Course coordinator
Associate Professor Simon Smart
Happy to consult - generally Friday afternoons between 1-3pm. Please email first to confirm.
Course overview
- Study period
- Semester 1, 2026 (23/02/2026 - 20/06/2026)
- Study level
- Postgraduate Coursework
- Location
- St Lucia
- Attendance mode
- Intensive
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Chemical Engineering School
This course introduces students to the language of energy and key scientific principles that underpin energy systems. Students are provided with an overview of the energy challenge including supply and demand and future scenarios for 2050. Students will gain a comprehensive understanding of the suite of renewable energy and technology options available.
This course is one of the foundations of the Master of Sustainable Energy (MSE) program, and delivers background training on energy systems & technology. The course enables students to become familiar with energy related concepts and terminology, establishing a common understanding among the cohort to advance together through the program. It provides students with basic facts and the capacity to argue clear cases around energy challenges. In addition, it introduces concepts and skills that will be fundamental to later courses in the MSE program.
Course requirements
Assumed background
This course has no assumed background knowledge beyond the ability to perform simple mathematical operations.
There is some pre-course reading to do before the start of the intensive (available on Blackboard).
Incompatible
You can't enrol in this course if you've already completed the following:
ENGY0x is not compatible with ENGY7000, and ENGY4000
Restrictions
Restricted to MSE, GDSE, GCSE, MEI and GCEI students.
Course contact
Course staff
Lecturer
Dr Mike Tebyetekerwa
Dr Kaige Sun
Tutor
Ms Tammy MacGinley
Mr Ahmed Alhashim
Mr Mohammed Nasser H Alnasser
Ms Tiana Rafmiwati
Mr Freddi Andreas Togar
Timetable
The timetable for this course is available on the UQ Public Timetable.
Aims and outcomes
This course aims to provide students with:
- an understanding of the language of energy,
- an appreciation of the scale of the sustainable energy challenge facing Australia and the world,
- knowledge of the variety of technology options available for energy (typically electricity) generation and supply systems, and
- a suite of tools with which to analyse energy (typically electricity) systems.
The focus of the course is on developing technical confidence and competence to be able to critique familiar and unfamiliar sustainable energy challenges.
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Demonstrate an understanding of renewable and low-carbon electricity generation technologies, electricity grid infrastructure and supply systems (how electricity is transmitted and distributed between generators and load centres), and energy storage technologies including how they interact with electricity grids at different time scales
LO2.
Use analytical tools to evaluate electricity generation, grid infrastructure and energy storage technologies with respect to efficiency, resource utilisation, and environmental impact
LO3.
Analyse social, political and economic challenges of new technology deployment and provide the most effective strategies to overcome barriers to sustainable energy transition
LO4.
Effectively communicate to multiple audiences and stakeholders, sustainable solutions to multifaceted energy problems
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Tutorial/ Problem Set | Solar Energy Problem Set | 15% |
11/03/2026 5:00 pm |
| Tutorial/ Problem Set | Wind Energy Problem Set | 15% |
18/03/2026 5:00 pm |
| Paper/ Report/ Annotation | Net Zero Electricity System - Report | 30% |
1/04/2026 5:00 pm |
| Examination, Tutorial/ Problem Set |
Oral Exam
|
40% |
13/04/2026 - 17/04/2026
Exams will be scheduled in consultation with students for suitable time slots. The schedule will be published on Blackboard. |
A hurdle is an assessment requirement that must be satisfied in order to receive a specific grade for the course. Check the assessment details for more information about hurdle requirements.
Assessment details
Solar Energy Problem Set
- Mode
- Written
- Category
- Tutorial/ Problem Set
- Weight
- 15%
- Due date
11/03/2026 5:00 pm
- Learning outcomes
- L01, L02
Task description
Students will be given data and tools which they will use to evaluate the potential of a solar resource and the performance of solar PV panels.
A full description including the data to be used in the assessment will be included on Blackboard.
