Outline

Overview

The unit deals with power systems modelling, analysis and simulation under dynamic conditions. The unit will cover the following topics: The links between power system steady state analysis and transient analysis; Basics of dynamic system in general and stability analysis methods; Analysis of power systems subject to electromagnetic and electromechanical transients. Power system modelling for stability analysis and electromagnetic transients analysis: Synchronous machine modelling using Park's transformation; Modelling of excitation systems and turbine governors; Modelling of the transmission system; Load modelling. Simulation of interconnected multi-machine systems; Stability analysis- Transient stability, Small signal stability, Voltage stability; Power system control: Voltage control, Power system transient stability control, Power system dynamic stability control, Emergency control; The unit is a specialist Unit for MPE (Power and Electrical) and ME (Power and Electrical). It is also available as a recommended elective for BE Electrical (Power).

Unit details and rules

Academic unit	School of Electrical and Computer Engineering
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	ELEC3203 or ELEC9203 or ELEC5732. The assumed knowledge for learning this UoS is a deep understanding on circuit analysis and its applications in power system steady state analysis
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Jin Ma, j.ma@sydney.edu.au

Assessment

The census date for this unit availability is 31 March 2026

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Written exam	Final Exam Supervised exam	55%	Formal exam period	2 hours	AI prohibited
Outcomes assessed:
In-class quiz	Week 3 Early Feedback Quiz On-line Canvas quiz	10%	Week 03 Due date: 09 Mar 2026 at 16:00	1 hour	AI allowed
Outcomes assessed:
Experimental design	Lab Complete the lab and submit the report	15%	Week 08 Due date: 24 Apr 2026 at 23:59	N/A	AI allowed
Outcomes assessed:
Experimental design	Project Complete the project and submit the project report	20%	Week 12 Due date: 22 May 2026 at 23:59	N/A	AI allowed
Outcomes assessed:
= group assignment ? = early feedback task ?

Assessment summary

Early Assessment: Set on week 3 to give students early feedback on their progresses in studying this course.
Final Exam: Individual based 2-hour close book exam to test students’ understandings on the knowledge and the problem solving skills
Lab: Practical group work to carry out the power system steady state and dynamic analysis for a Single Machine Infinite Bus system.
Project: Build a model of a multi-machine power system and analyse its dynamic behavior using simulation methods.

Minimum Performance Criteria: The WAM of all assessment components reaches 50 marks.

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name	Mark range	Description
High distinction	85 - 100	Solve the asked questions correctly. Provide clear and correct interpretations on the solutions of the problem. Effectively communicate the results to the readers.
Distinction	75 - 84	Attend to the details correctly and solve the asked questions with minor mistakes
Credit	65 - 74	Build the correct models with clear physical understandings and demonstrate attention to the required details in the solution process
Pass	50 - 64	Demonstrate a basic understanding on the theory and methods to solve the problem through using the correct formula and correct solution procedure
Fail	0 - 49	When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see guide to grades.

Use of generative artificial intelligence (AI)

You can use generative AI tools for open assessments. Restrictions on AI use apply to secure, supervised assessments used to confirm if students have met specific learning outcomes.

Refer to the assessment table above to see if AI is allowed, for assessments in this unit and check Canvas for full instructions on assessment tasks and AI use.

If you use AI, you must always acknowledge it. Misusing AI may lead to a breach of the Academic Integrity Policy.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

10% daily for late submission on lab report and project report.

Academic integrity

The University expects students to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

Our website provides information on academic integrity and the resources available to all students. This includes advice on how to avoid common breaches of academic integrity. Ensure that you have completed the Academic Honesty Education Module (AHEM) which is mandatory for all commencing coursework students

Penalties for serious breaches can significantly impact your studies and your career after graduation. It is important that you speak with your unit coordinator if you need help with completing assessments.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

Learning support

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Support for students

The Support for Students Policy reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

