Retour aux activités
Séminaire du GERAD

Generation scheduling under renewable-based uncertainty via two-stage adaptive robust optimization


19 avr. 2018   10h30 — 12h00

José M. Arroyo Universidad de Castilla-La Mancha, Espagne

Within the context of current day-ahead electricity markets, the presentation examines the use of two-stage adaptive robust optimization as a relevant tool to handle renewable-based uncertainty in generation scheduling. Unlike alternative approaches to deal with uncertainty, neither accurate probabilistic information nor a discrete set of uncertainty realizations are required. Rather, uncertainty is modeled by decision variables within a deterministic uncertainty set. Hence, the size of the robust models does not depend on the dimension of the space of uncertainty realizations belonging to the uncertainty set, thereby providing a computationally efficient framework. In addition, an easy control of the degree of conservativeness can be implemented. The resulting robust counterparts are instances of mixed-integer trilevel programming. Practical modeling aspects allow using effective decomposition-based techniques that guarantee finite convergence to optimality. Results from several case studies illustrate the effectiveness of the two-stage robust setting.

Do not forget to confirm your attendance:

Miguel F. Anjos responsable


Salle 4488
Pavillon André-Aisenstadt
Campus de l'Université de Montréal
2920, chemin de la Tour Montréal QC H3T 1J4 Canada

Organisme associé

Chaire de recherche industrielle CRSNG-Hydro-Québec-Schneider Electric en optimisation des réseaux électriques intelligents

PosterSeminarApril19.pdf (220 Ko)