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PhD scholarship in Artificial Intelligence Aided Predictive Control of Power Electronic Converters for Distributed Generation Systems, Electric Drives

Danmarks Tekniske Universitet (DTU)



Frist 15. juni 2020

The Center for Electric Power and Energy (CEE) at the Department of Electrical Engineering invites applications for PhD position associated with this project. The project will explore, develop and demonstrate solutions for machine learning based control of power electronic converters. The project is funded by DTU Strategic Alliance program and represents a strong collaboration between the Technical University of Munich and DTU.

The necessity of producing more energy combined with the interest in clean technologies leads to increased development of power distribution systems using renewable energy. Among the renewable energy sources, wind and photovoltaic technologies have the fastest growth today. Hydrogen fuel cell is another emerging technology that is expected to have an important contribution in the future energy production. In order to secure balanced power conditions in electrical power systems, distributed generators also need to be coordinated together with energy storage systems like batteries and flywheels, as well as electronic loads such as electrical drives. Since all these technologies are interfaced with the system through power electronic converters, their control plays an important role to achieve the future carbon neutral electrical power systems). Besides interfacing converters individually, it is also possible to interface them with the legacy grid through microgrids – intermediate entities that act as aggregators of generators, energy storage systems and loads.

Responsibilities and tasks
You will be responsible for developing methods for modelling and control of individual power electronic converters and microgrids with focus on model predictive control and artificial intelligence inspired techniques. You will also be analysing experimental data with machine learning models and contribute to the development of these machine learning models. You will be part of a group focusing on control and design of power electronic systems using advanced techniques particularly including artificial intelligence and model predictive control, in order to push the boundaries for what is possible to achieve with modern techniques. Particular focus will be given to improving the performance metrics of advanced controllers for individual power electronic converters and microgrids but having a low computational burden. These metrics may include better current & voltage power quality of individual converter, reduced operational costs/losses and/or improved cyber-security. The methods will have general applicability but will in particular be applied to control of power converters in distributed generation systems and microgrids. As a part of your studies, you will also make a 3-6 months guest PhD stay at the Technical University of Munich in Munich, Germany.

You will be positioned at the Center for Electric Power and Energy, where you will be part of a vibrant and diverse environment with an international atmosphere and strong links to the world-leading Danish energy industry. You will be part of a large group of fellow PhD-students within the field, and you can get access to our cutting-edge experimental facilities, PowerLabDK (www.powerlab.dk).

Qualifications
Candidates should have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree.

An ideal candidate will be self-motivated, enjoy working with complex topics, and thrive in international environment through collaboration and teamwork. You also have an open mind and can think creatively in a mathematical, physical, experimental, and programming context. You are eager to elaborate on the newest research results, to systematically implement and test ideas, and to improve the state-of-the-art. Besides the described personal skills, a candidate with the several of the following competences are particularly encouraged to apply:

  • Knowledge about power system operation and control, with special focus on hybrid power plants / microgrids
  • Knowledge about machine learning techniques
  • Familiarity with the advanced control techniques such as model predictive control
  • Familiar with optimization solvers
  • Experience with setting up experimental testbeds involving power electronic converters
  • Ability to present results in technical reports and prepare scientific papers for publication in top international journals. In this context, publication experience in top journals in area related to the position is preferable.

If this sounds interesting, you may be our new PhD student!

Approval and Enrolment
The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see the DTU PhD Guide.

We offer
DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.

Salary and appointment terms
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The period of employment is 3 years.

You can read more about career paths at DTU here.

Further information
Further information may be obtained from Professor Tomislav Dragičević, tomdr@elektro.dtu.dk.

You can read more about DTU Electrical Engineering at www.elektro.dtu.dk and about the Center for Electric Power and Energy at www.cee.elektro.dtu.dk.

Application
Please submit your online application no later than 15 June 2020 (local time). Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply online", fill out the online application form, and attach all your materials in English in one PDF file. The file must include:

  • A letter motivating the application (cover letter)
  • Curriculum vitae
  • Grade transcripts and BSc/MSc diploma
  • Excel sheet with translation of grades to the Danish grading system (see guidelines and Excel spreadsheet here)
  • Contact details of two individuals that can provide a letter of reference
  • Maximum 2-page research statement. Through the research statement, the applicants have the chance to present a research problem that interests them and propose how it might be investigated. The research problem should be related to the topic of the advertised PhD positions, and should preferably include introduction, method and contribution. Applications without a research statement may not be considered.

Candidates may apply prior to obtaining their master's degree but cannot begin before having received it.

Applications and enclosures received after the deadline will not be considered.

All interested candidates irrespective of age, gender, race, disability, religion or ethnic background are encouraged to apply.

DTU Electrical Engineering educates students within electrical engineering technologies. We offer studies at BEng, BSc, MSc and PhD levels, and participate in joint international programmes. We conduct state-of-the-art research within antenna and microwave technology, robot technology, power and physical electronics, acoustic environment, electro-acoustics, electric power and energy. Our department has more than 200 members of staff.

Technology for people

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Danmarks Tekniske Universitet (DTU) - hurtigt overblik


Danmarks Tekniske Universitet (DTU)
Danmarks Tekniske Universitet (DTU)
DTU er et teknisk eliteuniversitet med international rækkevidde og standard. Vores mission er at udvikle og nyttiggøre naturvidenskab og teknisk videnskab til gavn for samfundet. 11.200 studerende uddanner sig her til fremtiden, og 6.000 medarbejdere har hver dag fokus på uddannelse, forskning, myndighedsrådgivning og innovation, som bidrager til øget vækst og velfærd.

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