Miguel Jimenez Aparicio

Senior Member of Technical Staff

(505) 527-3448

Biography

Miguel Jimenez Aparicio is a Senior Member of Technical Staff in the Electric Power Systems Research Department at Sandia National Laboratories. His research focuses on fast, signal-based protection for distribution systems under scenarios of high renewable energy penetration. Miguel is also involved on the development of data-driven controllers for hybrid systems for grid-support tasks. His research interests include the reliable integration of distributed renewable energy resources into the grid, and the transition to data driven operation, control and protection of power systems. He received his M.S. in Electrical Engineering from Georgia Institute of Technology.

Education

M.S. in Electrical Engineering, Georgia Institute of Technology (Atlanta, USA)
M.S. in Industrial Engineering, Universidad Pontificia Comillas (Madrid, Spain)
B.S. in Electromechanical Engineering, Universidad Pontificia Comillas (Madrid, Spain)

Publications

Miguel Jimenez Aparicio, Felipe Wilches-Bernal, Rachid Darbali-Zamora, John Haines, David Schoenwald, S. Shafiul Alam, Vahan Gevorgian, Weihang Yan, (2022). Simulink Modeling and Dynamic Study of Fixed-Speed, Variable-Speed, and Ternary Pumped Storage Hydropower https://doi.org/10.2172/1887487 Publication ID: 80190

Matthew Reno, Miguel Jimenez Aparicio, Felipe Wilches-Bernal, Javier Hernandez Alvidrez, Armando Montoya, Pedro Barba, Jack Flicker, Andrew Dow, Ali Bidram, Sajay Paruthiyil, Rudy Montoya, Binod Poudel, Benjamin Reimer, Olga Lavrova, Milan Biswal, Frank Miyagishima, Christopher Carr, Shubhasmita Pati, Satish Ranade, Santiago Grijalva, Shuva Paul, (2022). Signal-Based Fast Tripping Protection Schemes for Electric Power Distribution System Resilience https://doi.org/10.2172/1890046 Publication ID: 80280

Felipe Wilches-Bernal, Miguel Jimenez Aparicio, Matthew Reno, (2021). A Machine Learning-based Method using the Dynamic Mode Decomposition for Fault Location and Classification https://doi.org/10.1109/ISGT50606.2022.9817543 Publication ID: 77015

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