IEEE Durham Region Speaker Series - Dr. Antonio Valderrabano-Gonzalez & Dr. Carlos Eduardo Castañeda
Dr. Antonio Valderrabano-Gonzalez & Dr. Carlos Eduardo Castañeda have accepted to give a talk on their research interest areas while visiting Ontario Tech University.
Date and Time
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- Date: 07 Jul 2022
- Time: 02:30 PM to 05:30 PM
- All times are (UTC-04:00) Eastern Time (US & Canada)
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- Ontario Tech University
- Oshawa, Ontario
- Canada
Speakers
Antonio Valderrabano-Gonzalez
Design Methodology for Interfacing DERs to Power Systems through VSC
On this talk, a methodology to connect DERs via VSC to three-phase systems of standard or non-standard voltages. The interfacing among converters is illustrated by transfer function blocks. The main input-output values to be considered in the application are detailed and the system can be modified to be included in other systems. This proposal defines the capacitive and inductive component values for an operating point and has the option to reduce them when adding smoothed variations and adaptive controllers.
Biography:
Dr. Antonio Valderrabano-Gonzalez is a research professor at Universidad Panamericana Mexico. He is working on Power Electronics, Power Electronic Converters, FACTS devices, and Power Quality. He completed his B.Sc from Instituto Tecnológico de Puebla, M.Sc. from Instituto Nacional de Astrofísica, Óptica y Electrónica, and Ph.D. from Cinvestav Guadalajara. Along with publishing several papers and books, he has also worked in companies like Molex and Solectron and is a level 1 member of the National System of Researchers in Mexico.
Carlos Eduardo Castañeda
Neural super-twisting controller to emulate a flywheel energy storage system
In this work, a neural super-twisting algorithm is applied to the design of a controller for a flywheel energy storage system (FESS) emulator. Emulation of the FESS is achieved through velocity control of a Permanent Magnet Synchronous Machine (PMSM) coupled to a shaft-to shaft DC motor in the energy storage stage and feedback stage. A Recurrent Wavelet First Order Neural Network (RWFONN) is proposed for neural identification while a supertwisting algorithm is applied for velocity control. This is combined with block control linearization technique to the control of the angular velocity.
Biography:
Carlos Eduardo Castañeda received the B.S. in Communications and Electronics in 1995 from the Universidad de Guadalajara, México, the M.Sc. degree in Electronics and Computer Systems in 2003 from the Universidad la Salle Bajío, México, and the Ph. D. in Electrical Engineering in 2009 from CINVESTAV Guadalajara, México; he is working as Professor at Universidad de Guadalajara, Centro Universitario de los Lagos, México. His research interests are Automatic Control and Renewable Energy Sources.