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2024/2025  KAN-CCMVV2429U  Energy System Economics and Modelling

English Title
Energy System Economics and Modelling

Course information

Language English
Course ECTS 7.5 ECTS
Type Elective
Level Full Degree Master
Duration One Semester
Start time of the course Autumn
Timetable Course schedule will be posted at calendar.cbs.dk
Study board
Study Board for cand.merc. and GMA (CM)
Course coordinator
  • Alexandra Lüth - Department of Economics (ECON)
Main academic disciplines
  • Economics
Teaching methods
  • Face-to-face teaching
Last updated on 05-02-2024

Relevant links

Learning objectives
This course is designed to equip students with the knowledge and skills to support businesses and policymaking in transitioning to low carbon energy supply. The energy sector is one of the largest and most critical sectors in the economy, and reforming it is crucial to mitigating climate change. In this course, you will gain a deep understanding of energy systems and learn how to critically analyse and support the development of renewable and sustainable energy systems, markets, and businesses. You will be able to use your knowledge to drive the green transition and support mitigating climate change.

The aim of this course is to enable the students to:
  • Demonstrate a comprehensive knowledge of the fundamentals of energy system economics
  • Use techno-economic analysis to quantitatively assess questions on energy systems using real-world data
  • Understand and interpret the strengths and weaknesses of large energy system and market models
  • Apply the basics of energy systems modelling in the programming language Julia
Course prerequisites
Mandatory prerequisites: Basic understanding of principles of Microeconomics. Basic experience with a programming language is ideal. Interest in Energy Economics, green transition, and quantitative analysis.
Energy System Economics and Modelling:
Exam ECTS 7,5
Examination form Oral exam based on written product

In order to participate in the oral exam, the written product must be handed in before the oral exam; by the set deadline. The grade is based on an overall assessment of the written product and the individual oral performance, see also the rules about examination forms in the programme regulations.
Individual or group exam Oral group exam based on written group product
Number of people in the group 4
Size of written product Max. 10 pages
Groups of 3-4 students

Max. 10 A4-pages
Assignment type Case based assignment
Release of assignment Subject chosen by students themselves, see guidelines if any
Written product to be submitted on specified date and time.
10 min. per student, including examiners' discussion of grade, and informing plus explaining the grade
Grading scale 7-point grading scale
Examiner(s) Internal examiner and second internal examiner
Exam period Winter
Make-up exam/re-exam
Same examination form as the ordinary exam
Re-take exam is to be based on the same report as the ordinary exam:

*if a student is absent from the oral exam due to documented illness but has handed in the written groupproduct she/he does not have to submit a new product for the re-take.

*if a whole group fails the oral exam they must hand in a revised product for the re-take.

*if one student in the group fails the oral exam the course coordinator chooses whether the student willhave the oral exam on the basis of the same product or if he/she has to hand in a revised product for there- take.
Description of the exam procedure

For the case-based assignment, students will be asked to hand in ten presentation slides of their case, a data description of the data they use (template is given) and their Julia script.

Course content, structure and pedagogical approach

One of humanity’s greatest challenges is the transition towards a low-carbon energy supply. To achieve this transition the energy sector needs to undergo significant restructuring processes. This course teaches you topics related to the design of energy, and especially electricity markets and systems with a high proportion of renewable electricity generation seen as a key element to mitigate climate change and protect future generations.


Following a general introduction to the energy sector, various special features of renewable energy and their impact on the functioning of the sector are introduced. The course will use cases and examples from current developments, such as wind energy expansion, the future hydrogen sector design, and decarbonisation of transport, and enable students to develop skills in assessing analytical results to guide businesses and policymakers in their energy strategies. The course teaches the open-source programming language Julia and the use of open data platforms like the Open Power System Data (OPSD) platform to provide a tool for the analysis of renewable energy systems.


The course is divided into two main parts. In the first part, you will attend weekly lectures that cover basics in energy economics. These lectures focus on techno-economic analysis using numerical optimization and emphasize ambiguity stemming from simplified models. In the second part, you will work on programming exercises about sample cases along the course’s material to prepare for your case-based assignment and the oral exam.



  • Introduction to the energy system and renewable energy sources
  • Introduction to energy systems modelling
  • Presentation of models for the analysis of energy systems using energy systems modelling
  • Use of cases and current examples from the energy sector to illustrate the use of energy system models



  • Introduction to Julia programming language
  • Programming exercises
  • Working with cases and small models
  • Discussion of group work



This module is endorsed by the Copenhagen School of Energy Infrastructure (CSEI) at CBS and it is embedded in its overall strategy of research and education. CSEI is directly supported by the European Commission (DG Energy).

Description of the teaching methods
There will be lectures where students are expected to participate actively, and case-based seminars/lectures.
Feedback during the teaching period
Through oral discussions in class, office hours, voluntary mid-term assignment

Student workload
Lectures 30 hours
Project and exam preparation 93 hours
Reading and preparation 80 hours
Exam 3 hours
Expected literature


Expected literature

Selected Chapters from:

Bhattacharyya, S.C. (2019), Energy Economics: Concepts, issues, markets and governance, 2nd ed., Springer.


Kirschen D.S. and Strbac, G. (2018), Fundamentals of Power System Economics, 2nd ed., John Wiley & Sons, Ltd.


Kwon, C. (2019), Julia Programming for Operations Research: A primer on computing, 2nd ed.


Stoft, S. (2002), Power System Economics: Designing markets for electricity, New York: Wiley.



Bezanson, J., Karpinski, S., Shah, V. B., & Edelman, A. (2012). Julia: A fast dynamic language for technical computing. arXiv preprint arXiv:1209.5145.


Dunning, I., Huchette, J., and Lubin, M. (2017), JuMP: A modeling language for mathematical optimization, SIAM Review, 59(2), 295-320.


Weibezahn, J. and Kendziorski, M. (2019), Illustrating the benefits of openness: A large-scale spatial economic dispatch model using the Julia language, Energies, 12(6), 1153.


Sinn,H.-W. (2017). Buffering volatility: A study on the limits of Germany’s energy revolution. European Economic Review, 99, 130–150.


Egerer, J., Weibezahn, J., & Hermann, H. (2016). Two price zones for the German electricity market—Market implications and distributional effects. Energy Economics, 59, 365–381.


Schill, W.-P., & Zerrahn, A. (2018). Long-run power storage requirements for high shares of renewables: Results and sensitivities. Renewable and Sustainable Energy Reviews, 83, 156–171.

Course material

Collection of articles and policy reports


Last updated on 05-02-2024