Artificial Intelligence (AI) and Machine Translation (MT) are emerging tools that may support students in completing this assessment task. Students may appropriately use AI and/or MT in completing this assessment task. Students must clearly reference any use of AI or MT in each instance. A failure to reference AI use may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
Please submit via the link on Blackboard.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 28 days. Extensions are given in multiples of 24 hours.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
An extension request is not considered late until 24 hours after the assessment due date & time.
Penalties Apply for Late Submission
Refer PPL Assessment Procedure Section 3 Part C (48)
A Student Access Plan (SAP) can only be used for a first extension. Extensions based on an SAP may be granted for up to seven (7) days, or the maximum number of days specified in the Course Instance (CI), if it is less than seven (7) days. Any further extensions will require additional supporting documentation, such as a medical certificate.
Wind Energy Problem Set
- Mode
- Written
- Category
- Tutorial/ Problem Set
- Weight
- 15%
- Due date
18/03/2026 5:00 pm
- Learning outcomes
- L01, L02
Task description
The problem set will examine wind speed corrections, turbine performance, wind resource evaluation and the impact of other factors on the overall performance of a wind farm.
Artificial Intelligence (AI) and Machine Translation (MT) are emerging tools that may support students in completing this assessment task. Students may appropriately use AI and/or MT in completing this assessment task. Students must clearly reference any use of AI or MT in each instance. A failure to reference AI use may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
Submission will be via a link in Blackboard.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 28 days. Extensions are given in multiples of 24 hours.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
An extension request is not considered late until 24 hours after the assessment due date & time.
Penalties Apply for Late Submission
Refer PPL Assessment Procedure Section 3 Part C (48)
A Student Access Plan (SAP) can only be used for a first extension. Extensions based on an SAP may be granted for up to seven (7) days, or the maximum number of days specified in the Course Instance (CI), if it is less than seven (7) days. Any further extensions will require additional supporting documentation, such as a medical certificate.
Net Zero Electricity System - Report
- Mode
- Written
- Category
- Paper/ Report/ Annotation
- Weight
- 30%
- Due date
1/04/2026 5:00 pm
- Learning outcomes
- L01, L02, L03, L04
Task description
Students will design a net zero emissions electricity system to service a given electricity demand using solar, wind and energy storage technologies. Full details included marking rubric are available on Blackboard.
The short report will include preliminary design details as well as some indicative costings and a discussion of the relevant environmental and social factors that need to be considered as part of the NZE pathway.
Artificial Intelligence (AI) and Machine Translation (MT) are emerging tools that may support students in completing this assessment task. Students may appropriately use AI and/or MT in completing this assessment task. Students must clearly reference any use of AI or MT in each instance. A failure to reference AI use may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
Submission via Blackboard.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 28 days. Extensions are given in multiples of 24 hours.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
An extension request is not considered late until 24 hours after the assessment due date & time.
Penalties Apply for Late Submission
Refer PPL Assessment Procedure Section 3 Part C (48)
A Student Access Plan (SAP) can only be used for a first extension. Extensions based on an SAP may be granted for up to seven (7) days, or the maximum number of days specified in the Course Instance (CI), if it is less than seven (7) days. Any further extensions will require additional supporting documentation, such as a medical certificate.
Oral Exam
- Hurdle
- Identity Verified
- In-person
- Mode
- Oral
- Category
- Examination, Tutorial/ Problem Set
- Weight
- 40%
- Due date
13/04/2026 - 17/04/2026
Exams will be scheduled in consultation with students for suitable time slots. The schedule will be published on Blackboard.
- Other conditions
- Time limited.
- Learning outcomes
- L01, L02, L03
Task description
Students will participate in an oral exam with a member of the course teaching team. All course content and case studies are assessable during the exam. The focus is on your individual learning from the course. You will be given 5 minutes to read through material before discussing, interview style, for 20 minutes.
