PRIN 2022 / Bezzo


Acronimo: PhotoControl
Titolo: A knowledge-based approach to automatic control and optimisation of photosynthetic bioprocesses
Coordinatore: prof. Fabrizio BEZZO- Dipartimento di Ingegneria Industriale-Università degli Studi di PADOVA
Partner-Unità di ricerca: Università degli Studi di PALERMO
Bando: PRIN 2022 - Decreto Direttoriale n. 104 del 02-02-2022
Durata: 28/09/2023 - 27/09/2025 (24 mesi)
Budget totale progetto: € 248.765,00

Abstract del progetto

Microalgae represent a highly promising source for food, feed, chemicals, and fuels. However, despite the enormous potential and the impressive R&D effort, industrial use of microalgae is still at its first developmental stage, with significant capital investment that is not compensated for by underperforming productivity. A fundamental reason for such poor results depends on unsatisfactory light conversion efficiency, which in industrial facilities is 5-10 times lower than the theoretical one, and on non-optimal management of input variables (e.g. nutrients). A major step forward can derive by the development and implementation of advanced control strategies, capable of automatizing and optimising culture conditions at industrial scale, exploiting effectively and synergically all control variables. PhotoControl aims at setting up a comprehensive and multidisciplinary research effort targeting two goals: 1. Definition of a reliable digital twin of microalgae growth that can be used as a virtual prototype to simulate and optimise process operation; 2. A model-based control strategy capable of exploiting all available control variable and sensors in an optimal way, integrating first principle modelling and machine learning approaches. Enhancing light efficiency in industrial cultivation systems is at the core of the project: artificial light such as light emitting diodes (LED) will be employed to assess and optimise light intensity and wave length as well as the frequency of light-dark cycles. Furthermore, the effect of nutrients and their interaction with the photosynthetic response will be assessed and optimised to boost microalgae growth and the yield of value-added metabolites. PhotoControl will pave the way towards a knowledge-based breakthrough in biological modelling and simulation, and automatic control, and will deliver tools and a methodology to speed up microalgae technology from lab to industrial equipment, and to increase profitability in the microalgae production sector.