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During 2021 we will continue to support students who need to study remotely due to the ongoing impacts of COVID-19 and travel restrictions. Make sure you check the location code when selecting a unit outline or choosing your units of study in Sydney Student. Find out more about what these codes mean. Both remote and on-campus locations have the same learning activities and assessments, however teaching staff may vary. More information about face-to-face teaching and assessment arrangements for each unit will be provided on Canvas.

Unit of study_

ELEC5203: Topics in Power Engineering

This unit of study provides an introduction to engineering optimisation, focusing specifically on practical methods for formulating and solving linear, nonlinear and mixed-integer optimisation problems that arise in science and engineering. The course is general enough to be of interest also for students from other engineering disciplines, not only for power engineering students. The course covers conventional optimisation techniques, including unconstrained and constrained single- and multivariable optimisation, convex optimisation, linear and nonlinear programming, mixed-integer programming, and sequential decision making using dynamic programming. The emphasis is on building optimisation models, understanding their structure and using off-the-shelf solvers to solve them. The application focus is on the optimisation problems arising in smart grids and electricity markets, including economic dispatch, unit commitment, home energy management and device scheduling. The course will use Matlab and AMPL as modelling tools and a range of state-of-the-art solvers, including Cplex, Gurobi, Knitro and Ipopt.


Academic unit Electrical and Information Engineering
Unit code ELEC5203
Unit name Topics in Power Engineering
Session, year
Semester 2, 2020
Attendance mode Normal day
Location Camperdown/Darlington, Sydney
Credit points 6

Enrolment rules

Assumed knowledge

Competence with linear algebra, differential calculus, numerical methods and Matlab; basic programming skills (Python or Matlab); familiarity with basic physics

Available to study abroad and exchange students


Teaching staff and contact details

Coordinator Gregor Verbic,
Type Description Weight Due Length
Final exam (Open book) Type C final exam Final exam
Final exam.
60% Formal exam period 2 hours
Outcomes assessed: LO1 LO2 LO4
Small test Homework problems
30% Multiple weeks n/a
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6
Small test Mid-semester exam
The mid-semester exam will cover the material covered up until Week 8.
10% Week 08 50 minutes
Outcomes assessed: LO1 LO2 LO4
Type C final exam = Type C final exam ?
  • Homework problems: Students are required to complete weekly tasks that apply knowledge gained in lectures and tutorials to solve practical power engineering problems.
  • In-semester exam: The in-semester exam tests students’ knowledge learned in the lectures and tutorials.
  • Final exam: the final exam tests students’ knowledge learned in lecture, tutorial, assignment, and lab.

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


High distinction

85 - 100



75 - 84



65 - 74



50 - 64



0 - 49

When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see

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.

Special consideration

If you experience short-term circumstances beyond your control, such as illness, injury or misadventure or if you have essential commitments which impact your preparation or performance in an assessment, you may be eligible for special consideration or special arrangements.

Academic integrity

The Current Student website provides information on academic honesty, academic dishonesty, and the resources available to all students.

The University expects students and staff to act ethically and honestly and will treat all allegations of academic dishonesty or plagiarism seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic dishonesty. If such matches indicate evidence of plagiarism or other forms of dishonesty, your teacher is required to report your work for further investigation.

WK Topic Learning activity Learning outcomes
Week 01 Introduction to optimisation (2 hr)  
Week 02 1. Classical optimisation techniques; 2. Single and multivariable unconstrained optimisation (4 hr)  
Week 03 1. Multivariable optimisation with equality constraints; 2. Solution by the method of Lagrange multipliers (4 hr)  
Week 04 1. Multivariable optimisation with inequality constraints; 2. Karush-Kuhn–Tucker optimality conditions (4 hr)  
Week 05 Convex optimisation (4 hr)  
Week 06 Linear programming (4 hr)  
Week 07 Economic dispatch (4 hr)  
Week 08 Nonlinear programming (4 hr)  
Week 09 Nonlinear programming (4 hr)  
Week 10 Mixed integer programming (4 hr)  
Week 11 Unit commitment problem (4 hr)  
Week 12 1. Sequential decision making; 2. Dynamic programming (4 hr)  
Week 13 Home energy management problem (4 hr)  

Attendance and class requirements

  • Study commitment: Tutorials are devoted to practising basic concepts covered in the lectures and understanding how more complex tasks can be handled by putting these basic concepts together. Students need to prepare for tutorials and  read the references to fully master the basic concepts covered in the lectures.

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.

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.

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

  • LO1. formulate engineering problems as optimisation problems and solve them using appropriate solvers
  • LO2. demonstrate an understanding of applied optimisation to be able to solve practical power engineering problems
  • LO3. demonstrate proficiency in using dedicated modelling tools and solvers for solving optimisation problems arising in power systems
  • LO4. apply linear algebra and differential calculus to solve applied optimisation problems
  • LO5. undertake inquiry and knowledge development by identifying the limits of the available information on applied optimisation in the context of power systems by drawing on relevant research papers and articles on the topic
  • LO6. deliver written and oral presentations using varied media aids and tools, to convey complex engineering material concisely and accurately

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
No changes have been made since this unit was last offered.


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