Recrutement

recrutement

Phd Position -- Control strategies for a wind farm based on a simplified dynamical wake modeling

Type de recrutement
Thèse
Durée
Urgent
oui
Rattachement
IFPEn - Mines (CAS)
Fin de l'affichage

 

In the field of wind energy, operators are now focusing on using wind turbines located in wind farms in the best possible way, to either produce the maximum energy possible, or produce the right amount of energy at the right time, to meet power grid requirements while limiting the wind turbine mechanical stress, in order to eventually minimize the cost of energy. 

It is possible to limit the interactions between a turbine wake and the downwind turbines by controlling its yaw angle and power produced, and thus alleviating the production losses and mechanical fatigue. In this context, our central question will be “How to robustly minimize a wind farm cost of energy via a control algorithm using a dynamic wind farm flow model, and how to implement it in real world”. 

The PhD results will contribute to three major advances: 

1. Develop wind farm control strategies based on a time-varying wake modeling and evaluate their added value. 

2. Define a cost criterion allowing to efficiently minimize the cost of energy over long time horizons. 

3. Contribute to the implementation and deployment of the developed control algorithms and prove and illustrate their robustness and efficiency. 

 

Keywords: Wind turbines, Wind farms, Control, Estimation, Optimal Control, Optimization, Predictive control

Academic supervisor 

Dr BRESCH-PIETRI Delphine, CAS Mines Paris, delphine.bresch-pietri@minesparis.psl.eu

Prof., DI MEGLIO Florent, CAS Mines Paris, 0000-0002-0232-6130 

 

Doctoral School 

Ingénierie des Systèmes, Matériaux, Mécanique, Énergétique 

IFPEN supervisor 

PhD, COLLET David, Research engineer, Control, signal and systems department, david.collet@ifpen.fr, 0000-0002-0022-9572 

PhD location 

IFP Energies Nouvelles, Lyon, France 

Duration and start date 

3 years, starting in fourth quarter 2024 

Employer 

IFP Energies Nouvelles, Lyon, France 

Academic requirements 

University Master degree mathematics or mechanical engineering 

Language requirements 

Fluency in French or English, willingness to learn French 

Other requirements 

Control systems, optimization, signal processing