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Course Outline

ELC701 Electrical Demand Forecasting and Management

Course Coordinator:Adrian McCallum (amccallu@usc.edu.au) School:School of Science, Technology and Engineering

2026Trimester 2

UniSC Moreton Bay

 Blended learning You can do this course without coming onto campus, unless your program has specified a mandatory onsite requirement.

Online

 Online You can do this course without coming onto campus.

Please go to usc.edu.au for up to date information on the
teaching sessions and campuses where this course is usually offered.

What is this course about?

Description

This course will provide you with in-depth knowledge and understanding of electrical demand forecasting and management. You will also apply demand flexibility and forecasting models.

How will this course be delivered?

Activity Hours Beginning Week Frequency
Blended learning
Learning materials – Asynchronous weekly learning material 1hr Week 1 12 times
Seminar – On campus 1hr Week 1 3 times
Tutorial/Workshop 1 – On campus 2hrs Week 1 10 times
Online
Learning materials – Asynchronous weekly learning material 1hr Week 1 12 times
Seminar – Online 1hr Week 1 3 times
Tutorial/Workshop 1 – Online 2hrs Week 1 10 times

Course Topics

Topics may include:

  • Overview of demand flexibility
  • Static and dynamic state estimation
  • short- and long-term forecasting models
  • Machine learning and AI in generating forecasting models
  • Prediction tools for aggregated response
  • Options for automated response, market based vs sign-up contract
  • Exposure of customer willingness, utility command and decay of manual response

What level is this course?

700 Level (Specialised)

Demonstrating a specialised body of knowledge and set of skills for professional practice or further learning. Advanced application of knowledge and skills in unfamiliar contexts.

What is the unit value of this course?

12 units

How does this course contribute to my learning?

Course Learning Outcomes On successful completion of this course, you should be able to... Graduate Qualities Mapping Completing these tasks successfully will contribute to you becoming... Professional Standard Mapping * Engineers Australia Stage 1 Professional Engineer Competency Standards
1 Synthesize short- and long-term load forecasting models for both static and dynamic states with given specifications and performance parameters. Creative and critical thinker 
2, 2.1.a, 2.1, 3, 3.1.c, 3.2.b, 3.4.a, 3.5.a, 3.2, 3.4, 3.5
2 Investigate and appraise innovative forecasting models using different AI and machine learning methodologies. Creative and critical thinker 
2, 2.1.d, 2.1, 3, 3.1.a, 3.1.c, 3.3.c, 3.4.b, 3.4.c, 3.5.a, 3.1, 3.3, 3.4, 3.5
3 Apply industry-standard software analysis tools to simulate and study electrical demand fluctuations and load forecasting Empowered 
2, 2.2.d, 2.2
4 Investigate the behavioural changes to load and demand in devising predictive and management models. Empowered 
2, 2.2.b, 2.2, 3, 3.1.a, 3.2.a, 3.4.b, 3.1, 3.2, 3.4
5 Demonstrate specialist knowledge and discern the key components in static and dynamic forecasting models and appraise the difference between them. Knowledgeable 
1, 1.3.a, 1.3, 3, 3.1.c, 3.1
6 Differentiate between various state estimation techniques for demand forecasting using advanced specialist knowledge. Knowledgeable 
1, 1.3.a, 1.3, 3, 3.1.c, 3.1

