PhD Thesis on
Advanced Techniques in Microgrid Modelling and Control to Attain Theoretical Guarantees
Supervising Team
Andrei BRAITOR andrei.braitor@l2s.centralesupelec.fr
Guillaume SANDOU guillaume.sandou@l2s.centralesupelec.fr
General Information
Fully funded PhD, 36 months, flexible starting date (preferably autumn 2024)
Application details
Interested candidates will email the supervising team enclosing their CV, cover letter, and other relevant documents (reference letter(s), research statement, bachelor’s/ master’s official transcripts, etc). Selected applicants will be invited to an interview.
Deadline: 15 March 2024
Location (Paris region)
L2S, CentraleSupélec, Université Paris-Saclay
3 rue Joliot Curie, 91190 Gif-sur-Yvette
(IBM France Lab Saclay, Rue Alfred Kastler, 91400 Orsay)
Funding
SYCOMORE Team, L2S, CentraleSupélec, Université Paris-Saclay
THESIS DESCRIPTION
Context: Of late, influenced significantly by the imperative demand for energy solutions that are both sustainable and dependable, the global energy landscape has initiated a pivotal transformation, which is currently still undergoing. Microgrids, as an integral part of this transformation, represent a change in perspective for energy management and distribution as they offer the potential to integrate a diverse range of renewable energy sources, improve reliability, and enhance energy efficiency. In other words, microgrids are transforming power systems with their increasing integration of renewable energy sources and controllable loads [1].
However, the increasing complexity of microgrids, characterised by integrating renewable energy sources, energy storage systems, and the dynamic demands of modern loads such as electric vehicles, presents new challenges. These systems, being multi-level and multi-time scale, face unique challenges. These challenges include guaranteeing stability, ensuring robustness, maintaining power quality, managing the intermittent nature of renewable sources, and ensuring efficient energy distribution within the electrical network system [2]. Furthermore, the interaction between AC and DC microgrids with distinct characteristics and control requirements adds another layer of complexity. Advancements in control strategies and modelling techniques are thus essential to address these challenges [3-4].
The proposed PhD thesis aims to tackle these challenges by developing advanced microgrid modelling and control methods. The research will focus on enhancing stability and system efficiency and facilitating the integration of renewable energy sources in microgrids, contributing to the overarching goal of sustainable and resilient energy systems.
The primary goals of this research are to devise novel control strategies that improve key aspects of microgrid operations, such as performance, robustness, efficiency, resiliency, and stability. Additionally, there is a focus on understanding the consequences of network configurations [5] and the adverse effects that may arise in the presence of nonlinear loads. Furthermore, the research aims to investigate the interactions between hybrid AC/DC microgrids, particularly in scenarios involving grid-forming and grid-following controls, to gain a comprehensive insight into their operational dynamics.
Research Methodology: The research methodology encompasses (but is not restricted/ limited to) a multifaceted approach to enhance microgrids’ performance and develop theoretical guarantees. This might include the application of nonlinear control techniques, linear matrix tools, network systems strategies, etc, to address challenges in decoupling dynamics, time-scale separation, or scalability within microgrid networks, for instance.
The research work could also focus on the development and advancement of control techniques ranging from primary to higher control levels (a bottom-up approach). Software tools such as MATLAB/Simulink are integral to the methodology, facilitating modelling, control, simulation, and testing processes.
Expected Outcomes: One expects whatever the outcomes to be relevant for academic research and practical applications in the energy sector. The potential outputs of this project are summed up below:
•
Enhanced understanding of the effects of renewable energy integration on microgrid dynamics.
•
Improved methodologies for modelling the interaction between various elements of a microgrid.
•
New theoretical frameworks and practical control strategies to ensure microgrid’s various theoretical metrics.
This research will contribute to the field of smart energy systems by providing advanced solutions for the challenges microgrids face. The proposed thesis will address critical microgrid modelling and control issues, contributing to developing more stable, efficient, and sustainable electrical power systems.
Candidate Profile: The ideal candidate for this PhD project should possess a master’s degree (or equivalent) in engineering (control systems, power electronics, power systems, etc) with a strong mathematical background. They must have excellent English writing and speaking skills, enabling them to communicate complex ideas effectively. The candidate should be proficient in using software tools like MATLAB/Simulink for modelling, simulation, and testing. They should also have an aptitude for innovative problem-solving and a passion for contributing to sustainable energy solutions. The candidate should be prepared to engage in interdisciplinary research and contribute to advancing the field of smart energy systems through theoretical and practical approaches.
Bibliography
[1] R. H. Lasseter, « MicroGrids, » 2002 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.02CH37309), New York, NY, USA, 2002, pp. 305-308 vol.1, doi: 10.1109/PESW.2002.985003.
[2] A.-C. Braitor, Advanced Hierarchical Control and Stability Analysis of DC Microgrids, 2022, No. 1, ISSN 2190-5053 Springer Nature, https://doi.org/10.1007/978-3-030-95415-4.
[3] A.-C. Braitor, G.C. Konstantopoulos and V. Kadirkamanathan, Stability analysis of DC micro-grids with CPLs under novel decentralised primary and distributed secondary control, Automatica, vol 139, 2022, 110187, ISSN 0005-1098, https://doi.org/10.1016/j.automatica.2022.110187.
[4] N. Gionfra, H. Siguerdidjane, G. Sandou, D. Faille, Hierarchical Control of a Wind Farm for Wake Interaction Minimization, IFAC-PapersOnLine, vol 49, 27, 2016, pp 330-335, ISSN 2405-8963, https://doi.org/10.1016/j.ifacol.2016.10.713.
[5] F. Dörfler, J. W. Simpson-Porco and F. Bullo, « Electrical Networks and Algebraic Graph Theory: Models, Properties, and Applications, » in Proceedings of the IEEE, vol. 106, no. 5, pp. 977-1005, May 2018, doi: 10.1109/JPROC.2018.2821924.
