Digital Energy Systems - Specialization
Digital Energy Systems
In the Digital Energy Systems specialization, students gain deep expertise in modern energy systems and learn to apply optimization, machine learning, and data-driven methods for optimal control, operation, and planning. The program also provides broad insight into the role of digital technologies in future energy systems with a high share of renewable energy sources.
Graduates are prepared to make informed operational, trading, and planning decisions using advanced modeling and analytics. They are highly sought after across the energy sector, including roles with system operators, utilities, technology developers, manufacturers, consultancies, and start-ups.
As energy systems become more digital and data-centric, professionals in this field are essential to delivering smart and sustainable energy solutions at both national and global levels.
Polytechnic foundation courses (10 ECTS):
The following courses are mandatory:
| 12100 | Quantitative methods to assess sustainability (Polytechnical Foundation) | 5 | point | F7 (Tues 18-22) |
| or | ||||
| 12106 | Quantitative methods to assess sustainability (Polytechnical Foundation) | 5 | point | Autumn E3B (Fri 13-17) |
| or | ||||
| 12105 | Quantitative methods to assess sustainability (Polytechnical Foundation) | 5 | point | E7 (Tues 18-22) |
| or | ||||
| 12101 | Quantitative methods to assess sustainability (Polytechnical Foundation) | 5 | point | Spring F3B (Fri 13-17) |
| 42500 | Innovation in Engineering (Polytechnical Foundation) | 5 | point | January |
| or | ||||
| 42504 | Innovation in Engineering (Polytechnical Foundation) | 5 | point | August |
| or | ||||
| 42501 | Innovation in Engineering (Polytechnical Foundation) | 5 | point | June |
Students with advanced innovation competences may take one of the following courses as an alternative to 42500/42501/42504:
| 42502 | Facilitating Innovation in Multidisciplinary Teams | 5 | point | January |
| or | ||||
| 42505 | Facilitating Innovation in Multidisciplinary Teams | 5 | point | August |
| or | ||||
| 42503 | Facilitating Innovation in Multidisciplinary Teams | 5 | point | June |
The following course can be taken as an alternative to the mandatory course 12100/12106/12105/12101:
| 41636 | Design for Circular Economy | 5 | point | January |
Programme-specific courses (50 ECTS)
Innovation Course II: Select one of the following courses (5 ECTS):
| 38102 | Technology Entrepreneurship | 5 | point | Autumn E1B (Thurs 13-17) |
| 42014 | Environmental and Resource Economics | 5 | point | F7 (Tues 18-22) |
| 42015 | Energy Economics | 5 | point | Autumn E3B (Fri 13-17) |
| 42016 | Business Economics and Finance | 5 | point | Spring F3B (Fri 13-17) |
The following three courses are compulsory components of the programme (15 ECTS in total):
| 46205 | Feasibility studies of energy projects | 5 | point | Autumn E3A (Tues 8-12) |
| 46740 | Distributed energy technologies, modelling and control | 5 | point | Spring F1B (Thurs 13-17) |
| 46770 | Integrated energy grids | 5 | point | Spring F5A (Wed 8-12) |
The following courses are mandatory for the specialization (10 ECTS in total):
| 46750 | Optimization in modern power systems | 5 | point | Autumn E5A (Wed 8-12) |
| 46765 | Machine learning for energy systems | 5 | point | Autumn E5B (Wed 13-17) |
Choose at least 10 ECTS from the following courses in machine learning, operations research, programming, and energy markets:
| 02452 | Machine Learning | 5 | point | Autumn E4A (Tues 13-17) |
| or | ||||
| 02180 | Introduction to Artificial Intelligence | 5 | point | Spring F3A (Tues 8-12) |
| 02476 | Machine Learning Operations | 5 | point | January |
| or | ||||
| 02807 | Computational Tools for Data Science | 5 | point | E7 (Tues 18-22) |
| 42112 | Mathematical Programming Modelling | 5 | point | January |
| or | ||||
| 42114 | Integer Programming | 5 | point | Autumn E4A (Tues 13-17) |
| 46120 | Scientific Programming for Wind Energy | 5 | point | Spring F2B (Thurs 8-12) |
| 46755 | Renewables in electricity markets | 5 | point | Spring F2A (Mon 13-17) |
Choose at least 5 ECTS from the following technology-related courses:
| 34552 | Photovoltaic systems | 5 | point | Spring F2B (Thurs 8-12) |
| 41418 | Green fuels and power-to-x | 5 | point | Spring F3A (Tues 8-12) |
| 41468 | Sustainable District Heating | 5 | point | Spring F1A (Mon 8-12) |
| 46200 | Planning and Development of Wind Farms | 5 | point | January |
| 47301 | Hydrogen energy and fuel cells | 5 | point | Spring F1B (Thurs 13-17) |
| 47330 | Energy storage and conversion | 5 | point | Autumn E1A (Mon 8-12) |
| 47334 | Carbon capture, utilization, and storage | 5 | point | Spring F3A (Tues 8-12) |
Choose at least 5 ECTS from the following courses:
| 02417 | Time Series Analysis | 5 | point | Spring F4B (Fri 8-12) |
| 02435 | Decision-Making Under Uncertainty | 5 | point | Spring F4A (Tues 13-17) |
| 02619 | Model Predictive Control | 5 | point | Autumn E2B (Thurs 8-12) |
| 46705 | Power grid analysis | 5 | point | Spring F3A (Tues 8-12) |
Elective courses (30 ECTS):
Any course classified as MSc-level in DTU’s course catalogue may be taken as an elective. This also includes programme-specific courses beyond the minimum requirements listed above. Master’s students may count up to 10 ECTS from DTU bachelor-level courses or equivalent courses from other higher education institutions. Additionally, MSc-level courses from other Danish or international universities can be included as electives.
In addition to the programme-specific courses mentioned above, the following elective courses are suggested for this specialization:
| 02431 | Risk Management | 5 | point | January |
| 02456 | Deep learning | 5 | point | Autumn E2A (Mon 13-17) |
| 02582 | Computational Data Analysis | 5 | point | Spring F2B (Thurs 8-12) |
| 41417 | Digitalization of Thermal Energy Technologies – Modelling and Simulation Methods | 5 | point | Autumn E1B (Thurs 13-17) |
| 42136 | Large Scale Optimization using Decomposition | 5 | point | Spring F2B (Thurs 8-12) |
| 42186 | Model-based machine learning | 5 | point | Spring F5B (Wed 13-17) |
| 42577 | Introduction to Business Analytics | 5 | point | Autumn E1A (Mon 8-12) |
| 46200 | Planning and Development of Wind Farms | 5 | point | January |
| 46500 | Probabilistic Methods in Wind Energy | 5 | point | Autumn E2A (Mon 13-17) |
| 46700 | Introduction to Electric Power Systems | 10 | point | Autumn E4 (Tues 13-17, Fri 8-12) |
| 46745 | Integration of wind power in the power system | 5 | point | Autumn E3B (Fri 13-17) |
| 47341 | AI4Materials: Artificial Intelligence for Accelerated Materials Design and Discovery | 10 | point | Autumn E5 (Wed 8-17) |
Master's thesis (30 ECTS):
The MSc thesis must be conducted within the area of the specialization. The project may be completed in collaboration with a relevant company.
Specializations are recommended pathways for selecting courses within the curriculum. Applicants are admitted to the programme and not to a specific specialization and may choose any courses within the curriculum according to the guidelines provided. However, if the requirements for a specialization are completed, the specialization title may be added to the diploma.
Study track responsible
Lesia Mitridati Assistant Professor Mobile: +45 31964979 lemitri@dtu.dk