PhD on Electrical Energy Systems
4 weken geleden
Job description
Do you want to explore how the electric power system and their markets can change from today’s dominant day ahead optimised system to tomorrow’s dominant real-time adaptive optimised system? If you are eager to work on a fundamentally new system operations methodology that utilizes the available flexibility in order to increase the hosting capacity of the medium and high-voltage network, and that can be implemented practically, then this is your opportunity.
Due to the increase in volatile renewable energy production and easy controllable electricity demand (electric vehicles, heat pumps) the power flows become more fluctuating and less predictable. Due to these uncertainties, day-ahead prognoses for network operation need to contain significant safety-margins. This means that not all network capacity will be used effectively.
The goal of the RESONATE project is to investigate how the network can be operated in real-time and adaptive to minimize the required safety margins and use the available network capacity as efficiently as possible. The project will define prerequisites for the implementation of real-time system operations and develop an appropriate system architecture for TSO and DSO. Real-time system operations uses available network capacity more efficiently than is possible in the present paradigm. It therefore will be possible to connect more customers to the network when real-time becomes the dominant system operation methodology.
This research position will focus on the system operation “rules” and “controls” to maintain the system balance, system security and integrity under dominant adaptive real-time control and the resulting impact on the energy market design. The research leads to the development of suitable control algorithms and a system architecture to enable an integral real-time operation of both the transmission and distribution network. It will be investigated which controllable sources are present in which network and how much flexibility they offer for adaptive system stability in their local or other networks. Suitable cross TSO-DSO control algorithms will be developed and simulated on real distribution and transmission networks. Finally a system architecture will be developed that can be implemented in the control centers of the participating network operators and which can be integrated in the energy markets. The impact and practical use of the framework and controls therefore also needs to be analyzed from a market design perspective.
You will contribute to the TKI project RESONATE of the Electrical Energy Systems group.
Job requirements
A master’s degree (or an equivalent university degree) in Electrical Engineering. A research-oriented attitude. Ability to work in an interdisciplinary team with strong interest in collaborating with industrial partners. Motivated to develop your teaching skills and coach students. Fluent in spoken and written English (C1 level). Ability to write and present your results for scientific and non-scientific audiences. Solid knowledge in Power Engineering. Experience in system operation, electricity markets, control algorithms and system platform development is an advantage. Modelling skills in simulation tools such as PowerFactory or PSS/E is an advantage. Experience with setting up tests and measurements in electricity grids is an advantage.
Conditions of employment
A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:
Full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months. You will spend 10% of your employment on teaching tasks. Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min. €2,770 max. €3,539). A year-end bonus of 8.3% and annual vacation pay of 8%. High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process. An excellent technical infrastructure, on-campus children's day care and sports facilities. An allowance for commuting, working from home and internet costs A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.-
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