Energy System Analysis

llsms2051  2025-2026  Louvain-la-Neuve

Energy System Analysis
5.00 credits
30.0 h
Q2
Language
English
Prerequisites
Undergraduate courses in energy systems from a technical perspective, microeconomics, systems analysis.
Main themes
Some of the topics treated in the course include:
o Central energy management for generation
o Generation technologies
o Energy transmission and distribution
o Energy storage
o Energy sources, location and constraints.
o Local energy management
o Energy economics, cost function for generation, transmission and distribution.
o New technologies
o Market actors and locations
o Technical regulation of generation and transport
Learning outcomes

At the end of this learning unit, the student is able to :

The course provides a techno-economic basis for students to understand the energy generation, storage, transmission, distribution and consumption from a system-economic perspective.  The scope includes gas and electrical systems and their specificities.  
After the course, the students should be able to understand in the techno-economic interactions of various actors and processes in the energy system.
In terms of methodology, the students should be able to perform managerial energy economic analyses using tools and approaches that are applied in the sector. 
 
Content
Some of the topics treated in the course include:
o Central energy management for generation
o Generation technologies
o Energy transmission and distribution
o Energy storage
o Energy sources, location and constraints.
o Local energy management
o Energy economics, cost function for generation, transmission and distribution.
o New technologies
o Market actors and locations
o Technical regulation of generation and transport
Note: The content of the course might be adjusted based on the availability of guest speakers.
Teaching methods
Ex-cathedra lectures, lectures with active student participation (such as group work, computer simulations, and student presentations), and guest lectures if possible.
Evaluation methods

Grading Structure

  • Participation (30 percent)
    Participation includes group work, student presentations, and active involvement in class activities.
    • Students are expected to attend company visits organized as part of the course and to actively engage when guest speakers are invited.
    • Failure to actively participate will result in a lower participation grade.
    • The participation grade is final and cannot be retaken.
  • Exam (70 percent)
    A written exam will take place at the end of the course.
    • A minimum score of 10 out of 20 on the exam is required to pass the course.
    • If a resit is necessary, the format may be adapted, for example, the resit may be conducted as an oral exam.

Use of AI Tools

AI tools may be used for assignments and preparation unless explicitly stated otherwise for a specific task. If AI is used, students must clearly state this in their submission, briefly describing:
  1. Which AI tool or tools were used
  2. For what purpose they were used, such as drafting text, generating ideas, or running code
  3. A short description of their own contribution, clarifying what was done by the student themselves versus the AI
Recording all prompts or outputs is not required, but students should keep a record of key steps if the instructor requests clarification.
Responsibilities when using AI:
Students remain fully responsible for the quality and integrity of their work. They must:
  • Understand and verify all results, calculations, and arguments included in their submission
  • Be able to present and explain their work, including any AI-generated parts, during discussions or presentations
  • Ensure they have read and understood all references and source materials cited in their work
  • Check the correctness of all derivations, code, and factual claims
  • Avoid entering personal or confidential information into AI systems
Failure to meet these responsibilities may negatively affect the assignment grade, even if AI use is properly disclosed.

Late Submission Policy

Late submissions of assignments will result in a grade deduction, with the exact penalty depending on how late the submission is.
  • Submissions that are several days late may not be accepted, unless prior arrangements have been made with the instructor.
  • Exceptions will only be considered in documented cases of illness or other serious circumstances.

Free Riding Policy

All group members are expected to contribute actively and fairly to group assignments.
  • Free riding will result in a full grade deduction on the assignment for the student concerned.
  • Instances of free riding should be reported in Moodle.
  • Groups are encouraged to keep a simple record of contributions such as meeting notes or task lists to clarify responsibilities if disagreements arise.
Other information
The communication between the professor and the students takes place through the electronic platform Moodle. You should enroll in the course on Moodle to have access to the online documents such as course notes, slides and additional material that will be posted.
Faculty or entity


Programmes / formations proposant cette unité d'enseignement (UE)

Title of the programme
Sigle
Credits
Prerequisites
Learning outcomes
Master [120] : Business Engineering

Master [120] : Business Engineering