Course Title: Renewable Electrical Energy Systems
Part A: Course Overview
Course Title: Renewable Electrical Energy Systems
Credit Points: 12.00
Terms
Course Code |
Campus |
Career |
School |
Learning Mode |
Teaching Period(s) |
EEET2334 |
City Campus |
Undergraduate |
125H Electrical & Computer Engineering |
Face-to-Face |
Sem 2 2010, Sem 2 2011, Sem 1 2012, Sem 2 2013, Sem 2 2014, Sem 2 2015, Sem 2 2016 |
EEET2334 |
City Campus |
Undergraduate |
172H School of Engineering |
Face-to-Face |
Sem 2 2017, Sem 2 2018, Sem 2 2019, Sem 2 2020, Sem 2 2021, Sem 2 2022, Sem 2 2023, Sem 2 2024 |
EEET2335 |
City Campus |
Postgraduate |
125H Electrical & Computer Engineering |
Face-to-Face |
Sem 2 2010, Sem 2 2011, Sem 1 2012, Sem 2 2013, Sem 2 2014, Sem 2 2015, Sem 2 2016 |
EEET2335 |
City Campus |
Postgraduate |
172H School of Engineering |
Face-to-Face |
Sem 2 2017, Sem 2 2018, Sem 2 2019, Sem 2 2020, Sem 2 2021, Sem 2 2022, Sem 2 2023, Sem 2 2024 |
Flexible Terms
Course Code |
Campus |
Career |
School |
Learning Mode |
Teaching Period(s) |
EEET2412 |
SHAPE, VTC |
Undergraduate |
172H School of Engineering |
Face-to-Face |
OFFSe22017 (VE18) |
EEET2412 |
SHAPE, VTC |
Undergraduate |
172H School of Engineering |
Face-to-Face |
OFFSep2018 (VE20) |
EEET2412 |
SHAPE, VTC |
Undergraduate |
172H School of Engineering |
Face-to-Face |
OFFSep2019 (VE22), OFFSep2019 (VE25), OFFSep2019 (All) |
EEET2412 |
SHAPE, VTC |
Undergraduate |
172H School of Engineering |
Face-to-Face |
OFFSep2020 (VE24), OFFSep2020 (VE27) |
EEET2412 |
SHAPE, VTC |
Undergraduate |
172H School of Engineering |
Face-to-Face |
OFFSep2021 (VE26) |
EEET2412 |
SHAPE, VTC |
Undergraduate |
172H School of Engineering |
Face-to-Face |
OFFSep2022 (VE28) |
EEET2412 |
SHAPE, VTC |
Undergraduate |
172H School of Engineering |
Face-to-Face |
OFFSep2024 (All) |
Course Coordinator: Dr. Manoj Datta
Course Coordinator Phone: +61 3 9925 2105
Course Coordinator Email: manoj.datta@rmit.edu.au
Course Coordinator Location: 10.08.10
Course Coordinator Availability: contact by email to arrange a meeting time
Pre-requisite Courses and Assumed Knowledge and Capabilities
You should have completed a programming course and several mathematical courses. You should be able to analyse electrical energy circuits and conduct mathematical analyses. It is assumed that you have a broad scientific and engineering background and can for example perform energy balance analysis of renewable energy systems.
Course Description
This course will introduce you to renewable electrical energy systems, their characteristics, design procedures and economic analysis. Major renewable energy sources such as solar PV and Wind will be covered in detail. The emphasis is on the design and analysis of practical renewable electrical energy systems as well as on the distributed generation, recent grid codes and economic analysis of renewable energy sources in the context of a smart grid.
Please note that if you take this course for a bachelor honours program, your overall mark in this course will be one of the course marks that will be used to calculate the weighted average mark (WAM) that will determine your award level. (This applies to students who commence enrolment in a bachelor honours program from 1 January 2016 onward. See the WAM information web page for more information.
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.
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.
- PLO3: Apply engineering research principles, methods and contemporary technologies and practices to plan and execute projects taking into account ethical, environmental and global impacts.
- 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.
At postgraduate level this course develops the following Program Learning Outcomes for:
- High levels of technical competence in the field.
- Be able to apply problem solving approaches to work challenges and make decisions using sound engineering methodologies.
Upon successful completion of this course, you will be able to:
- Analyse the characteristics of a PV system, explain and develop a maximum power point tracking algorithm, and design grid-connected PV systems, standalone PV systems, and PV-based water pumping systems.
- Explain and identify different components of a wind power generation system and analyse the output power characteristics, design grid-connected wind power systems, and estimate and analyse available wind power for a specific wind resource site using probability density functions.
- Explain and identify different components of standard energy storage systems and design charging/ discharging control based on averaging algorithm.
- Design renewable energy-based microgrids and perform economic analysis and feasibility study.
- Understand the structure and various elements of distributed generation (DG) and their advantages and disadvantages including renewable and non-renewable generators in the context of smart grid codes around the world and Australia.
- Understand and apply the Standards AS/NZS 4777.1 and AS/NZS 4772.2: Grid connection of energy systems via inverters.
- Work in a team environment with nominal directions and converse engineering findings and designs through modelling experiments and written reports.
Overview of Learning Activities
Student Learning occurs through the following experiences and evaluation processes:
- Viewing weekly pre-recorded lecture videos will guide you to important theoretical concepts and principles of renewable energy systems.
- Weekly lectorials will allow you to attempt a range of renewable generator-based mathematical and design problems and receive feedback on solution strategies.
- Weekly laboratory classes will guide you through modelling, simulating and developing renewable energy systems.
- Microgrid design workshops will guide you to design and perform a feasibility analysis of a microgrid using industrial/professional design tools.
Overview of Learning Resources
The learning resources include:
- Videos and lecture notes.
- Lectorial problems and solutions.
- Prescribed and recommended reference books and reading materials: for details see the course guide Part B.
- Professional and Industrial design tools and software during the laboratory classes.
- Online course contents and materials available on the course Canvas.
Overview of Assessment
☒This course has no hurdle requirements.
The assessment tasks for this course include formative and summative elements. The formative elements will be conducted during the normal semester teaching period and enable students to receive feedback on their performance. The summative element is a final measure of student’s performance in order to evaluate the extent to which the student have achieved the learning outcomes listed above.
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Assessment tasks: Online Quizzes Weighting 20% This assessment task supports Course Learning Outcomes (CLOs) 1, 2, 3, 4, 5, & 6 Mid-semester Assessment (on campus) Weighting 20% This assessment task supports Course Learning Outcomes (CLOs) 1 & 2 Laboratory Exercises Weighting 30% This assessment task supports Course Learning Outcomes (CLOs) 1, 2, 4, & 7 Design Assignment Weighting 30% This assessment supports Course Learning Outcomes (CLOs) 1, 2, 3, 4, 5, 6, & 7 |