Course coordinator
Associate Professor Richard Yan
Course overview
- Study period
- Semester 1, 2025 (24/02/2025 - 21/06/2025)
- Study level
- Postgraduate Coursework
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Elec Engineering & Comp Science School
Covers renewable energy technologies around the world; current grid codes and standards and the major issue of intermittency; key technical challenges associated with renewable energy integration and ways to overcome them.
ELEC7313 will cover renewable energy (especially the most implemented new renewable technologies such as wind, solar PV and battery storage) integration challenges faced by power system operator, transmission-distribution utilities, energy retailors and end-users. This course will first focus on analysis and evaluation methods to clarify the techno-economic issues related to high renewable penetration, and then potential solutions will be introduced. The content is aimed at students with basic understanding of power system and renewable energy operation principles and is organized in a logical sequence as follows:
- Part 1: Generator level: Traditional synchronous machine technology versus new inverter-based generation technology (PV, wind and battery) including grid codes; Comparison of these technologies which paves the way for integration challenges at the network level;ﾠBasic analytical tool revisit (Power Flow);
- Part 2: High-Voltage Network level: A range of topics related to the core of large-scale network operation including frequency stability, system strength, sub-synchronous oscillation, economic dispatch, recent incidents and rule changes; A case study of the 2016 South Australian blackout to address the current integration challenges;ﾠ
- Part 3: Low-Voltage Network level: Residential roof-top PV and electric vehicle-related issues such as voltage rise, reverse power, voltage regulation, line capacity limits, grid visibility and battery control; UQ Gatton 3.3 MW PV case study for demonstrating evaluation methods and smart grid solutions.
The course will be complemented by guest lectures from local industry, covering their experiences, approaches and outlooks on renewable integration, with a special Australian focus.
Response to student feedback: Based on students' feedback from last year, more real-world case studies and examples have been incorporated in ELEC7313 this year which will help students to better understand the practical applications of theoretical concepts. Also, problem-based learning (PBL) sessions will be recorded this year.
Course requirements
Assumed background
Fundamental knowledge on power systems analysis.
Recommended prerequisites
We recommend completing the following courses before enrolling in this one:
ELEC4310
Course contact
Course staff
Lecturer
Associate Professor Richard Yan
Timetable
The timetable for this course is available on the UQ Public Timetable.
Additional timetable information
Sessions for laboratory experiments will be arranged by the teaching team during the semester. Please regularly check Blackboard announcement and your email.
Aims and outcomes
The overall aimﾠof the course is to expose students to the technical challenges and corresponding solutions related to renewable energy integration into the existing power networks, especially the challenges and solutions associated with the most popular wind,ﾠsolar PV and battery storage technologies due to their non-synchronous and highly variable characteristics. The corresponding development trend will also be introduced.
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Relate Renewable Energy and its integration to the techno-economic, environmental and social aspects of current international trends and developments
LO2.
Explain characteristics and control techniques of the traditional power generation and the new inverter based renewable generation
LO3.
Analyse the differences between traditional generators and inverter based generators with the context of integration impacts on the existing power networks
LO4.
Analyse characteristics of traditional synchronous machines, solar PV systems and wind generators through laboratory experiments (or demonstration) and effectively process the experimental data to reveal the working principles of each generation technology.
LO5.
Identify and evaluate the main challenges and solutions of renewable integration from transmission and distribution system perspectives.
LO6.
Assess PV integration impacts as a professional electrical engineer in a team environment and develop group skills such as effective collaboration and communication.
LO7.
Simulate and assess renewable integration impacts using industry software
LO8.