This assessment task evaluates students' abilities, skills and knowledge without the aid of generative Artificial Intelligence (AI) or Machine Translation (MT). Students are advised that the use of AI or MT technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.
Hurdle requirements
Students must pass (>=50%) this exam to pass the course.Exam details
| Planning time | 5 minutes |
|---|---|
| Duration | 20 minutes |
| Calculator options | (In person) Casio FX82 series only or UQ approved and labelled calculator |
| Open/closed book | Closed book examination - no written materials permitted |
| Exam platform | Other |
| Invigilation | Invigilated in person |
Submission guidelines
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 28 days. Extensions are given in multiples of 24 hours.
Late submission
An extension request is not considered late until 24 hours after the assessment due date & time.
Penalties Apply for Late Submission
Refer PPL Assessment Procedure Section 3 Part C (48)
A Student Access Plan (SAP) can only be used for a first extension. Extensions based on an SAP may be granted for up to seven (7) days, or the maximum number of days specified in the Course Instance (CI), if it is less than seven (7) days. Any further extensions will require additional supporting documentation, such as a medical certificate.
Course grading
Full criteria for each grade is available in the Assessment Procedure.
| Grade | Description |
|---|---|
| 1 (Low Fail) |
Absence of evidence of achievement of course learning outcomes. Course grade description: (0-29.99%) Low Fail: Absence of evidence of achievement of course learning outcomes |
| 2 (Fail) |
Minimal evidence of achievement of course learning outcomes. Course grade description: (30-44.99%) Fail: Minimal evidence of achievement of course learning outcomes |
| 3 (Marginal Fail) |
Demonstrated evidence of developing achievement of course learning outcomes Course grade description: (45-49.99%) Marginal Fail: Demonstrated evidence of developing achievement of course learning outcomes |
| 4 (Pass) |
Demonstrated evidence of functional achievement of course learning outcomes. Course grade description: (50-64.99%) Pass: Demonstrated evidence of functional achievement of course learning outcomes |
| 5 (Credit) |
Demonstrated evidence of proficient achievement of course learning outcomes. Course grade description: (65-74.99%) Credit: Demonstrated evidence of proficient achievement of course learning outcomes |
| 6 (Distinction) |
Demonstrated evidence of advanced achievement of course learning outcomes. Course grade description: (75-84.99%) Distinction: Demonstrated evidence of advanced achievement of course learning outcomes |
| 7 (High Distinction) |
Demonstrated evidence of exceptional achievement of course learning outcomes. Course grade description: (85-100%) High Distinction: Demonstrated evidence of exceptional achievement of course learning outcomes |
Additional course grading information
Students must pass (>=50%) the oral exam to pass the course.
Supplementary assessment
Supplementary assessment is available for this course.
Supplementary assessment will take the form of an oral exam. Students will need to answer 5 of 8 questions correctly to pass the supplementary exam.
Learning resources
You'll need the following resources to successfully complete the course. We've indicated below if you need a personal copy of the reading materials or your own item.
Library resources
Find the required and recommended resources for this course on the UQ Library website.
Learning activities
The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.
Filter activity type by
Please select
| Learning period | Activity type | Topic |
|---|---|---|
Week 1 |
Lecture |
Lectures Primary content delivery for the course. These are timetabled as General Contact Hours, but will be a series of lectures across 2 days in Week 1. Will cover (typical order):
Learning outcomes: L01, L02, L03 |
Multiple weeks From Week 2 To Week 6 |
Workshop |
Workshops These workshops will extend initial lecture material and introduce problem sets. A typical structure would be:
Topics covered include (but not limited to):
Learning outcomes: L01, L02, L03, L04 |
Policies and procedures
University policies and procedures apply to all aspects of student life. As a UQ student, you must comply with University-wide and program-specific requirements, including the:
- Student Code of Conduct Policy
- Student Integrity and Misconduct Policy and Procedure
- Assessment Procedure
- Examinations Procedure
- Reasonable Adjustments for Students Policy and Procedure
- AI for Assessment Guide
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.