Miguel Jimenez Aparicio

Senior Member of Technical Staff

Author profile picture

Senior Member of Technical Staff

mjimene@sandia.gov

Google Scholar

(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

  • Jimenez Aparicio, M., Wilches-Bernal, F., Darbali-Zamora, R., Haines, J., Schoenwald, D., Shafiul Alam, S., Gevorgian, V., Yan, W., & Yan, W. (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
  • Reno, M., Jimenez Aparicio, M., Wilches-Bernal, F., Hernandez Alvidrez, J., Montoya, A., Barba, P., Flicker, J., Dow, A., Bidram, A., Paruthiyil, S., Montoya, R., Poudel, B., Reimer, B., Lavrova, O., Biswal, M., Miyagishima, F., Carr, C., Pati, S., Ranade, S., … Paul, S. (2022). Signal-Based Fast Tripping Protection Schemes for Electric Power Distribution System Resilience. https://doi.org/10.2172/1890046 Publication ID: 80280
  • Wilches-Bernal, F., Jimenez Aparicio, M., Reno, M., & Reno, M. (2021). A Machine Learning-based Method using the Dynamic Mode Decomposition for Fault Location and Classification [Conference Paper]. https://doi.org/10.1109/ISGT50606.2022.9817543 Publication ID: 77015
3 publications