Explain and generalise how and why high renewable penetration can affect traditional network operation with respect to frequency stability, system strength, subsynchronous oscillation, economic dispatch, recent incidents and rule changes, voltage regulation, and capacity limitation
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Paper/ Report/ Annotation |
Problem Based Learning Assignments
|
10% |
PBL Assignment-1 17/03/2025 2:00 pm PBL Assignment-2 9/04/2025 2:00 pm PBL Assignment-3 7/05/2025 2:00 pm |
| Paper/ Report/ Annotation | Assignment | 20% |
19/05/2025 4:00 pm |
| Paper/ Report/ Annotation, Practical/ Demonstration |
Practical Assessment
|
30% |
Week 12 Mon - Week 13 Fri
More information on assessment schedules for individual students will be available on Blackboard before Week 12. The students should frequently check emails and Blackboard announcements. |
| Examination |
Final Exam
|
40% |
End of Semester Exam Period 7/06/2025 - 21/06/2025 |
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
Problem Based Learning Assignments
- Team or group-based
- Mode
- Written
- Category
- Paper/ Report/ Annotation
- Weight
- 10%
- Due date
PBL Assignment-1 17/03/2025 2:00 pm
PBL Assignment-2 9/04/2025 2:00 pm
PBL Assignment-3 7/05/2025 2:00 pm
- Other conditions
- Peer assessment factor.
- Learning outcomes
- L02, L03, L05, L06, L07, L08
Task description
There are three problem-based learning (PBL) assignments (the first one, 2%, individual submission; the second one, 3%, group based; the third one, 5%, group based). The grouping will be arranged during the PBL time. For the second and third PBL assignments based on groups, one group member is responsible for submitting the assignments online through UQ Blackboard. Each group only needs one submission for each group based PBL assignment. Group peer assessment is optional. Peer assessment should be provided in percentage regarding communication, timeliness and contribution. For example, student-A in a group of 2 students provides 50% Communication, 70% Timeliness and 80% Contribution for himself, and 50% Communication, 30% Timeliness and 20% Contribution for his group member. This means he thinks his overall performance (200% in total) is twice better than his group member (100% in total). Peer assessment needs to be submitted individually and confidentially to the course coordinator via emails before the due date of the assessment item. NOTE: if there is no peer review submitted by the due date, we will assume all of you have contributed equally. For a situation with large discrepancy, the lecturer or demonstrators will talk to whoever involved. Please raise your issues with evidence as early as possible regarding contribution of group members.
PBL Assignment-1: 2%, Individual
PBL Assignment-2: 3%, Group-based
PBL Assignment-3: 5%, Group-based
This task has been designed to be challenging, authentic and complex. Whilst students may use AI and/or MT technologies, successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance.
A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.
To pass this assessment, students will be required to demonstrate detailed comprehension of their written submission independent of AI and MT tools.
Submission guidelines
Individual or group online submission through Blackboard.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 7 days. Extensions are given in multiples of 24 hours.
This course uses a progressive assessment approach where feedback and/or detailed solutions will be released to students within 14 days.
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.
Assignment
- Mode
- Written
- Category
- Paper/ Report/ Annotation
- Weight
- 20%
- Due date
19/05/2025 4:00 pm
- Learning outcomes
- L02, L03, L05, L07, L08
Task description
Research Topic Background:
‒In this assignment, students will utilise widely used industry PSSE-Python platform to simulate and evaluate power systems with high renewable penetration. Students can also aim to achieve a high standard completion of this assignment by submitting PSSE and Python files to show a fully automated co-simulation platform. After validation of the files, the students who have submitted the files may obtain upto 3 marks bonus. This will be close to industry standard, but submission of the files is optional.
‒All the related materials (including assignment, relevant program, data and software training) will be given through UQ Blackboard. Some training will be provided through problem based learning sessions.
‒Students need to submit individual assignment answers through UQ Blackboard.
This task has been designed to be challenging, authentic and complex. Whilst students may use AI and/or MT technologies, successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance.
A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.
To pass this assessment, students will be required to demonstrate detailed comprehension of their written submission independent of AI and MT tools.
Submission guidelines
Individual online submission through Blackboard.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 7 days. Extensions are given in multiples of 24 hours.
This course uses a progressive assessment approach where feedback and/or detailed solutions will be released to students within 14 days.
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.
Practical Assessment
- Identity Verified
- In-person
- Mode
- Activity/ Performance, Oral, Written
- Category
- Paper/ Report/ Annotation, Practical/ Demonstration
- Weight
- 30%
- Due date
Week 12 Mon - Week 13 Fri
More information on assessment schedules for individual students will be available on Blackboard before Week 12. The students should frequently check emails and Blackboard announcements.
