Unit Outline

This unit provides students with the skills and knowledge required to model energy systems in an environment where generation, demand and energy storage in power systems are rapidly evolving. Students will develop energy balance models for individual power systems components, based on realisation of physical processes associated with for example hydro storage and generation, battery storage, renewable sources of generation and fixed and flexible demand, and will then develop simulations of complete power systems under a range of different scenarios. Students will gain skills in running energy system simulations and appropriately interpreting outcomes in order to formulate well-articulated rationale for and descriptions of future energy systems. Students will gain an understanding of energy markets and their role in shaping future energy systems.

Intended Learning Outcomes

As per the Assessment and Results Policy 1.3, your results will reflect your achievement against specified learning outcomes.

On completion of this unit, you will be able to:


1	Identify key elements required for energy systems modelling, based on physical power systems components
2	Evaluate approaches for energy delivery in power systems, including energy services not currently electrified
3	Interpret large energy system modelling study assumptions, data inputs and key outcomes
4	Quantify key enablers for renewable energy based power systems via energy system modelling
5	Quantify the interaction of renewable generation with energy markets by applying knowledge of energy economics and energy markets

Requisites


REQUISITE TYPE	REQUISITES
Pre-requisite	ENG767 Power Systems 1

Alterations as a result of student feedback

Adjustments to timing of some assessments

How will I be Assessed?

For more detailed assessment information please see MyLO.

Assessment schedule


ASSESSMENT TASK #	ASSESSMENT TASK NAME	DATE DUE	WEIGHT	LINKS TO INTENDED LEARNING OUTCOMES
Assessment Task 1:	In-semester Test	Week 10	20 %	LO1, LO3, LO5
Assessment Task 2:	Presentation	Week 11	10 %	LO4, LO5
Assessment Task 3:	Major Project	Week 14	40 %	LO2, LO3, LO4
Assessment Task 4:	Energy System Dispatch Model Assignments (x 2)	Refer to Assessment Description	30 %	LO1, LO2, LO4

Assessment details

Assessment Task 1: In-semester Test

Task Description:

In-semester test
Students will be required, under timed test conditions, to complete a short coding and energy systems analysis test.

Generative AI use is not permitted for this task.

Task Length:

90 minutes

Due Date:

Week 10

Weight:

20 %

CRITERION #

CRITERION

MEASURES INTENDED

LEARNING OUTCOME(S)


1	Define key characteristics, inputs, outputs, state variables, relationships and constraints for a variety of power system components	LO1
2	Analyse and interpret energy systems modelling data for a power system containing renewable energy and storage	LO3
3	Describe typical financing and contract management processes as they apply to a new renewable energy project	LO5
4	Explain how energy markets operate and how renewable generation interacts with markets	LO5

Assessment Task 2: Presentation

Task Description:

Presentation assignment
In this presentation students will focus on the actions needed to successfully integrate a new renewable project into an energy system. Students will apply their knowledge of energy market operation and data to present a business case for a new renewable energy project.

Generative AI use is permitted for this task, but must be acknowledged.

Task Length:

15 minutes

Due Date:

Week 11

Weight:

10 %

CRITERION #

CRITERION

MEASURES INTENDED

LEARNING OUTCOME(S)


1	Describe the actions needed to successfully integrate a new renewable project into an energy system	LO4
2	Present a business case for a new renewable energy project based on knowledge of energy market operation and data	LO5

Assessment Task 3: Major Project

Task Description:

Major project
Apply energy system modelling approaches to the selection of renewable energy generators and to selecting an suitable mix of generation, storage and flexible demand for an energy system.
The findings of this project will be shared through a written report.

Generative AI use is permitted in development of code and for written elements of this task, but must be acknowledged.

