L
Lamine Mili
Researcher at Virginia Tech
Publications - 244
Citations - 8818
Lamine Mili is an academic researcher from Virginia Tech. The author has contributed to research in topics: Electric power system & Estimator. The author has an hindex of 40, co-authored 228 publications receiving 6979 citations. Previous affiliations of Lamine Mili include University of Virginia & University of Liège.
Papers
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Journal ArticleDOI
Power system observability with minimal phasor measurement placement
TL;DR: In this article, the placement of a minimal set of phasor measurement units (PMUs) so as to make the system measurement model observable, and thereby linear, is investigated.
Journal ArticleDOI
Power System Dynamic State Estimation: Motivations, Definitions, Methodologies, and Future Work
Junbo Zhao,Antonio Gomez-Exposito,Marcos Netto,Lamine Mili,Ali Abur,Vladimir Terzija,Innocent Kamwa,Bikash C. Pal,Abhinav Kumar Singh,Junjian Qi,Zhenyu Huang,A. P. Sakis Meliopoulos +11 more
TL;DR: A unified framework is proposed to clarify the important concepts related to DSE, forecasting-aided state estimation, trackingstate estimation, and static state estimation and provide future research needs and directions for the power engineering community.
Proceedings ArticleDOI
Initial review of methods for cascading failure analysis in electric power transmission systems IEEE PES CAMS task force on understanding, prediction, mitigation and restoration of cascading failures
Ross Baldick,Badrul H. Chowdhury,Ian Dobson,Zhao Yang Dong,Bei Gou,David Hawkins,H. Huang,Manho Joung,Daniel S. Kirschen,Fangxing Li,Juan Li,Zuyi Li,Chen-Ching Liu,Lamine Mili,Stephen S. Miller,Robin Podmore,Kevin P. Schneider,Kai Sun,David Wang,Zhigang Wu,Pei Zhang,Wenjie Zhang,Xiao-Ping Zhang +22 more
TL;DR: In this article, the authors define cascading failure for blackouts and give an initial review of the current understanding, industrial tools, and the challenges and emerging methods of analysis and simulation.
Journal ArticleDOI
A Robust Iterated Extended Kalman Filter for Power System Dynamic State Estimation
TL;DR: In this paper, a robust iterated extended Kalman filter (EKF) based on the generalized maximum likelihood approach (termed GM-IEKF), is proposed for estimating power system state dynamics when subjected to disturbances.
Journal ArticleDOI
Robust Kalman Filter Based on a Generalized Maximum-Likelihood-Type Estimator
Mital A Gandhi,Lamine Mili +1 more
TL;DR: A robust filter in a batch-mode regression form to process the observations and predictions together, making it very effective in suppressing multiple outliers, and results revealed that this filter compares favorably with the H¿-filter in the presence of outliers.