- Other conditions
- Time limited.
- Learning outcomes
- L02, L03, L04, L05
Task description
This Practical Assessment contains three aspects the students learn over the semester, and students will be requested to perform laboratory experiments and analyse characteristics of traditional synchronous machines (10%), solar PV systems (10%) and wind generators (10%) and also answer experiment related questions in written format. The students will conduct these experiments based on the provided instructions under the lecturer and/or demonstrators' guidance. After practice over the semester, the students will be asked to complete different assessments in the lab based on the lab activities, including physical wiring of electrical circuits in a group, conducting individual experiments, orally answering experimental questions and completing written questions. The Practical Assessment will be scheduled to complete in 3 hours (about 1-h for each aspect) for each student during the last two weeks of the semester (Week 12 and Week 13). Due to equipment constraints, student availability and experimental nature of this assessment, the Practical Assessment may be scheduled in sub-sessions. The lecturer and teaching demonstrators will schedule this Practical Assessment during the semester and publish the schedule before Week 12.
This assessment task is to be completed in-person. The use of generative Artificial Intelligence (AI) or Machine Translation (MT) tools will not be permitted. Any attempted use of AI or MT may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
Submit the assessment to the lecturer or demonstrators in the end of the scheduled Practical Assessment sessions.
Deferral or extension
You may be able to defer this exam.
Practical Assessment is completed as part of a scheduled period. If there are exceptional circumstances, an exemption may be approved and may involve rescheduling certain aspects in the Practical Assessment. Exemptions must be requested as an extension with a note specifying exemption via my.UQ.
Late submission
You will receive a mark of 0 if this assessment is submitted late.
Final Exam
- Hurdle
- Identity Verified
- In-person
- Mode
- Written
- Category
- Examination
- Weight
- 40%
- Due date
End of Semester Exam Period
7/06/2025 - 21/06/2025
- Other conditions
- Time limited.
- Learning outcomes
- L01, L02, L03, L05, L06, L08
Task description
Delivery Mode:
Paper-based on campus exam.
Timing:
The final exam will be centrally scheduled at a fixed time for all students – 10min planning time plus 120min exam time.
Permitted materials:
The exam is a closed-book exam, and the students are allowed to take one A4 sheet of handwritten notes double sided and an approved calculator.
Other information:
Final exam accounts for 40% or 40 marks out of 100 marks (full mark of this course). The student must achieve 40% (16 marks) or more out of 40 marks in the final exam in order to pass the course (hurdle). If 40% (16 marks) in the final exam are not achieved, then the grade will be capped to 3.
This assessment task is to be completed in-person. The use of generative Artificial Intelligence (AI) or Machine Translation (MT) tools will not be permitted. Any attempted use of AI or MT may constitute student misconduct under the Student Code of Conduct.
Hurdle requirements
Final exam accounts for 40% or 40 marks out of 100 marks (full mark of this course). The student must achieve 40% (16 marks) or more out of 40 marks in the final exam in order to pass the course (hurdle). If 40% (16 marks) in the final exam are not achieved, then the grade will be capped to 3.Exam details
| Planning time | 10 minutes |
|---|---|
| Duration | 120 minutes |
| Calculator options | (In person) Casio FX82 series only or UQ approved and labelled calculator |
| Open/closed book | Closed Book examination - specified written materials permitted |
| Materials | One A4 sheet of handwritten notes, double sided, is permitted |
| Exam platform | Paper based |
| Invigilation | Invigilated in person |
Submission guidelines
Deferral or extension
You may be able to defer this exam.
