Project

Deep Learning for Feature Extraction in Power System Security Assessment

Publisher

Supervisor

Location

Greater Copenhagen area

The increase in fluctuating renewable energy, such as wind and solar, and the increase in electricity demand driven by the electrification of heat and transport sectors challenge traditional power system operation. Power system operators routinely perform system security assessments to ensure a safe and stable operation. With growing uncertainty, the complexity of this computationally intensive task further increases calling for the development of new approaches.

Deep learning has shown tremendous potential in a wide range of scientific and technological applications, recently publicized for the game of Go with the computer program AlphaGo winning against the world champion. However, the application of deep learning in power systems has been limited so far. One promising direction is deep learning for feature extraction. The goal is to map the high-dimensional power system state to a significantly lower-dimensional feature space more suitable for a classifier to discriminate between safe and unsafe operation. The resulting tool could aid operators in maintaining a stable power system operation.

Please see the attached proposal for more information.


Requirements

Power system modeling or machine learning, good knowledge of Matlab, Python or another programming language, high interest in deep learning.

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Contact

Company / Organization

DTU Elektro

Name

Andreas Venzke

Position

Ph.d.-studerende

Mail

andven@elektro.dtu.dk

Supervisor info

MSc in Computer Science and Engineering

Supervisor

Andreas Venzke

Co-supervisors

Spyros Chatzivasileiadis

ECTS credits

10 - 35

Type

MSc thesis, Special course

MSc in Electrical Engineering

Supervisor

Andreas Venzke

Co-supervisors

Spyros Chatzivasileiadis

ECTS credits

10 - 35

Type

MSc thesis, Special course

MSc in Mathematical Modelling and Computation

Supervisor

Andreas Venzke

Co-supervisors

Spyros Chatzivasileiadis

ECTS credits

10 - 35

Type

MSc thesis, Special course

MSc in Sustainable Energy

Supervisor

Andreas Venzke

Co-supervisors

Spyros Chatzivasileiadis

ECTS credits

10 - 35

Type

MSc thesis, Special course

Technical University of Denmark

For almost two centuries DTU, Technical University of Denmark, has been dedicated to fulfilling the vision of H.C. Ørsted – the father of electromagnetism – who founded the university in 1829 to develop and create value using the natural sciences and the technical sciences to benefit society.


Today, DTU is ranked as one of the foremost technical universities in Europe, continues to set new records in the number of publications, and persistently increases and develops our partnerships with industry, and assignments accomplished by DTU’s public sector consultancy.

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