TEK9410 – Energy Markets and Regulation - Electricity System Modelling and Analysis
Course description
Course content
There is a wide-spread consensus on the urgency to achieve the headline goal of the Paris Agreement of keeping global warming to well below 2?C and in so doing avoid dangerous climate change. This requires a rapid decarbonisation of the energy system, which, as has been shown by modelling-based research, can be achieved by electrified and interconnected systems with a high share of variable renewable energy sources (VREs) (i.e. wind and solar) providing up to 100% of the total electricity output. ?In such electrified systems with high shares of VREs, weather and climate have an important and growing influence on the supply and demand of energy in Europe, from solar and wind generation to heating and cooling demands.
Electricity system models are used to advise policy makers and planners on how to design such highly renewable electricity systems.
In this course students will learn how to code their own electricity system model in GAMS so as to answer questions related to electricity markets and systems. We will start with a simple model and over the course add complexity via more constraints and technologies such as electricity storage.? Developing models requires preparing input data as well as making assumptions; students will learn to understand what data is required, where to find it, how to prepare it using Python, and how to use the data in their models. Students will learn how to run the models and interpret results. The course will focus on future systems with high shares of variable renewable energy sources within a European context.
Learning outcome
After completing this course, you
- know the basics of linear programing
- are able to define research questions on electricity system and market problems and to build model formulations to answer them
- are able to collect and prepare input data using Python
- are able to build your own electricity system model in GAMS and conduct the analysis
- are able to interpret model results
- are able to describe your modelling approach and results including shortcomings
- can read and critically analyze state-of-the-art literature based on electricity models
- are able to write a research report and present it to a specialized audience
- can relate and apply the knowledge gained in this course?to?improve your?own?PhD research.
Admission to the course
PhD candidates from the University of Oslo should apply for classes and register for examinations through?Studentweb.
If a course has limited intake capacity, priority will be given to PhD candidates who follow an individual education plan where this particular course is included. Some national researchers’ schools may have specific rules for ranking applicants for courses with limited intake capacity.
PhD candidates who have been admitted to another higher education institution must?apply for a position as a visiting student?within a given deadline.?
The courses?TEK5410 and?TEK9410 have common admission, with a maximum of 40 places.?Applicants are ranked by the following criteria:
Students with admission to the master's programme?Renewable Energy Systems (master) have priority.
PhD candidates at the MN faculty who have the course as part of the approved curriculum and visiting PhD candidates.
For the remaining places, students?will be given admission based on the regular rules (number of credits first, then?on?a first-come-first-served basis).
Recommended previous knowledge
The course links to the course TEK5350 – Energy Markets and Regulation. While TEK5350 is not a prerequisite, we advise you to go through the book Electricity Markets: Pricing, Structures and Economics before starting this course.
For those without previous knowledge in programming, we advise you to attend one of the workshops on Programming in Python organized by UiO.
Overlapping courses
- 10 credits overlap with TEK5410 – Energy Markets and Regulation - Modelling and Analysis.
Teaching
The course extends over a full semester with 3 hours of teaching every second week.?
Examination
- A portfolio assessment counts 75% towards the final grade
- A final oral exam counts 25% towards the final grade.
For PhD candidates, the portfolio assessment consists of assignments and a research report (4000 words). The portfolio assignments and the research report must be passed before you can sit the final oral exam.
When writing your exercises make sure to familiarize yourself with the rules for use of sources and citations. Breach of these rules may lead to suspicion of attempted cheating.
It will also be counted as one of the three attempts to sit the exam for this course, if you sit the exam for (one of) the following course(s):
Examination support material
No examination support material is allowed.
Language of examination
The examination text is given in English, and you submit your response in English.
Grading scale
Grades are awarded on a pass/fail scale. Read more about?the grading system.
Resit an examination
Students who can document a valid reason for absence from the regular examination are?offered a postponed examination at the beginning of the next semester.
Re-scheduled examinations are not offered to students who withdraw during, or did not pass, the original examination.
More about examinations at UiO
- Use of sources and citations
- How to use AI as a student
- Special exam arrangements due to individual needs
- Withdrawal from an exam
- Illness at exams / postponed exams
- Explanation of grades and appeals
- Resitting an exam
- Cheating/attempted cheating
You will find further guides and resources at the web page on examinations at UiO.