Optimization in modern power systems

M.Sc - DTU

3–6 Months

Masters of Science Programes

Course Overview

Operating a complex system such as the power grid requires making informed decisions under uncertainty and risk, whether defining optimal market clearing for electricity and ancillary services, identifying strategic bidding strategies for producers, or determining long-term investments for grid operators. In each case, decision-makers must ask: What is the best possible outcome? What actions lead to it? What are the trade-offs and constraints? This course equips students with the tools to answer these questions by introducing the fundamental principles of optimization techniques, with a focus on their application to real-world decision-making problems in power systems.

Main Goal

Students will gain a deep understanding of linear programming and convex optimization, duality theory, complementarity modelling, and optimization techniques under uncertainty, and learn how to apply these tools to a range of real-world challenges in power systems.

Skills to be Gained

The course emphasizes computational thinking and model-based reasoning as foundational skills for formulating and solving decision-making problems using mathematical optimization.

Practical Notes

Contact details: lemitri@dtu.dk

Date:

August 2025

Period:

Expected duration:

3–6 Months

Format:

Hybrid

Level:

Advanced

Language of instruction:

English

Requirements:

Course 46700/46705/02402/42112/42101 at DTU, or equivalent. Solid programming skills (Python, Julia or similar) are expected, since programming is an essential part of the course assignments. It is highly recommended that students are familiar with the fundamentals of electric power systems modelling and operation, including balanced three-phase circuits, power system components modelling, and power flow equations, and electricity markets organisation.

Teaching and assessment methods:

The course combines hybrid and flipped classrooms, hands-on coding exercises, collaborative projects and peer discussions, and tailored board games to foster intuition, creativity and a deeper understanding of complex optimization techniques. Overall assessment based on: i) Participation in individual exercises and peer-feedback sessions; ii) Two group assignments (deliverables include reports, project code, and individual contribution tables); iii) Oral group exam involving group presentation and individual questions on assignments and course curriculum.

Registration Price:

To be updated

Registration deadline:

To be updated

Instructors

Lesia Mitridati