Course - Energy Markets - IØ8303
IØ8303 - Energy Markets
Examination arrangement: Home examination
Grade: Letter grades
|Evaluation||Weighting||Duration||Grade deviation||Examination aids|
|Home examination||100/100||24 hours|
One part of the PhD class on Energy Markets provides an in-depth overview of the main economic models of energy markets. The other part of the class will focus on the energy resource markets for coal, oil, and natural gas. The course will offer detailed insights into the markets' value chains and challenges. It will link the technical characteristics of the value chains to the market organization. Different analytical concepts will be introduced to support a well-founded economic analysis of the sectors, such as game theory and institutional economics (contract theory). Moreover, for each sector, a numerical model will be introduced.
Position and function in the PhD program:
The course is meant for PhD students in management science, broadly defined. We assume that students have a foundation in selected areas of finance and optimization, comparable to a Master of Science in Industrial Economics and Technology Management. Specifically we build on courses having subjects such as microeconomics, equilibrium models (microeconomics) and real options analysis. The course audience is PhD students having an interest in computational equilibrium models, energy and environment in the interface between energy economics and technical systems analysis, and investment under uncertainty. It will give the students in-depth knowledge and a competence foundation making them able to participate in research processes so they can develop new knowledge within the area.
After following this course the student should:
- have knowledge about regulation and market mechanisms in electricity, natural gas, coal and oil markets.
- have knowledge about theory of investment under uncertainty in energy projects.
- be able to discuss uses and models for advanced analysis of energy systems and markets and be familiar with model classes, features and drivers.
- be able to model and discuss the links between markets and the physical characteristics of underlying technologies.
Learning methods and activities
The class will be a mixture of lectures, small assignments, presentations and discussions of topical subjects. Required reading has to be prepared for each class, and recommended reading will additionally be provided.
Attendance: Students are expected to be present and prepared for every class session. Active participation during lectures and seminar discussions is essential.
Homework assignments: For each course day (except the very first one), you are given assignments to be prepared in advance. In general, these are questions related to the mandatory reading. Small parts of the assignments may also be related to current news topics. Homework assignments must be submitted before the course day by email or on paper.
Homework assignments are graded approved/not approved. Non-submitted assignments and assignments with less than 50% of the expected answers are graded not approved. You need to have a minimum of homework assignments approved in order to be admitted to the final exam.
Two oral presentations: Each student must give two 15-20 minute presentations on a piece of literature, one for each part of the class. You can choose from the additional readings given for each session or freely select an academic paper on the course topics (you may be the author or not). The presentations will be part of the sessions and will be scheduled according to the topics so as to fit in the class' programme.
Further on evaluation
Homework assignments: Graded approved/not approved, and is a condition in order to be admitted to the final exam.
Compulsory activities from previous semester may be approved by the department.
Recommended previous knowledge
TIØ4117 Microeconomics and TIØ4126 Optimization and Decision Support for Industrial Business Planning.
Scientific articles and selected literature. Given at course start-up.
Credits: 10.0 SP
Study level: Doctoral degree level
Term no.: 1
Teaching semester: AUTUMN 2022
Language of instruction: English
- Managerial Economics, Finance and Operations Research
- Finance and Managerial Economics
- Industrial Economics and Technology Management
- Business Economics
- Business Econimics and Management
- Technological subjects
Department with academic responsibility
Department of Industrial Economics and Technology Management
Examination arrangement: Home examination
- Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
- Autumn ORD Home examination 100/100 INSPERA
Room Building Number of candidates
- * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
For more information regarding registration for examination and examination procedures, see "Innsida - Exams"