Title :
Triggering the deep learning approach in power system courses using Free and Open Source Software
Author :
Vanfretti, L. ; Milano, F.
Author_Institution :
Electr. Power Syst. Div., R. Inst. of Technol. (KTH), Stockholm, Sweden
Abstract :
This paper describes how Free and Open Source Software can enable the deep learning approach in power system courses. With this aim, the paper describes authors´ experience with PSAT for undergraduate and graduate education. Specific examples of undergraduate activities based on PSAT, such as class activities and course projects, are given as illustrations. Experience with graduate PhD level education is also described. Interviews with former students reveal the positive impact that the use of FOSS in general, and PSAT in particular, had on their learning and how it has influenced their professional life.
Keywords :
computer aided instruction; power engineering education; public domain software; deep learning approach; free software; graduate level education; open source software; power system courses; undergraduate education; Computer languages; Education; Interviews; MATLAB; Mathematical model; Power systems; GNU Octave; Matlab; Power system analysis; Python; constructive alignment; deep learning; free and open-source software; functioning knowledge; learning activities; surface learning;
Conference_Titel :
Power and Energy Society General Meeting, 2011 IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4577-1000-1
Electronic_ISBN :
1944-9925
DOI :
10.1109/PES.2011.6039034
