Organisation/Company: CITCEA-UPC
Department: CITCEA
Research Field: Engineering
Researcher Profile: First Stage Researcher (R1)
Positions: PhD Positions
Country: Spain
Application Deadline: 30 Nov 2024 - 22:00 (Europe/Madrid)
Type of Contract: Temporary
Job Status: Full-time
Hours Per Week: 37.5
Offer Starting Date: 6 Jan 2025
Is the job funded through the EU Research Framework Programme? Horizon Europe
Reference Number: HORIZON-101119349-Inter-oPEn
Is the Job related to staff position within a Research Infrastructure? No
Offer Description Inter-oPEn (Marie Sklodowska-Curie Action project) offers a unique doctoral training program for 10 researchers that integrates multi-sectorial knowledge, gathering electrical engineering and legal researchers. To achieve the common goal of the interoperable PE-dominated power system, openness will be a pivotal factor across the different doctoral projects, tackling fundamental aspects of modern PE-based electrical systems such as control, protection, interoperability, governance, and intellectual property challenges.
Comprised of 8 academic partners and 13 industrial associated partners, Inter-oPEn offers a broad industry and transmission system operator expertise for doctoral trainings, research, and secondments. Compared to previous EU projects and doctoral training networks on the interoperable PE-dominated grid, Inter-oPEn is innovative by including two fundamental and new aspects: (1) the interplay of technical and legal perspectives is considered, and (2) openness principles are the heart of engineering and legal research, as well as, training.
The project will provide training through doctoral research to talented Doctoral Candidates. InterOpen Doctoral Candidates will enrol on PhD degree programmes and be employed for 36 months in a network of universities and industry with expertise in the field of power electronics, HVDC and modern power systems.
Project title: Data-driven control of power converters for modern power networks
Objectives: This thesis aims to develop data-driven controllers to be implemented in VSC-based grid-connected power converters. The transition of the power networks towards a system of black-boxed systems interconnected together with their highly variable nature driven by renewable energy variation, requires new technology capable of operating in such an environment.
Optimization-based data-driven predictive controllers thrive in such an environment as they are capable of constructing high performance, reliable and adaptable controllers fully based on network captured data, without requiring detailed models.
The thesis will provide the methodology to synthesize such controllers, starting from the system data capture process, model identification (if needed), construction of the optimization-based controller and then simulation verification in benchmark power systems implemented in Simulink and PSCAD. As an example of this class of controllers, the thesis will further develop and expand the concept of Data-enabled Predictive Control (DeePC).
Key applications: The developed techniques will be applied to HVDC, FACTS, and renewable energy systems controllers.
Minimum Requirements Strong academic qualification with an internationally recognized degree at Masters level in Mathematics, Computer Science, Electrical Engineering, Power Systems Engineering, or any related field.
Preferred knowledge: dynamic power converters and power system modelling and analysis, power converter control, data-driven techniques, optimization techniques.
Software development experience in Matlab and/or Python and/or relevant tools in the field.
Experience that demonstrates your team-oriented, independent, innovative, and strategic working styles.
Fluency in English, both written and spoken.
Candidates not fulfilling the previous requirement but interested in working with us are encouraged to contact us explaining the situation, as we may have other opportunities available.
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