Task Length:

25 pages

Due Date:

Week 14

Weight:

40 %

CRITERION #

CRITERION

MEASURES INTENDED

LEARNING OUTCOME(S)


1	Develop and validate an integrated energy balance model of a power system containing a variety of components	LO2
2	Evaluate outcomes for a range of modelled energy system scenarios	LO2
3	Justify selection of renewable generation and storage technologies, by interpreting energy system modelling	LO3
4	Quantify, via energy system modelling, a suitable mix of generation, storage and flexible demand for an energy system	LO4

Assessment Task 4: Energy System Dispatch Model Assignments (x 2)

Task Description:

Assignment (x2)

Assignment 1 due week 5
In this assignment students will define key characteristics, inputs, outputs, relationships and constraints for a variety of power system components and develop and apply simple energy balance models to solve merit order dispatch in a small, closed system.

Assignment 2 due week 8
In this assignment students will define key characteristics, inputs, outputs, state variables, relationships and constraints for a variety of power system components and develop and apply simple mathematical descriptions of state variable transitions for those components, and include merit order dispatch to meet demand and balance resources.

Generative AI use is permitted in development of code and for written elements of this task, but must be acknowledged.

Task Length:

10 pages each

Due Date:

Refer to Assessment Description

Weight:

30 %

CRITERION #

CRITERION

MEASURES INTENDED

LEARNING OUTCOME(S)


1	Define key characteristics, inputs, outputs, state variables, relationships and constraints for a variety of power system components	LO1
2	Develop and apply simple mathematical descriptions of state variable transitions for energy balance modelling of energy system components	LO2
3	Evaluate a range of published energy systems modelling studies to specify the requirements for power systems to host large amounts of renewable energy generation	LO4

How your final result is determined

To pass this unit, you need to demonstrate your attainment of each of the Intended Learning Outcomes and achieve a final unit grade of 50% or greater.

To pass ILO1 your aggregate mark on the components of the Assignments and the In-semester Test assessing ILO1, weighted according to their contribution to the final mark, must be greater than or equal to 50%.

To pass ILO2 your aggregate mark on the components of the Assignments and the Major Project assessing ILO2, weighted according to their contribution to the final mark, must be greater than or equal to 50%.

To pass ILO3 your aggregate mark on the components of the Assignments and the Major Project assessing ILO3, weighted according to their contribution to the final mark, must be greater than or oequal to 50%.

To pass ILO4 your aggregate mark on the components of the Major Project and the Presentation assessing ILO4, weighted according to their contribution to the final mark, must be greater than or equal to 50%.

To pass ILO5 your aggregate mark on the components of the Presentation and the In-semester Test assessing ILO5, weighted according to their contribution to the final mark, must be greater than or equal to 50%.

Academic progress review

The results for this unit may be included in a review of your academic progress. For information about progress reviews and what they mean for all students, see Academic Progress Review in the Student Portal.

Submission of assignments

Where practicable, assignments should be submitted to an assignment submission folder in MYLO. You must submit assignments by the due date or receive a penalty (unless an extension of time has been approved by the Unit Coordinator). Students submitting any assignment in hard copy, or because of a practicum finalisation, must attach a student cover sheet and signed declaration for the submission to be accepted for marking.

Academic integrity

Academic integrity is about acting responsibly, honestly, ethically, and collegially when using, producing, and communicating information with other students and staff members.

In written work, you must correctly reference the work of others to maintain academic integrity. To find out the referencing style for this unit, see the assessment information in the MyLO site, or contact your teaching staff. For more detail about Academic Integrity, see Important Guidelines & Support.

Requests for extensions

If you are unable to submit an assessment task by the due date, you should apply for an extension.

A request for an extension should first be discussed with your Unit Coordinator or teaching support team where possible. A request for an extension must be submitted by the assessment due date, except where you can provide evidence it was not possible to do so. Typically, an application for an extension will be supported by documentary evidence: however, where it is not possible for you to provide evidence please contact your Unit Coordinator.

The Unit Coordinator must notify you of the outcome of an extension request within 3 working days of receiving the request.

Late penalties

Assignments submitted after the deadline will receive a late penalty of 5% of the original available mark for each calendar day (or part day) that the assignment is late. Late submissions will not be accepted more than 10 calendar days after the due date, or after assignments have been returned to other students on a scheduled date, whichever occurs first. Further information on Late Penalties can be found on the Assessments and Results Procedure.