Course Title: Smart Grids

Part A: Course Overview

Course Title: Smart Grids

Credit Points: 12.00

Terms

Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)

EEET2613

City Campus

Undergraduate

172H School of Engineering

Face-to-Face

Sem 1 2022,
Sem 2 2023

Flexible Terms

Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)

EEET2631

SHAPE, VTC

Undergraduate

172H School of Engineering

Face-to-Face

OFFJan2023 (VE26)

Course Coordinator: Dr Kazi Hasan

Course Coordinator Phone: +61 3 9925 2238

Course Coordinator Email: kazi.hasan@rmit.edu.au

Course Coordinator Location: 10.11.12

Course Coordinator Availability: Appointment by email


Pre-requisite Courses and Assumed Knowledge and Capabilities

Assumed Knowledge

EEET2106 Power System Analysis and Control

The student should have a broad scientific and engineering background, sound knowledge of mathematics and statistics, and basic understanding of the operation of electrical power systems.


Course Description

This course provides theoretical insight and operational aspects of evolving electrical power grid with new types of generation resources, load components, telecommunication facilities, control architectures, data analytics, cyber security and protection requirements.

This course covers the basic aspects of smart grid components that include smart grid framework, smart generation, transmission, and distribution, smart grid communication and protection, smart cities, buildings and homes, and smart grid markets. The emphasis is on the smart grid enabling technologies that includes relevant theory, analysis, grid code and practical examples of demand response, electric vehicles, microgrids, and virtual power plants in the context of smart power systems.


Objectives/Learning Outcomes/Capability Development

At undergraduate level this course contributes to the following Program Learning Outcomes for students who commenced their program prior to 2023:

1.3 In-depth understanding of specialist bodies of knowledge within the engineering discipline.

2.1 Application of established engineering methods to complex engineering problem solving.

2.2 Fluent application of engineering techniques, tools and resources.

2.3 Application of systematic engineering synthesis and design processes.

At undergraduate level this course contributes to the following Program Learning Outcomes for students who commenced their program in 2023:

  • PLO1: Demonstrate an in-depth understanding and knowledge of fundamental engineering and scientific theories, principles and concepts and apply advanced technical knowledge in specialist domain of engineering. 
  • PLO2: Utilise mathematics and engineering fundamentals, software, tools and techniques to design engineering systems for complex engineering challenges.    
  • PLO4: Apply systematic problem solving, design methods and information and project management to propose and implement creative and sustainable solutions with intellectual independence and cultural sensitivity. 


On completion of this course, you should be able to:

  1. Explain and identify different components of smart grid systems/frameworks at different levels of electrical power systems, such as generation, transmission, distribution and power consumers.
  2. Explain and identify different levels of smart grid communication and protection.
  3. Explain the basic working principles of a smart grid with demand response and electric vehicles.
  4. Explain and identify different approaches of planning and operation of microgrids and virtual power plants.
  5. Explain and identify the operation and components of smart cities, buildings, homes, and smart grid markets.   
  6. Work in a team environment with nominal directions and converse engineering findings and designs through simulation experiments and written reports.


Overview of Learning Activities

The typical learning activities included in this course are:

  • Pre-recorded weekly lectures will introduce you to important principles and concepts.
  • The weekly tutorial classes will provide opportunities to apply a number of applicable numerical techniques used in practice to solve smart grid related problems.

Laboratory tasks that will help you to connect theory with practice and will reinforce the principles and concepts learned from the pre-recorded lecture materials. 


Overview of Learning Resources

The learning resources include:

  • Pre-recorded lecture videos and slides prepared and supplied by the academic staff.
  • Tutorial problems prepared and delivered by the academic staff.
  • Prescribed and recommended reference books and reading materials.
  • Simulation software to perform laboratory tasks.

Course materials are available through RMIT’s online systems.


Overview of Assessment

This course has no hurdle requirements.

 

Assessment Tasks

Assessment Task 1: Laboratory Tasks
Weighting 30%
This assessment task supports CLOs 3, 4, 5, and 6

Assessment Task 2: Mid-Semester Test
Weighting 20%
(This test will be a 1-hour test that may be taken any time within a specified 24-hour period)
This assessment task supports CLOs 1, 2, and 3

Assessment Task 3: End Semester Test
Weighting 20%
(This test will be a 1-hour test that may be taken any time within a specified 24-hour period)
This assessment task supports CLOs 3, 4, and 5

Assessment Task 4: Project Assignment
Weighting 30%;
This assessment supports CLOs 1, 2, 3, 4, 5, and 6