P
Patricia Rousseaux
Researcher at University of Liège
Publications - 30
Citations - 814
Patricia Rousseaux is an academic researcher from University of Liège. The author has contributed to research in topics: Electric power system & Kalman filter. The author has an hindex of 12, co-authored 30 publications receiving 750 citations.
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A taxonomy of multi-area state estimation methods
Antonio Gomez-Exposito,Antonio de la Villa Jaén,Catalina Gomez-Quiles,Patricia Rousseaux,Thierry Van Cutsem +4 more
TL;DR: In this paper, the authors present a critical review of the state of the art in multi-area state estimation (MASE) methods, which are currently gaining renewed interest due to their capability of properly tracking multi-TSO transactions and accommodating highly redundant information systems.
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SIME: A hybrid approach to fast transient stability assessment and contingency selection
TL;DR: In this paper, the authors propose an integrated scheme for transient stability assessment which in a sequence screens contingencies and scrutinizes only the selected ones, based on a hybrid method, called SIME for SIngle Machine Equivalent.
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Extended equal area criterion revisited (EHV power systems)
Y. Xue,Louis Wehenkel,R. Belhomme,Patricia Rousseaux,Mania Pavella,E. Euxibie,Bertrand Heilbronn,J.-F. Lesigne +7 more
TL;DR: In this paper, a study was conducted on the extra high voltage (EHV) French power system in order to explore the extended equal-area criterion and test its suitability as a fast transient stability indicator.
On the use of PMUs in power system state estimation
Antonio Gomez-Exposito,Ali Abur,Patricia Rousseaux,Antonio de la Villa Jaén,Catalina Gomez-Quiles +4 more
TL;DR: In this paper, the benefits that existing and future state estimators (SE) can achieve by incorporating synchronized phasor measurement units (PMUs) in the monitoring process are presented, in a tutorial manner.
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Whither dynamic state estimation
TL;DR: In this article, the authors present some feasible directions along which investigations on dynamic state estimation have been carried out and could be developed in the future, and they show that the benefits which could be encountered from dynamic estimation are linked to its predictive ability which provides the necessary information to perform preventive analysis and control.