Juan M. Rey, pHD.
ASSISTANT PROFESSOR, UIS.
research
These are the research projects that we are currently developing. Contact me if you want to know more details.
In this project, we are developing alternative control strategies for grid-connected PV inverters with load compensation and LVRT capabilities. We are also analyzing the operation of distribution networks with high renewable energy penetration and the inclusion of multifunctional PV systems for voltage sags.
Collaborators: Universidad Nacional de Colombia (Colombia) + Universidad Distrital Francisco José de Caldas (Colombia) + Universidad Antonio Nariño (Colombia).
Supported by MinCiencias project "Programa de Investigación en Tecnologías Emergentes para Microredes Eléctricas Inteligentes con Alta Penetración de Energias Renovables" + MinCiencias project: "Diseño de estrategias alternativas de operación y control para sistemas fotovoltaicos multifuncionales en redes de
distribución con alta penetración de energías renovables".
Team: Prof. María A. Mantilla + David Rincon (PhD Student) + Wilmar Sotelo (Master's Student)
Control strategies for grid-connected PV systems
IIoT based platform for Industry 4.0 [Project website]
In this project, we are designing and implementing an IIoT platform for training students in industry 4.0 technologies. The platform will integrate a central server with controlled process modules using portable, compact, and low-cost modules operated remotely by the students. At the end of the project, a training program will be offered in conjunction with strategic Colombian industries.
Collaborators: Diseño y Automatización Industrial S.A.S. (Colombia).
This project is supported by MinCiencias "Diseño, desarrollo e implementación de una plataforma IIoT para formación de profesionales en tecnologías de la cuarta revolución industrial".
Team: Jonathan Gómez (Master's Student) + Felipe Rubio (Master's Student) + Alejandro Ortiz (Master's Student) + Juliam Díaz (Master's Student) + Joaquín Delgado (Master's Student)
The complexity of the operation of grid-connected microgrids brings challenges to the operation and control. However, with the deployment of smart meters, novel data-driven methods based on artificial intelligence are explored. In this project, we are studying different reinforcement learning techniques to deal with the assignation of retail energy prices in distribution systems with multiple microgrids.
Supported by UIS project "Estrategia basada en aprendizaje por refuerzo para la asignación de precios minoristas en redes de distribución con múltiples microrredes".
Machine learning for electrical microgrids