Fall semester 2022: New master / phd course is offered - Energy Informatics - Smart Energy and Power Systems Modelling

Department of Computer Science, campus Tromsø, will in the fall semester 2022 offer a new master level / phd course: INF-3010 / INF-8010 Energy Informatics - Smart Energy and Power Systems Modelling.

Ilustration photo: Smart Energy and Power Systems IoT Smart City Concept.
Ilustration photo: Smart Energy and Power Systems IoT Smart City Concept. Foto: mostphotos.com
Portrettbilde av Fuglesteg, Jan
Fuglesteg, Jan jan.fuglesteg@uit.no Studierådgiver
Publisert: 10.05.22 10:08 Oppdatert: 12.06.22 08:07
Bærekraft Energi Naturvitenskap Studentliv / Studier Teknologi

Master version
Target group for the master version is master level students at both the 2-year and 5-year master program. The course is categorized as an elective course in both these programs and can also be a specialisation for the 5-year program. The course is also very relevant for master students at other departments at the Faculty of Science and Technology, for example the 5-year masterprogram in Energy, climate and environment (EKM-studiet). Exchange students may in certain cases take the course if they have the recommended prerequisites to take it. The course is not available for bachelor students.

Associate Professor Chiara Bordin, Department of computer science (UiT) will be responsible for the course. The language of instruction is English and all of the syllabus material is in English.

Chiara Bordin will be course responsible for the new master / pdh course in Energy Informatics - Smart Energy and Power Systems Modelling. Foto: Privat.

Course content
This course covers the Energy Informatics discipline through the use of mathematical optimization as a background. The course will discuss how mathematical optimization, in the context of computer science, can contribute to more effectively manage smart energy and power systems. The content of this course can be summarized as follows. An introduction to energy systems and power systems will be provided, together with a broad overview of topics where the most relevant energy and power systems challenges and opportunities can be identified. Afterwards, the fundamental concepts of mathematical optimization will be presented, with focus on applications for energy and power systems related problems. Finally, broader perspectives of smart energy and power systems modelling in the context of Energy Informatics will be addressed. This will lead to discussions on relevant links that exist at the intersection of energy systems, power systems, economics, computer engineering, social science, computer science, applied mathematics.

Recommended prerequisites: Basic knowledge in physics, linear algebra or discrete mathematics; and basic programming skills in Python.

Course objectives and other course info: INF-3010 Energy Informatics - Smart Energy and Power Systems Modelling

If you have professional / technical questions you can contact Chiara Bordin.

Phd version
This course will also be avaliable in a phd version - INF-8010 Energy Informatics - Smart Energy and Power Systems Modelling.

The lectures for the two versions will be the same, but the examiantion form and the grade scale is different.

Lectures / Time tables
The lectures and colloquium will be digital and accessible for students not physically based in Tromso. But external master students must come to Tromsø for the written on-campus exam.

Tentative time table: https://timeplan.uit.no/emne_timeplan.php?sem=22h&module[]=INF-3010-1#week-19

Registration
Master level students at UiT must register for the exam through the Studentweb within September 1st, 2022. Applicants from other universitys must apply within June 1st, 2022. Application code: 9371 - Singular courses at master's level.

Phd students at UiT must register for the exam through the Studentweb within September 1st, 2022. External phd students apply for admission for singular phd courses via UiTs application website within June 1st, 2022. Application code 9301 – Singular courses at PhD level.

Detailed information can be found here: https://uit.no/utdanning/opptaksinfo#innhold_711494


Kortnytt fra Institutt for informatikk
Fuglesteg, Jan jan.fuglesteg@uit.no Studierådgiver
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