Course grading
Full criteria for each grade is available in the Assessment Procedure.
| Grade | Cut off Percent | Description |
|---|---|---|
| 1 (Low Fail) | 0 - 19 |
Absence of evidence of achievement of course learning outcomes. Course grade description: Some engagement with the assessment tasks; however no demonstrated evidence of understanding of the concepts in the field of study |
| 2 (Fail) | 20 - 46 |
Minimal evidence of achievement of course learning outcomes. Course grade description: Deficiencies in understanding the fundamental concepts of the field of study Inability to identify data, cases, problems and their solutions, and implications Presents inappropriate or unsupported arguments Inability to apply knowledge and skills Communicates information or ideas in ways that are frequently incomplete, confusing and not appropriate to the conventions of the discipline |
| 3 (Marginal Fail) | 47 - 49 |
Demonstrated evidence of developing achievement of course learning outcomes Course grade description: Superficial understanding of the fundamental concepts of the field of study Attempts to identify data, cases, problems and their solutions, and implications Presents undeveloped arguments Emerging ability to apply knowledge and skills Communicates information or ideas with limited clarity and inconsistent adherence to the conventions of the discipline |
| 4 (Pass) | 50 - 64 |
Demonstrated evidence of functional achievement of course learning outcomes. Course grade description: Adequate knowledge of fundamental concepts of the field of study Identifies data, cases, problems and their solutions, and implications Develops routine arguments or decisions Acceptable application of knowledge and skills Uses some of the conventions of the discipline to communicate appropriately |
| 5 (Credit) | 65 - 74 |
Demonstrated evidence of proficient achievement of course learning outcomes. Course grade description: Good knowledge of fundamental concepts of the field of study Considered evaluation of data, cases, problems and their solutions, and implications Develops or adapts convincing arguments and provides coherent justification Effective application of knowledge and skills Uses the conventions of the discipline to communicate at an effective level |
| 6 (Distinction) | 75 - 84 |
Demonstrated evidence of advanced achievement of course learning outcomes. Course grade description: Substantial knowledge of fundamental concepts of the field of study Critical evaluation of data, cases, problems and their solutions, and implications Perceptive insights in identifying, generating and synthesising competing arguments or perspectives Extensive application of knowledge and skills Uses the conventions of the discipline to communicate at a professional level |
| 7 (High Distinction) | 85 - 100 |
Demonstrated evidence of exceptional achievement of course learning outcomes. Course grade description: Mastery of content Expert and critical evaluation of data, cases, problems and their solutions, and implications Significant and sophisticated insights in identifying, generating and synthesising competing arguments or perspectives Original, novel and/or creative application of knowledge and skills Exploits the conventions of the discipline to communicate at an expert level |
Additional course grading information
The overall final marks will be rounded first, and then the final grade will be determined. The course coordinator reserves the right to moderate marks.
Supplementary assessment
Supplementary assessment is available for this course.
Additional assessment information
Any student who enrolls in a course must not be given exemptions or partial credit from their previous attempts for any piece of assessment.
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.
Additional learning resources information
Handouts
Any handouts including PBL sheets, lecture notes,ﾠpractical experiments, assignments and all other materials will be available through UQ Blackboard.ﾠIt is the student’s responsibility to make these documents available for their use.
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 |
|---|---|---|
Not scheduled |
Not Timetabled |
Visit to UQ Renewable Energy Lab An optional research lab visit to the state-of-the-art UQ Renewable Energy Lab will be organized to enrich your learning experience. Learning outcomes: L02, L05, L06 |
Multiple weeks From Week 1 To Week 13 |
Problem-based learning |
Project based learning (Problem solving, group project and discussion) Students will be working in groups on a given topic (or simulation) related to grid integration of renewable energy during general contact sessions. Learning outcomes: L01, L02, L03, L05, L06, L07, L08 |
Lecture |
Lectures Apart from the normal activities, guest lecturers from local industry and other areas of UQ will be invited to present industry activities on renewable energy integration. Learning outcomes: L01, L02, L03, L05, L06, L08 |
|
Multiple weeks From Week 4 To Week 13 |
Practical |
Lab Experiment (or Demonstration) Practicals focus on analyzing characteristics of traditional synchronous machines, solar PV systems and wind generators through laboratory experiments or demonstrations. Learning outcomes: L01, L02, L03, L04, L05 |
Additional learning activity information
Visit to UQ Renewable Energy Lab is optional and based on learning interest.
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 - Students Policy and Procedure
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.
You'll also need to be aware of the following policies and procedures while completing this course:
School guidelines
Your school has additional guidelines you'll need to follow for this course: