Duration
15h Th, 15h Pr, 6h AUTR
Number of credits
| Master in environmental bioengineering, professional focus | 4 crédits |
Lecturer
Language(s) of instruction
French language
Organisation and examination
Teaching in the first semester, review in January
Schedule
Units courses prerequisite and corequisite
Prerequisite or corequisite units are presented within each program
Learning unit contents
Energy and agro-ecological transitions are at the heart of environmental, health and food issues. In this respect, agriculture can play an accelerating role by developing new, resilient models that respond to societal expectations and ensure better remuneration for producers.
Among these, agrivoltaics, or agri-photovoltaics, is based on the use of the same land for both photovoltaic energy production and agricultural production. This practice offers attractive prospects for meeting the challenges of the water-energy-supply nexus. Indeed, if certain technological implementation conditions are met, total land productivity can be improved compared with disjointed systems, and water savings can be achieved. However, the multiple interactions between these components and the diversity of agro-pedoclimatic conditions call for the application of complex systems engineering techniques to study, optimize and operationalize the conditions for developing synergies as a function of system parameters.
Furthermore, to maintain the territory's food sovereignty, the agricultural function of the land must be maintained over the long term. This means ensuring that agricultural productivity remains sufficient, while maintaining attractive farm incomes. We therefore need to determine the technological conditions that will preserve the agricultural function, and ideally even provide it with beneficial services such as combating climatic hazards, erosion and pests, etc.
The course is based on the use of the open-source framework developed by the Digital Energy and Agriculture Lab "Python Agrivoltaic Simulation Environment" to model these systems. It makes use of existing experimental devices or those under development. The course can involve both theoretical and experimental aspects, depending on the project chosen by the students from among the proposals presented to them. In particular, the course is aimed at engineers who want to work in design offices or research units specializing in energy, agriculture and the environment.
Learning outcomes of the learning unit
During the proposed course, students will develop and demonstrate their ability to mobilize and reinforce their knowledge of environmental sciences and technologies, as well as their skills in agronomy and ecophysiology, around the design, modeling and optimization of an agrivoltaic project.
At the end of this course, students should be able to model a complex system in an environment representative of real-life conditions, study the influence of technological parameters on system performance indicators, carry out optimization and analyze stability under a variety of agro-pedo-climatic conditions. He/she will be able to apply concepts and methods enabling the design of a digital eco-solution to reduce the environmental impact of human activities in the field of bioengineering, using digital tools.
They will also be able to mobilize engineering sciences and operational technologies in a data-driven approach, using the concepts and methods of the digital twin.
Finally, he/she will be able to adopt good IT development practices in a collaborative development environment.
Prerequisite knowledge and skills
Physics (optics, mechanics, fluid mechanics, environmental physics,..)
Biology (plant physiology)
Chemistry (soils)
System dynamics and models
Object-oriented programming in Python
Planned learning activities and teaching methods
Ex cathedra class
Project
Mode of delivery (face to face, distance learning, hybrid learning)
Face-to-face course
Blended learning
Further information:
Hybrid
Course materials and recommended or required readings
Platform(s) used for course materials:
- Microsoft Teams
Further information:
https://gitlab.uliege.be/pase/pase_1.0/
Exam(s) in session
Any session
- In-person
oral exam
- Remote
oral exam
Written work / report
Further information:
Written report at the end of the course and oral presentation with specific support during the session