* Competencies by Professional Body

CODE COMPETENCY
Engineers Australia Stage 1 Professional Engineer Competency Standards
1 Elements of competency: Knowledge and Skill Base
1.3.a Knowledge and Skill Base - In-depth understanding of specialist bodies of knowledge within the engineering discipline: Proficiently applies advanced technical knowledge and skills in at least one specialist practice domain of the engineering discipline.
1.3 Knowledge and Skill Base: In-depth understanding of specialist bodies of knowledge within the engineering discipline.
2 Elements of competency: Engineering Application Ability
2.1.a Engineering Application Ability - Application of established engineering methods to complex engineering problem solving: Identifies, discerns and characterises salient issues, determines and analyses causes and effects, justifies and applies appropriate simplifying assumptions, predicts performance and behaviour, synthesises solution strategies and develops substantiated conclusions.
2.1.d Engineering Application Ability - Application of established engineering methods to complex engineering problem solving: Investigates complex problems using research-based knowledge and research methods.
2.2.d Engineering Application Ability - Fluent application of engineering techniques, tools and resources: Applies a wide range of engineering tools for analysis, simulation, visualisation, synthesis and design, including assessing the accuracy and limitations of such tools, and validation of their results.
2.2.b Engineering Application Ability - Fluent application of engineering techniques, tools and resources: Constructs or selects and applies from a qualitative description of a phenomenon, process, system, component or device a mathematical, physical or computational model based on fundamental scientific principles and justifiable simplifying assumptions.
2.1 Engineering Application Ability: Application of established engineering methods to complex engineering problem solving.
2.2 Engineering Application Ability: Fluent application of engineering techniques, tools and resources.
3 Elements of competency: Professional and Personal Attributes
3.1.c Professional and Personal Attributes - Ethical conduct and professional accountability: Understands the accountabilities of the professional engineer and the broader engineering team for the safety of other people and for protection of the environment.
3.2.b Professional and Personal Attributes - Effective oral and written communication in professional and lay domains: Prepares high quality engineering documents such as progress and project reports, reports of investigations and feasibility studies, proposals, specifications, design records, drawings, technical descriptions and presentations pertinent to the engineering discipline.
3.4.a Professional and Personal Attributes - Professional use and management of information: Is proficient in locating and utilising information - including accessing, systematically searching, analysing, evaluating and referencing relevant published works and data; is proficient in the use of indexes, bibliographic databases and other search facilities.
3.5.a Professional and Personal Attributes - Orderly management of self, and professional conduct: Demonstrates commitment to critical self-review and performance evaluation against appropriate criteria as a primary means of tracking personal development needs and achievements
3.1.a Professional and Personal Attributes - Ethical conduct and professional accountability: Demonstrates commitment to uphold the Engineers Australia - Code of Ethics, and established norms of professional conduct pertinent to the engineering discipline.
3.3.c Professional and Personal Attributes - Creative, innovative and pro-active demeanour: Is aware of broader fields of science, engineering, technology and commerce from which new ideas and interfaces may be drawn and readily engages with professionals from these fields to exchange ideas.
3.4.b Professional and Personal Attributes - Professional use and management of information: Critically assesses the accuracy, reliability and authenticity of information.
3.4.c Professional and Personal Attributes - Professional use and management of information: Is aware of common document identification, tracking and control procedures.
3.2.a Professional and Personal Attributes - Effective oral and written communication in professional and lay domains: Is proficient in listening, speaking, reading and writing English.
3.1 Professional and Personal Attributes: Ethical conduct and professional accountability.
3.2 Professional and Personal Attributes: Effective oral and written communication in professional and lay domains.
3.3 Professional and Personal Attributes: Creative, innovative and pro-active demeanour.
3.4 Professional and Personal Attributes: Professional use and management of information.
3.5 Professional and Personal Attributes: Orderly management of self, and professional conduct.

Am I eligible to enrol in this course?

Refer to the UniSC Glossary of terms for definitions of “pre-requisites, co-requisites and anti-requisites”.

Pre-requisites

Enrolled in GC005, GD005 or MC005.

Co-requisites

Not applicable

Anti-requisites

Not applicable

Specific assumed prior knowledge and skills (where applicable)

Not applicable

How am I going to be assessed?

Grading Scale

Standard Grading (GRD)

High Distinction (HD), Distinction (DN), Credit (CR), Pass (PS), Fail (FL).

Details of early feedback on progress

Early feedback will be provided through completion of weekly activities in workshops.  Furthermore, feedback on each assessment will be provided which will be used to help with the following assessment.

