luca
Fabrizio Bezzo
Quentin Béchet
Olivier Bernard
author_sort Riccardo De-Luca
title Meteorological Data-Based Optimal Control Strategy for Microalgae Cultivation in Open Pond Systems
title_short Meteorological Data-Based Optimal Control Strategy for Microalgae Cultivation in Open Pond Systems
title_full Meteorological Data-Based Optimal Control Strategy for Microalgae Cultivation in Open Pond Systems
title_fullStr Meteorological Data-Based Optimal Control Strategy for Microalgae Cultivation in Open Pond Systems
title_full_unstemmed Meteorological Data-Based Optimal Control Strategy for Microalgae Cultivation in Open Pond Systems
title_sort meteorological data-based optimal control strategy for microalgae cultivation in open pond systems
publisher Hindawi-Wiley
series Complexity
issn 1076-2787
1099-0526
publishDate 2019-01-01
description Outdoor biofuel production from microalgae is a complex dynamical process submitted to climatic variations. Controlling and optimizing such a nonlinear process strongly influenced by weather conditions is therefore tricky, but it is crucial to make this process economically sustainable. The strategy investigated in this study uses weather forecast coupled to a detailed predictive model of algal productivity for online optimization of the rates of fresh medium injection and culture removal into and from the pond. This optimization strategy was applied at various climatic conditions and significantly increased productivity compared to a standard operation with constant pond depth and dilution rate, by up to a factor of 2.2 in a Mediterranean climate in summer. A thorough analysis of the optimizer strategy revealed that the increase of productivity in summer was achieved by finding a trade-off between algal concentration to optimally distribute light and pond temperature to get closer to optimal growth temperature. This study also revealed that maintaining the temperature as high as possible is the best strategy to maximize productivity in cold climatic conditions.
url http://dx.doi.org/10.1155/2019/4363895
work_keys_str_mv AT riccardodeluca meteorologicaldatabasedoptimalcontrolstrategyformicroalgaecultivationinopenpondsystems
AT fabriziobezzo meteorologicaldatabasedoptimalcontrolstrategyformicroalgaecultivationinopenpondsystems
AT quentinbechet meteorologicaldatabasedoptimalcontrolstrategyformicroalgaecultivationinopenpondsystems
AT olivierbernard meteorologicaldatabasedoptimalcontrolstrategyformicroalgaecultivationinopenpondsystems
_version_ 1725256739587096576