Duration
18h Th, 18h Pr, 24h Proj., 1d FW
Number of credits
| Master of Science (MSc) in Electrical Engineering | 5 crédits | |||
| Master of Science (MSc) in Electromechanical Engineering | 5 crédits |
Lecturer
Language(s) of instruction
English 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
Learning unit contents
Microgrids are localized grids that are operated in parallel from the main utility grid. They are developing strongly these days, mainly because the price of producing electricity next to the load is becoming in many part of the world cheaper than the retail price of electricity. Future microgrids are very likely to rely strongly on storage, renewable sources of energy and a smart management of the load. Power electronics will play a central role in the electrical structure of these microgrids.
This class is made of three main parts. However, the course is under constant evolution and is evolving towards a more practical content, considering practical implementations constraints, possibilities offered by IoT to monitor and control the load and learn from it, ways to store microgrid management related data, etc.
- The first part focuses on the modeling of microgrids components and microgrid topologies.
- The second part will focus on the optimal operation of microgrids so as to maximize its revenues and other objectives. For this part, different models of interaction of the microgrids with the main utility grid will be considered such as for example: a fully off-grid microgrid, a microgrid that can trade energy with other actors of the electrical system or a microgrid that can sell ancillary services to the main utility grid.
- The third part of the course will build on the first and second parts to determine how to size a microgrids from a clean sheet.
Learning outcomes of the learning unit
- To understand what are the main components of a microgrid and to get the basic knowledge for buidling one.
- To know how to optimize both the "behavior" of a microgrid and its sizing.
- To understand how microgrids can be integrated into the main utility grid.
Prerequisite knowledge and skills
- Basic knowledge of circuit theory, energy markets, and power systems.
- Prior exposure to optimisation and machine learning is a plus, but key notions will be introduced during the lectures.
- Scientific programming in Python
Planned learning activities and teaching methods
Short theoretical sessions. Implementation and experimentation by the student on computer aided simulation tools and in the lab. Q&A with the Professor and the teaching assistant.
Mode of delivery (face to face, distance learning, hybrid learning)
Short teaching sessions, face to face discussion of assignments.
Organisational adjustments related to the current health context
Lectures and exams will be organized remotely if needed.
Recommended or required readings
Course slides and other material are made available on eCampus along the year.
Recommended but not mandatory reading: Microgrids and other local area power and energy networks, Cambridge university press, 2016, A. Kwasinski, W. Weaver, R. Balog.
Assessment methods and criteria
Below you will find information on the evaluation methods planned for in-person and remote exams as well as those planned for hybrid sessions. Depending on how the health crisis evolves, the chosen method will be communicated to you no later than one month before the start of the exam session.
Oral exam at the end of the quadrimester and assignments along the quadrimester.
Work placement(s)
There will be no work placement but the students will work for their projects very closely with researchers of ULiège active in the field of microgrids.
Organizational remarks
The class is given during the first semester.
See www.montefiore.ulg.ac.be/~cornelusse for the course schedule and organization.