IRMGR41118 Dynamic Modelling and Simulation of Micro Grids (Spring 2023)

Facts about the course

ECTS Credits:
10
Responsible faculty:
Faculty of Computer Sciences, Engineering and Economics
Campus:
Fredrikstad.
Course Leader:
Nicolae Lucian Mihet
Teaching language:
English.
Duration:
½ year

Table of contents

The course is affiliated to the following study programme

Master in Green Energy Technology (Compulsory in Smart Energy Technology profile).

Recommended previous knowledge

Basic knowledge of modelling and simulation tools and of implementation simple mathematical models of energy systems. Previous knowledge of the fundamental area within energy technology or the subject Renewable energy (10 ECTS) from the 1st semester courses.

Teaching semester

Second semester (spring).

Content

  • Introduction to simulation tools (MATLAB & Simulink, DiGSILENT Power Factory, NEPLAN)
  • Concepts in modeling and simulation
  • Theory and practice of modeling and analysis of distributed energy resources (DER) components (wind turbines (WT), photovoltaic (PV), Hydro Power, Smart Homes, Energy Storage Systems, Electric Vehicles (EVs))
  • Control strategies methods for distributed energy resources (DER) components and systems;
  • Dynamic properties and optimization models & techniques of electric generators and power electronic converters, used as main components of a Microgrid
  • Analyzing different dynamic system models suitable for Advanced Microgrids and Smart Grid Integration.

 

The course includes lectures with interactive models based design and simulation tools, labs with practical implementation of the models and with simulation exercises and an internal seminar on topic of modeling of renewable energy sources and energy conversion systems, with professors from other universities

The objectives of the course are to introduce the students to the fundamentals of energy conversion systems modeling, using state-of-the-art simulation tools. Combine theory and practice of modeling, optimization and simulation, addressing challenges on different time-scales involved in operation, optimization and design. Implementing a simple mathematical model of intelligent energy systems at different time-scale

The aim of the seminar is to practice connecting the topic to their own research through different perspectives from the field.

The student's learning outcomes on passing the course

Knowledge:

The student

  • has advanced knowledge of energy conversion systems modelling, and state-of-the-art simulation tools
  • has advance knowledge of distributed energy resources for Smart Grids and Microgrids.

 

Skills:

The student

  • can combine theory and practice of modelling, optimization and simulation, addressing challenges on different time-scales involved in operation, optimization and design of Microgrids
  • can implement a simple mathematical model of intelligent Distributed Energy Resources in a Microgrid at different time-scales
  • is able to develop a simulation model based on a block diagrams and/or a mathematical model.

 

General competence:

The student

  • can conduct project based learning using model based design in collaboration with other students
  • can present a scientific topic orally
  • can apply acquired knowledge and skills to solve advanced project tasks.

Teaching and learning methods

A variety of teaching and learning methods will be used, from regular lectures with basic teaching using video-projection and other interactive devices (dialogue-based teaching) but also using individual and group modelling and simulation exercises. The group work based teaching will force students to develop not only computer simulation skills but also to use their social skills in cooperation and communication. The course will also include the laboratory exercises and project work to develop project-based learning method, which will highlight the student¿s abilities in solving practical problems and teamwork. New topics and simulation tools will be introduced by presenting concrete examples and problems using teaching methods with an inductive approach.

Workload

250-300 hours.

Coursework requirements - conditions for taking the exam

  • 6 labs with simulation exercises based on written reports
  • 3 individual project's-based simulations + one individual project-based measurements

Exam

This exam consists of two parts:

Part 1: Written individual report. Counts as 40% of the final grade.

Part 2 Consist of two components:

  • Written report, in a group of 3-4 students
  • Oral presentation, 15 minutes per student in the group. Counts as 60% of the final grade. One overall grade will be awarded on the basis of all the components of part 2.

Individual grades are given for both parts of the exam

Grades from A to F, where A is the best grade, E is the lowest passed grade, and F is failed.

Examiners

One internal and one external examiner.

Conditions for resit/rescheduled exams

A re-take for both parts of the exam will be arranged in August the following semester.

Course evaluation

The course will be evaluated through a standardized electronic form.

Reading list

The current reading list for 2023 Spring can be found in Leganto
Last updated from FS (Felles studentsystem) Oct. 15, 2026 3:00:54 AM