Digital Energy Systems - Specialization
Digital Energy Systems
In the specialization Digital Energy Systems, the students achieve a good understanding of the energy system and learn how optimization, machine learning, and data-driven methods can be exploited for the optimal operation and planning of energy systems. Further, the students will gain a broad understanding of the role of digital solutions in future modern energy systems with high penetration of renewable energy sources.
The graduates will be able to make optimal operational, trading, and planning decisions for plants or energy systems using advanced modelling, optimisation, machine learning and data-driven methods. Graduates in the specialzation Digital Energy Systems are highly qualified candidates for jobs in the energy sector including system operators, utilities, developers, manufacturers, consultancy companies, and start-ups. Digital solutions driven by big data availability in modern energy systems are playing an increasingly important role in sustainable energy and are expected to contribute significantly to the energy supply nationally and worldwide.
Polytechnic foundation courses (10 ECTS):
The following courses are mandatory:
| 12100 | Quantitative Sustainability (Polytechnical Foundation) | 5 | point | F7 (Tues 18-22) |
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| 12106 | Quantitative Sustainability (Polytechnical Foundation) | 5 | point | Autumn E3B (Fri 13-17) |
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| 12105 | Quantitative Sustainability (Polytechnical Foundation) | 5 | point | E7 (Tues 18-22) |
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| 12101 | Quantitative Sustainability (Polytechnical Foundation) | 5 | point | Spring F3B (Fri 13-17) |
| 42500 | Innovation in Engineering (Polytechnical Foundation) | 5 | point | January |
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| 42504 | Innovation in Engineering (Polytechnical Foundation) | 5 | point | August |
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| 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 |
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| 42505 | Facilitating Innovation in Multidisciplinary Teams | 5 | point | August |
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| 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: Please choose one of the following courses (5 ECTS):
| 38102 | Technology Entrepreneurship | 5 | point | Autumn E1B (Thurs 13-17) |
| 41636 | Design for Circular Economy | 5 | point | January |
| 42014 | Environmental and Resource Economics | 5 | point | F7 (Tues 18-22) |
| 42016 | Business Economics and Finance | 5 | point | Spring F3B (Fri 13-17) |
| 46755 | Renewables in electricity markets | 5 | point | Spring F2A (Mon 13-17) |
The following three courses are mandatory for the programme (15 ECTS):
| 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):
| 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) |
Please choose at least 10 ECTS among the following courses:
| 02180 | Introduction to Artificial Intelligence | 5 | point | Spring F3A (Tues 8-12) |
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| 02450 | Introduction to Machine Learning and Data Mining | 5 | point | Spring F4A (Tues 13-17), Autumn E4A (Tues 13-17) |
| 02418 | Statistical modelling: Theory and practice | 5 | point | Autumn E4A (Tues 13-17) |
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| 02807 | Computational Tools for Data Science | 5 | point | E7 (Tues 18-22) |
| 42015 | Energy Economics | 5 | point | Autumn E3B (Fri 13-17) |
| 42112 | Mathematical Programming Modelling | 5 | point | January |
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| 42101 | Introduction to Operations Research | 5 | point | Autumn E2A (Mon 13-17) |
Please choose at least 5 ECTS among the following 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) |
Please choose at least 5 ECTS among 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) |
| 02465 | Introduction to reinforcement learning and control | 5 | point | Spring F4B (Fri 8-12) |
| 02619 | Model Predictive Control | 5 | point | Autumn E2B (Thurs 8-12) |
| 46705 | Power grid analysis | 5 | point | Spring F3A (Tues 8-12) |
| 46755 | Renewables in electricity markets | 5 | point | Spring F2A (Mon 13-17) |
Elective courses (30 ECTS):
Any course classified as MSc course in DTU's course base may be an elective course. This includes programme-specific courses in excess of the minimal requirements. Master students may choose as much as 10 credit points among the bachelor courses at DTU and courses at an equivalent level from other higher institutions. In addition, it is possible to take MSc-level courses at other Danish universities or abroad.
Suggestions for elective courses under 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) |
| 42014 | Environmental and Resource Economics | 5 | point | F7 (Tues 18-22) |
| 42114 | Integer Programming | 5 | point | Autumn E4A (Tues 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) |
| 46120 | Scientific Programming for Wind Energy | 5 | point | Spring F2B (Thurs 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) |
Master's thesis (30 ECTS):
MSc. thesis within the area of the specialization shall be conducted. The project can be completed in collaboration with a relevant company.
Specializations are merely recommended ways of choosing the courses in the curriculum. Applicants are not admitted to a specialization but to the programme and it is possible to choose among all the courses in the curriculum following the directions given. However, if a specialization has been fulfilled the title of the specialization may be added to the diploma.
Study track responsible
Lesia Mitridati Assistant Professor Mobile: +45 31964979 lemitri@dtu.dk