course-details-portlet

ELDI1001 - Renewable Energy Informatics

About

Examination arrangement

Examination arrangement: Aggregate score
Grade: Letter grades

Evaluation Weighting Duration Grade deviation Examination aids
School exam 40/100 4 hours D
Portfolio 60/100

Course content

Renewable Energy Informatics involves decarbonization, decentralization and digitalization components of next generation power systems. The course aims to play a guidance role by elaborating the basic definitions and principles of digitalization (digital shift) and decarbonization (green shift) under three main sections:

  • Section 1: Foundations of renewable energy technologies (wind, solar and hydropower) and electrification (Electric Ships, Electric Aviation, Energy Storage Units, Electric Vehicles),
  • Section 2: Basics of information and communication technology used for smart grids, (Smart Grids, SCADA, Energy Management Systems, Internet of Energy and Computational Platforms for Energy Informatics)
  • Section 3: Introduction to energy analytics and informatics using artificial optimization, intelligence and blockchain technology. (Energy Forecasting, Use of AI in Energy Systems, Energy Blockchain, Sharing Economy & Future Energy Systems)

Students are expected to gain the core skills which will be necessary to conceive the basics of the digital and green shift related topics, develop initial design, implementation and operate skills by using the information systems competencies and multi-disciplinary knowledge.

Learning outcome

Knowledge:

After successfully completing this course, the students will be able to comprehend, analyze, assess, and apply, as applicable, the following:

  • Basics of renewable energy systems, electrification and digitalization technologies,
  • Methods of designing, modeling and analysis of renewable energy systems such as wind and solar energy systems,
  • Methods used in digitalization technologies such as blockchain technology, artificial intelligence, big data,
  • Understanding of innovative renewable energy management and electrification concepts.

Skills:

After completing this course the student will be able to:

  • Understand the importance and drivers of the green and digital energy transition,
  • Understand the effect of electrification on power systems and markets,
  • Perform simple analysis of how various renewable energy systems work,
  • Calculate annual energy yield from various renewable energy resources.
  • Understand basic principles of artificial intelligence, machine learning and big data,
  • Perform simple analysis of how various digitalization methods and technologies work in the energy domain,
  • Understand the fundamentals of energy analytics and time series forecasting tools using statistics or machine learning,
  • Understand how blockchain technology works

Learning methods and activities

Lectures, exercise lectures, mandatory exercises and small projects will be prepared using Conceive, Design, Implement and Operate (CDIO) pedagogical convention.

Compulsory assignments

  • Assignments
  • Laborotory

Further on evaluation

40% Exam, 60%: Project (2 x Practical Sessions and 1 x presentation) and exercises (4 x assessments).

Assignment 1: RES Assignment 2: RES Assignment 3: Electrification Practical session 1: IIot and communication with Raspberry Pi Assignment 4: AI/ML using Rapidminer Practical session 2: Combine Rapidminer and AEMS Presentations: Mini Literature review on the chosen topic

Written Exam and assignment must be answered in English.

Re-sit exam

The written school exam can be re-taken as a re-sit in August. In the event of a re-sit examination, the examination may be changed to an oral examination.

If you fail the project, the whole course must be re-taken as a whole.

Specific conditions

Course materials

Announced at the start of semester.

More on the course

No

Facts

Version: 1
Credits:  7.5 SP
Study level: Foundation courses, level I

Coursework

Term no.: 1
Teaching semester:  AUTUMN 2023

Language of instruction: English

Location: Trondheim

Subject area(s)
  • Electrical Power Engineering
Contact information
Course coordinator: Lecturer(s):

Department with academic responsibility
Department of electric energy

Examination

Examination arrangement: Aggregate score

Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
Autumn ORD School exam 40/100 D 2023-11-29 15:00 INSPERA
Room Building Number of candidates
SL111 blå sone Sluppenvegen 14 36
Autumn ORD Portfolio 60/100
Room Building Number of candidates
Summer UTS School exam 40/100 D INSPERA
Room Building Number of candidates
  • * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
Examination

For more information regarding registration for examination and examination procedures, see "Innsida - Exams"

More on examinations at NTNU