A novel data-driven model for prediction and adaptive control of pH in raceway reactor for microalgae cultivation.
N Biotechnol
; 82: 1-13, 2024 Sep 25.
Article
en En
| MEDLINE
| ID: mdl-38615946
ABSTRACT
This work proposes a new data-driven model to estimate and predict pH dynamics in freshwater raceway photobioreactors. The resulting model is based purely on data measured from the reactor and divides the pH dynamics into two different behaviors. One behavior is described by the variation of pH due to the photosynthesis phenomena made by microalgae; and the other comes from the effect of CO2 injections into the medium for control purposes. Moreover, it was observed that the model parameters vary throughout the day depending on the weather conditions and reactor status. Thus, a decision tree algorithm is also developed to capture the parameter variation based on measured variables of the system, such as solar radiation, medium temperature, and medium level. The proposed model has been validated for a data set of more than 100 days during 10 months in a semi-industrial raceway reactor, covering a wide range of weather and system scenarios. Additionally, the proposed model was used to design an adaptive control algorithm which was also experimentally tested and compared with a classical fixed parameter control approach.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Microalgas
Idioma:
En
Revista:
N Biotechnol
Asunto de la revista:
BIOLOGIA MOLECULAR
/
ENGENHARIA BIOMEDICA
Año:
2024
Tipo del documento:
Article
País de afiliación:
España
Pais de publicación:
Países Bajos