Teacher(s)
Language
English
Prerequisites
Courses in sustainability, environmental transition, macroeconomics, statistical analyses. Advanced courses in energy system analysis and energy economics, energy market analysis and regulation.
Main themes
Some of the topics treated in the course include:
- Future demand effects; energy efficiency, electrical vehicles, infrastructure investments
- Geopolitical analysis of energy sources and systems
- Industrial structure and locational analysis
- Technology and infrastructure development
- Global, regional and national energy models for forecasting (CLIMATIC, PRIME, JEDI, et al.)
- Forecasts of climate impact of energy system choices
Learning outcomes
At the end of this learning unit, the student is able to : | |
| The course takes a wholistic perspective on the energy in the society, economically, socially and environmentally. Looking at the energy policy objectives in terms of security of supply, environmental sustainability and economic affordability, the course critically examines the historic and current energy value chain. The course includes two additional perspectives: a geopolitical analysis of energy sources and technologies, and a supply chain perspective on industrial structure and locational development. After the course, the students should be familiar with and able to :
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Content
The course examines the energy transition from more than one discipline: system analysis, economics, policy, and the geopolitical and distributional conditions that decide what is feasible. Within the Energy Management major it is the transition course: the technologies are treated in LLSMS2051, and electricity market economics in LLSMS2052.
Europe has set emission targets and built instruments to meet them, mainly emissions trading and national targets under effort sharing. Whether they deliver depends on cost, on industrial competitiveness, and on how households and firms respond. Much of the manufacturing capacity for clean technology now sits in China, which changes what European industrial policy can achieve. For a firm, these are not background conditions: a carbon price, a border adjustment or a support scheme decides which investments clear and where production stays.
Topics treated include:
Note: The content of the course might be adjusted based on the availability of guest speakers.
Europe has set emission targets and built instruments to meet them, mainly emissions trading and national targets under effort sharing. Whether they deliver depends on cost, on industrial competitiveness, and on how households and firms respond. Much of the manufacturing capacity for clean technology now sits in China, which changes what European industrial policy can achieve. For a firm, these are not background conditions: a carbon price, a border adjustment or a support scheme decides which investments clear and where production stays.
Topics treated include:
- Emissions and energy trends: worldwide, EU and Belgian emissions by sector, global electricity and fossil fuel markets
- Energy balances: supply, transformation and consumption, primary against final energy, units and orders of magnitude
- Energy system models: cost optimisation, scenarios, and what levelised cost can and cannot settle
- Net-zero pathways for Belgium: buildings, transport, power and industry
- Externalities: instrument choice, prices against quantities under uncertainty
- Resource economics: optimal extraction, Hotelling, scarcity rents, backstop technologies
- Green growth: whether growth and emissions decouple, Kuznets curves, the Kaya identity, consumption-based emissions
- EU climate policy: targets, emissions trading, effort sharing, CBAM, progress against objectives
- Industrial policy and competitiveness: clean technology supply chains, China's position, European industry under pressure
- Clean molecules: hydrogen supply, cost, imports and the geopolitics of those imports
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, guest lectures, and company visits where these can be arranged.
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.
- Students are expected to attend company visits organized as part of the course and to actively engage when guest speakers are invited.
- 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.
- A minimum score of 10 out of 20 on the exam is required to pass the course.
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:- Which AI tool or tools were used
- For what purpose they were used, such as drafting text, generating ideas, or running code
- A short description of their own contribution, clarifying what was done by the student themselves versus the AI
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
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
Communication between the teachers and the students takes place through Moodle. Students should enrol in the course on Moodle to access course notes, slides and additional material.
This course is part of the Energy Management major. The technologies themselves are treated in LLSMS2051, and electricity market economics in LLSMS2052. The course is also suitable as a standalone elective for students who want a wider background in energy and climate policy.
Additional information on the major is available at https://www.bertwillems.com/energy-management-major/, a page maintained by the teacher.
This course is part of the Energy Management major. The technologies themselves are treated in LLSMS2051, and electricity market economics in LLSMS2052. The course is also suitable as a standalone elective for students who want a wider background in energy and climate policy.
Additional information on the major is available at https://www.bertwillems.com/energy-management-major/, a page maintained by the teacher.
Faculty or entity
