Sara Siniscalchi Minna was born in Rome, Italy, in 1990. She carried out the Bachelor and Master degrees in Energy Engineering from University "La Sapienza" of Rome in July 2016. She carried out her Master’s Thesis in the Technical University of Denmark (DTU), Department of Wind Energy. There, she studied the modelling of wake effects for the wind turbine fatigue-life prediction in large wind farms. During the Bachelor thesis she performed a numerical analysis of a moored floating structure for allocation of wave energy converter (WEC) systems. The findings of this research were presented at the International Conference on Offshore Mechanics and Arctic Engineering, San Francisco, CA, 8-13 June 2014. In September 2016, as part of the INCITE network, Sara started her PhD at IREC in collaboration with UPC. Her research project is to propose distributed control strategies for wind farms aimed to regulate the active and reactive power injected into the grid in order to provide support frequency, voltage stability and other grid support services. The aim is to consider the individual behaviour of each turbine in the farm and to achieve a coordinated behaviour to fulfil the TSOs demands.
Advisor: José Luis Domínguez-García
A multi-objective predictive control strategy for enhancing primary frequency support with wind farms, S. Siniscalchi Minna, M. De Prada Gil, F. D. Bianchi, C. Ocampo-Martinez and B. De Schutter, J. Phys.: Conf. Ser. (2018) 1037 032034
Predictive control of wind farms based on lexicographic minimizers for power reserve maximization, S. Siniscalchi Minna, F. D. Bianchi, C. Ocampo-Martinez, Proc. of the 2018 Annual American Control Conference (ACC), Milwaukee, USA (2018)
A wind farm control strategy for power reserve maximization, S. Siniscalchi Minna, F. D. Bianchi, M. De Prada Gil, C. Ocampo-Martinez, Renewable Energy 131 (2019) 37-44
A constrained wind farm controller providing secondary frequency regulation: An LES study, S. Boersma, B.M. Doekemeijer, S. Siniscalchi Minna, F. D. Bianchi, J.W. van Wingeren, Renewable Energy 134 (2019) 639-652
Partitioning approach for large wind farms: Active power control for optimizing power reserve, S. Siniscalchi-Minna, C. Ocampo-Martinez, F. D. Bianchi, M. De-Prada-Gil and B. De-Schutter, 2018 IEEE Conference on Decision and Control (CDC), FL, USA, 2018, pp. 3183-3188.