Distributed Control of Cellular Microgrids: Towards Resilient, Stable, and Flexible Operation

Type de recrutement
FEMTO-ST Research Institute
Fin de l'affichage

Host laboratory: FEMTO-ST Research Institute

Thesis director (contact): Professor Salah LAGHROUCHE –

Co-advisors: Dr Youcef AIT AMIRAT

Funding: Université de Technologie de Belfort Montbéliard (UTBM)

Doctoral School: SPIM (Engineering Sciences and Microtechnologies), speciality Automation

Keywords: microgrid network, system of systems, real-time power flow management, stability, flexibility, resilience.

Scientific background :

In order to improve the reliability and resilience of large microgrids (macro-grids), in parallel with the development of cyber-physical systems, many recent studies recommend dividing the macro-grid into several autonomous cells. A cell is characterized as the smallest part of the network capable of operating independently by exploiting its own resources, such as Distributed Energy Resources (DER) and loads. Therefore, each cell must be able to operate when the main macro-grid fails due to disturbances. In addition, this allows for better adaptation to changing system conditions over time through decentralized and flexible management of cells that can be dynamically reconfigured.

The central scientific question of this research is to develop real-time power flow coordination strategies that can address the hierarchical control structure of a macro network as a whole. This unified and integrated control approach should achieve the following objectives:

  • Maximize self-consumption indices in buildings and load level.
  • Coordinate power flows on time scales corresponding to the dynamics of the macro-grid, ensuring optimal setpoints for DERs based on current system status and forecasted ambient conditions.
  • Smoothly regulate voltages and frequencies despite large fluctuations in sources, loads and topology changes (connection and disconnection of DERs and loads).
  • Propose a constructive approach that demonstrates the stability [1] of the microgrid and allows the stability zone to be assessed.

These objectives must be achieved while respecting various constraints, such as operating parameter ranges, asset limitations, network issues, regulatory, legislative, and legal frameworks, market constraints and communication times.

Technically, a reliable and efficient energy management system involves solving a non-linear, multi-objective and constrained optimization problems. The design of a real-time optimization methodology adapted to meet these requirements is a major challenge.

Description of the thesis:

This thesis topic focuses on the development of a control approach for interconnected microgrids (macrogrid) in a "system of systems" context, guaranteeing resilient, stable, and scalable operation for the renewable energy resources that make it up.

The macro-network can be seen as a system made up of many cells, and its functioning depends on these different "cells". Together with a distributed communication infrastructure, they form a cyber-physical system. The control of this system can be approached according to the system of systems paradigm: each cell of the macro-grid is modelled, and a power flow and operational layer control law is synthesized for the optimization of DERs without intercell communication, to regulate distribution voltages and to manage peak demand. An intelligent supervisory system coordinates the cells for the network reconfiguration and service restoration, ensuring optimal resilience and stability in real time.

Scientific and technical challenges: Conventional OPF [2] (Optimal Power Flow) energy management methods for microgrids are hierarchically structured, creating a disjunction between control levels depending on the time scale and dynamics involved. They are usually based on a temporal separation combining offline feedforward optimization and low-level controllers (droop [3], AGC). The high intermittency of renewable energy sources and loads, parametric uncertainties in the modelling of microgrid components and possible communication problems can make hierarchical synthesis suboptimal without guaranteeing the desired control.

Planned work: Two approaches will be explored to address these objectives:

  • By exploiting the notion of homogeneity [4, 5], which is based on convergence and stabilization in finite time [6, 7, 8], it is possible to separate and prioritize spatially distributed control and optimization processes in time, while respecting strict temporal constraints. This approach greatly simplifies the analysis and design of large-scale solutions for interconnected (cyber-physical) systems. In sum, this method facilitates the management of these complex systems.
  • Partial learning based predictive control, where these controllers use a basic, partially known physical model of the system and add a learning layer to compensate for the unknown part of the model, combining the stability characteristics of the model-based design with the advantages of the free learning model in terms of fast convergence and robustness to uncertainties.

Presentation of the host laboratory:

The FEMTO-ST Institute, in Franche-Comté, is the result of the collaboration between the UFC, the CNRS, the ENSMM and the UTBM. Composed of 7 departments and more than 700 members, it will host the PhD thesis in the SHARPAC team of the Energy Department in Belfort, from October 2023 for 3 years.

Thesis funding:

This thesis will be financed by the UTBM through a MESRI doctoral grant. The doctoral student will be registered at the UBFC (Université de Bourgogne Franche-Comté) and at the SPIM doctoral school (Engineering Sciences and Microtechnologies) in the speciality Automation.

Candidate profile:

A strong motivation for scientific research and advanced English language skills are required. The candidate must also demonstrate rigour, method, autonomy and practical skills in simulation, data analysis and presentation. A master's degree or equivalent with excellent grades is required, as well as a strong background in control theory, optimization, and electrical engineering.

Gross monthly Salary : 1975€

List of documents to be provided:

  • CV
  • A letter of motivation
  • Academic transcript and ranking of Master 1 and 2
  • Recommendation letter(s)

The application should be sent by e-mail to:

The closing date for the application is: 5/06/2023


  • [1] M. Farrokhabadi et al, Microgrid Stability Definitions, Analysis, and Examples, IEEE Transactions on Power Systems, vol. 35, no. 1, pp. 13-29, Jan. 2020.
  • [2] V.A. Evangelopoulos, P.S. Georgilakis, N.D. Hatziargyriou, Optimal operation of smart distribution networks: A review of models, methods and future research, Electr. Power Syst. Res., 140 (2016), pp. 95-106
  • [3] Bolognani, R. Carli, G. Cavraro, S. Zampieri, On the need for communication for voltage regulation of power distribution grids, IEEE Transactions on Control of Network Systemsn  6(3) (2019) 1111–1123.
  • [4] L.Fridman, D. Efimov, S. Laghrouche, Homogeneous Sliding-Mode Control and Observation, Int. J. Robust & Non. Cont. SI. 31(9), 2021.
  • [5] M. Harmouche, S. Laghrouche et al. Stabilisation of perturbed chains of integrators using Lyapunov-based homogeneous controllers, Int. J. of Cont., 90(12) 2017.
  • [6]  Y. Chitour, M. Harmouche, S. Laghrouche, Lp-stabilization of integrator chains subject to input saturation using Lyapunov-based homogeneous design, SIAM Journal on Control and Optimization, 53(4) 2015.
  • [7] S. Laghrouche et al. Higher Order Super-Twisting for Perturbed Chains of Integrators, IEEE Trans. on Automatic Control, 62(7) 2017.
  • [8] S. Laghrouche et al. Barrier Function-Based Adaptive Higher Order Sliding Mode Controllers, Automatica, Volume 123, 2021.