| Course label : |
Electromagnetic energy conversion and eco-design |
| Teaching departement : |
EEA / Electrotechnics - Electronics - Control Systems |
| Teaching manager : |
Mister STEPHANE BRISSET |
| Education language : |
|
| Potential ects : |
0 |
| Results grid : |
|
| Code and label (hp) : |
MR_E2D2_EEA_EEC - Electromagn energy conversion |
Education team
Teachers : Mister STEPHANE BRISSET
External contributors (business, research, secondary education): various temporary teachers
Summary
The design of complex systems is a key activity of the integrating engineer due to its multidisciplinary or even interdisciplinary nature. To deal with complexity, the designer uses optimization tools to find tradeoffs between conflicting objectives in the presence of multiple constraints. Among the objectives are economic criteria and more and more environmental criteria.
The objective of this course is to understand and master the tools for optimization and life cycle analysis. Students will use software widely used in industry, service and academia: Matlab Optimization Toolbox for optimization and EIME for life cycle assessment.
The example treated is the design by optimizing the energy system of an smart building with renewable energies and energy storage. Through practical work, students will achieve optimal energy management, build an environmental model and then find the optimal trade-offs between the cost of ownership and greenhouse gas emissions under operational constraints.
Educational goals
At the end of the course, the student will be able to:
- Perform a life cycle analysis
- Carry out an optimization and eco-optimization process
At the end of the course, the student will have progressed in knowledge and skills:
- Life cycle thinking or the need to design more completely by quantifying the environmental impacts from cradle to grave
- Mastery of the EIME life cycle analysis software
- The optimization process, the formulation of an optimization problem, the criteria for optimality
- Optimization algorithms: diversity, operating principle, characteristics, complementarity
- Optimization approaches: multi-granularity, multidisciplinary, systemic
- The mastery of Matlab Optimization Toolbox: model formatting, algorithm configuration, optimization problem specification, advanced programming
Sustainable development goals
Knowledge control procedures
Continuous Assessment
Comments: Work during the sessions and report of the practical works.
Online resources
All course materials, practical work wordings, and Matlab examples.
Pedagogy
This course will be built around a "common thread" that is an smart building that both produces and consumes energy. Optimal storage and management of energy allow a better rate of self-consumption with positive economic and environmental benefits. In the end, all the trade-offs between economic and environmental aspects are found.
Optimization course: 8 hours
Practical work on optimization: 4 hours
Course on eco-design and life cycle analysis: 2 hours
Practical work on life cycle analysis and eco-optimization: 4 hours
Sequencing / learning methods
| Number of hours - Lectures : |
32 |
| Number of hours - Tutorial : |
4 |
| Number of hours - Practical work : |
14 |
| Number of hours - Seminar : |
0 |
| Number of hours - Half-group seminar : |
0 |
| Number of student hours in TEA (Autonomous learning) : |
0 |
| Number of student hours in TNE (Non-supervised activities) : |
0 |
| Number of hours in CB (Fixed exams) : |
0 |
| Number of student hours in PER (Personal work) : |
0 |
| Number of hours - Projects : |
0 |
Prerequisites
Programming basis.
Maximum number of registrants
Remarks