AØKA08243U Energy Economics of the Green Transition

Volume 2024/2025

MSc programme in Economics – elective course

Students enrolled at the Master programme and the 3rd year of the Bachelor programme can take the course.

Bacheloruddannelsen i økonomi – valgfag på 3. år

The Danish BSc programme in Economics - elective at the 3rd year


The course provides an understanding of the challenges associated with the transition from fossil-based fuels to renewable energy, considering both the supply and demand side of energy markets. This includes the technological challenges of introducing renewable energy in the energy system and the regulatory challenges of designing optimal policies to facilitate the transition. While the course generally deals with the several energy markets, special emphasis is placed on electricity markets due to the significant role of electricity in a carbon neutral energy system.


The course applies theory and analytical tools from microeconomics, macroeconomics, and econometrics. A large part of the course is also based on numerical structural models of the energy system.


The exam consists of a written assignment on a relevant topic chosen by the students. The exam paper has to based on a formal analysis, but the student is free to choose if the paper is mainly theoretical, quantitative, or econometric.


Learning Outcome

After completing the course, the student should be able to:



  • Account for the structure of the main energy markets and the differences between them.
  • Account for the key pathways in the transitition to renewable energy, including direct and indirect electrification.
  • Account for the main technical challenges for an energy system that increasingly relies on intermittent renewable energy.
  • Identify and discuss the economic effects of expanding generating capacity based on intermittent energy sources.
  • Account for the potential technologies aimed at solving the challenges of intermittent energy supply and assess their potential for mitigating the costs of intermittency.
  • Discuss the price responsiveness of short-run energy demand along with its determinants and evaluate the corresponding policy implications of making energy demand more elastic.
  • Discuss the concept of network effects and asses the implications for green technology adoption.
  • Discuss the energy efficiency gap and identify the corresponding optimal policy to foster investments in green technologies.
  • Discuss and evaluate optimal and second-best policies for reducing energy related emissions, including a discussion of the main European and Danish energy- and climate policies.



  • Characterize and formulate models of the electricity system with/without intermittency, cross-border trade, energy storage, coupled energy markets (e.g. hydrogen and district heating systems), and long-run planning of generation capacity.
  • Master linear programming by both deriving first-order conditions characterizing the optimal solution as well as numerically solving linear programming models of the energy system.
  • Numerially solve and structurally estimate non-linear models of the energy system.
  • Evaluate the cost-effectivenes of energy- and climate policies such as carbon taxes, cap-and-trade systems, technology subsidies, feeed-in-tariffs, and renewable energy targets.



  • Perform advanced model analyses of the energy system.
  • Perform a comprehensive critical evaluation of the strengths and weaknesses of energy market designs.
  • Evaluate and suggest energy- and climate policies targeting the energy sector.
  • Machiel Mulder: “Regulation of Energy Markets: Economic Mechanisms and Policy Evaluation” Springer 2021, ISBN: 978-3-030-58321-7.
  • Anna Cretí and Fulvio Fontini: “Economics of Electricity: Markets , Competition and Rules” Cambridge University Press 2019, ISBN: 978-1-316-88461-4.
  • Jonathan M. Harris and Brian Roach: “Environmental and Natural Resource Economics: A Contemporary Approach”, Routledge 2021, ISBN: 978-0-367-53138-6. (Chapter 11)
  • Selected papers from the research frontier of Energy Economics.
  • A handful of lecture notes on electricity system modeling.
The student should have followed courses similar to “Microeconomics I” and “Microeconomics II”, “Macroeconomics I” and “Macroeconomics II”, “Mathematics A” and “Mathematics B”, “Probability theory and statistics” and “Econometrics I” at the Bachelor of Economics, University of Copenhagen. It is also highly receommeded that students have programming experience in Python. Part of the requirements for registering for the exam is to pass an exercise from the exercise classes based on formulating and solving a numerical electricity system model programmed in Python. Note, however, that it is not required to use programming in the exam paper.
Lectures and exercise classes.

Lectures present relevant theory, models, and empirics.. Roughly half of the lectures are centered around structural models of the electricity system.. The other half of the lectures deal with other aspects of transitioning to net-zero emissions through selected papers on the research frontier of Energy Economics.

As a complement to the ordinary lectures, the course includes guest lectures by Danish industry experts and/or policy makers, who discuss relevant topics suchs as the recent energy crises and the decarbonization of the Danish energy sector.

In exercise classes students will formulate, solve, and estimate structural models of the energy system. The models are programmed in Python, but students are allowed to use other software if preferred. Students will also solve analytical models within the field of energy economics by using the standard mathematical methods for static optimization.
3 hours lectures every week and 2 hours exercise classes from week 36 to 50 (except week 42).

Timetable and venue:
To see the time and location of lectures please press the link under "Timetable"/​"Se skema" at the right side of this page (E means Autumn).

You can find the similar information partly in English at
-Select Department: “2200-Økonomisk Institut” (and wait for respond)
-Select Module:: “2200-E24; [Name of course]”
-Select Report Type: “List – Weekdays”
-Select Period: “Efterår/Autumn”
Press: “ View Timetable”

Please be aware:
- The schedule of the lectures can change without the participants´ acceptance. If this occures, you can see the new schedule in your personal timetable at KUnet, in the app myUCPH and through the links in the right side of this course description and the link above.
- It is the students´s own responsibility continuously throughout the study to stay informed about their study, their teaching, their schedule, their exams etc. through the curriculum of the study programme, the study pages at KUnet, student messages, the course description, the Digital Exam portal, Absalon, the personal schema at KUnet and myUCPH app etc.
  • Category
  • Hours
  • Lectures
  • 42
  • Class Instruction
  • 24
  • Preparation
  • 100
  • Project work
  • 40
  • Total
  • 206
Peer feedback (Students give each other feedback)

The students receive oral feedback from the lecturers during lectures.

Students are provided with exercises that can be solved using the Python implementations of core models; Oral feedback on these will be available during lectures as well.

The students may attend the biweekly office hours during the semester to discuss ideas for the exam paper

7,5 ECTS
Type of assessment
Written assignment, 4 weeks
Type of assessment details
It is possible to collaborate up to 3 persons.
The exam assignment is in English and must be answered in English.
Exam registration requirements

Students should pass two selected exercises from the exercise classes. At least one of these exercises will be based on programming a structural model of the electricity system.

If students do not pass in the first try, they will get a second try.


All aids allowed at the written exams.


Use of AI tools is permitted. You must explain how you have used the tools. When text is solely or mainly generated by an AI tool, the tool used must be quoted as a source.



Marking scale
7-point grading scale
Censorship form
No external censorship
for the written exam.
Exam period


Exam information:

More information is available in Digital Exam from the middle of the semester. In special cases decided by the Department, the exam can change to another day and/or time than announced. 


More information about examination, rules, aids etc. at Master (UK), Master  (DK) and Bachelor (DK).


The reexamination form is the same as the ordinary exam. Written exam with 4 weeks duration.


Reexam info:

More information in Digital Exam in February. 


More info: Master(UK),Master(DK), Bachelor(DK).

Criteria for exam assesment

Students are assessed on the extent to which they master the learning outcome for the course.


In order to obtain the top grade "12", the student must with no or only a few minor weaknesses be able to demonstrate an excellent performance displaying a high level of command of all aspects of the relevant material and can make use of the knowledge, skills and competencies listed in the learning outcomes.


In order to obtain the passing grade  “02”, the student must in a satisfactory way be able to demonstrate a minimal acceptable level of  the knowledge, skills and competencies listed in the learning outcomes.