Weekly schedule

WK	Topic	Learning activity
Multiple weeks	Review lecture notes; Work on tutorial questions and lab work; Study the subjects that are used in learning this course and acquire further information extending the class contents via drawing on vast resources.	Self-directed learning (56 hr)
Week 01	A general introduction to this Unit of Study and to power system dynamics and control including the definition of power system dynamics and stability, mathematical interpretation as well as physical interpretation of power system dynamics and stability, a history review on power system dynamics and stability, the classification of the power system stability, and the connections of power system dynamics with other research areas in power system operation and control.	Seminar (2 hr)
Week 02	Review Laplace Transformation/numerical simulation methods; General nonlinear dynamic system modeling and Lyapunov stability	Seminar (2 hr)
Week 03	General nonlinear dynamic system modeling and Lyapunov stability (Cont'); Fundamentals of Electromagnetic Transients; Early feedback assessment; Tutorial 1	Tutorial (2 hr)
Week 04	Per unit system; Power flow and its solution; Modeling transmission Network in dynamic studies; Tutorial 2	Tutorial (2 hr)
Week 05	Introduction to power system dynamic modeling, Analysis on the electric field and the magnetic field of the generator; Modelling generator in three-phase coordinates; Tutorial 3	Tutorial (2 hr)
Week 06	Equation of Motion and the introduction to transient Stability; Lab 1	Lecture (4 hr)
Week 07	Transient stability studies on SMIB system; Lab 2	Lecture (4 hr)
Week 08	Excitation controller/Governor/numerical simulation methods on analyzing power system stability; Lab 3	Lecture (4 hr)
Week 09	Electro-magnetic transients modelling of generator, park transformation, some applications of the generator electro-magnetic transient modelling; Lab 4	Lecture (4 hr)
Week 10	Application of electro-magnetic generator models in power system dynamic studies; Generator models with different accuracy; Developing the pre-fault, fault-on, post-fault electricity network model; Lab 5	Lecture (4 hr)
Week 11	Generator operational parameters and transfer function model; Kron reduction and simulate the electricity networks in power system stability and control; Lab 6	Lecture (4 hr)
Week 12	Equal Area Criteria and numerical analysis for power system stability, from SMIB to Multi-machine power systems; Tutorial 4	Lecture (4 hr)
Week 13	Multi-machine power system dynamic analysis and control; Review of the whole course; Tutorial 5	Lecture (4 hr)

Attendance and class requirements

Attending the class to complete the early assessment task is compulsory

Attend the class and engage the discussions with the teacher.

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

The lecture notes are developed upon combination of a few references and self-contained for this UoS.

Reading the following books can be helpful in understanding the power system dynamics, stability and control, but is not compulsory.

P. Kundur, Power System Stability and Control. New York, McGraw-Hill, Inc., 1994. 978-0070359581
P.M.Anderson, A.A.Fouad, Power System Control and Stability, IEEE Press, 2003, 0-471-23862-7

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

Outcomes
Graduate qualities

At the completion of this unit, you should be able to:

LO1. explain the definition, causes and fundamental analysis methods on power system dynamics
LO2. explain state-space based multi-variable system modelling and linearization methods with their applications on power system dynamics and control
LO3. Explain the concepts of Lyapunov stability and its related analysis methods on nonlinear systems with the applications to power system dynamics.
LO4. model the power system major components for power system dynamic analysis and control
LO5. Explain the feedback control mechanisms and their applications in power system control
LO6. calculate the steady state power system operation point and clarify the connections between the power system steady state studies and power system dynamic studies
LO7. calculate the generator rotor dynamic trajectories after being disturbed and evaluate the transient stability of power system
LO8. evaluate the power system small-signal stability using eigenvalue based approaches
LO9. apply computer simulation algorithms to analyse power system dynamics for single-machine-infinite-bus power system and multi-machine power system with simplified controls
LO10. present concise information accurately through calculation and interpretation on the numerical results for course related problems

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

One tutorial hour is added to support the students to learn. Tutorial questions are updated.

Additional information

Work, health and safety

No food and drinks in the lab environment.

Disclaimer

Important: the University of Sydney regularly reviews units of study and reserves the right to change the units of study available annually. To stay up to date on available study options, including unit of study details and availability, refer to the relevant handbook.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Work, health and safety

Disclaimer

On this page

Useful links

ELEC5211: Power System Dynamics and Control

Semester 1, 2026 [Normal day] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Work, health and safety

Disclaimer

On this page

Useful links