Assessment tasks

Delivery mode Task No. Assessment Product Individual or Group Weighting % What is the duration / length? When should I submit? Where should I submit it?
All 1 Quiz/zes Individual 30% 
6 quizzes
 Throughout teaching period (refer to Format) Online Assignment Submission with plagiarism check
All 2 Written Piece Individual 40% 
2000 words
 Week 7 Online Assignment Submission with plagiarism check
All 3 Oral Individual 30% 
15 minutes
 Week 12 Online Assignment Submission with plagiarism check
All - Assessment Task 1:Quizzes
Goal: 
Student will apply knowledge through practical tasks and problem solving, early in the course.
Product: Quiz/zes
Format: 
Student will apply knowledge through practical tasks and problem solving, early in the course. Weeks 2, 4, 6, 8, 10, 12.
Criteria:
No. Learning Outcome assessed
1 
Synthesis of short- and long-term load forecasting models for both static and dynamic states with given specifications and performance parameters.
 1
2 
Application of industry-standard software analysis tools to simulate and study electrical demand fluctuations and load forecasting
 3
3 
Demonstration of specialist knowledge and discernment of the key components in static and dynamic forecasting models and appraise the difference between them.
 5
4 
Differentiation between various state estimation techniques for demand forecasting using advanced specialist knowledge.
 6
Generic Skills: 
Problem solving, Applying technologies, Information literacy
All - Assessment Task 2:Written Piece
Goal: 
Simulation, assessment and evaluation electrical demand fluctuations using industry-standard software analysis tools and reporting the results.
Product: Written Piece
Format: 
Simulation, assessment and evaluation electrical demand fluctuations using industry-standard software analysis tools and reporting the results.
Criteria:
No. Learning Outcome assessed
1 
Synthesis of short- and long-term load forecasting models for both static and dynamic states with given specifications and performance parameters.
 1
2 
Application of industry-standard software analysis tools to simulate and study electrical demand fluctuations and load forecasting
 3
3 
Investigation of the behavioural changes to load and demand in devising predictive and management models.
 4
4 
Demonstration of specialist knowledge and discernment of the key components in static and dynamic forecasting models and appraise the difference between them.
 5
5 
Differentiation between various state estimation techniques for demand forecasting using advanced specialist knowledge.
 6
Generic Skills: 
Communication, Problem solving, Organisation, Applying technologies
All - Assessment Task 3:Oral
Goal: 
Application of predictive and management models to a real world example and presentation of the results.
Product: Oral
Format: 
Application of predictive and management models to a real world example and presentation of the results.
Criteria:
No. Learning Outcome assessed
1 
Synthesis of short- and long-term load forecasting models for both static and dynamic states with given specifications and performance parameters.
 1
2 
Investigation and appraisal of innovative forecasting models using different AI and machine learning methodologies.
 2
3 
Application of industry-standard software analysis tools to simulate and study electrical demand fluctuations and load forecasting
 3
4 
Investigation of the behavioural changes to load and demand in devising predictive and management models.
 4
5 
Demonstration of specialist knowledge and discernment of the key components in static and dynamic forecasting models and appraise the difference between them.
 5
6 
Differentiation between various state estimation techniques for demand forecasting using advanced specialist knowledge.
 6
Generic Skills: 
Communication, Problem solving, Organisation, Applying technologies, Information literacy

Directed study hours

A 12-unit course will have total of 150 learning hours which will include directed study hours (including online if required), self-directed learning and completion of assessable tasks. Student workload is calculated at 12.5 learning hours per one unit.

What resources do I need to undertake this course?

Please note: Course information, including specific information of recommended readings, learning activities, resources, weekly readings, etc. are available on the course Canvas site– Please log in as soon as possible.

Prescribed text(s) or course reader

There are no required/recommended resources for this course.

Specific requirements

Not applicable

How are risks managed in this course?

Health and safety risks for this course have been assessed as low. It is your responsibility to review course material, search online, discuss with lecturers and peers and understand the health and safety risks associated with your specific course of study and to familiarise yourself with the University’s general health and safety principles by reviewing the online induction training for students, and following the instructions of the University staff.

What administrative information is relevant to this course?

Assessment: Academic Integrity

Academic integrity is the ethical standard of university participation.  It ensures that students graduate as a result of proving they are competent in their discipline.  This is integral in maintaining the value of academic qualifications. Each industry has expectations and standards of the skills and knowledge within that discipline and these are reflected in assessment.

Academic integrity means that you do not engage in any activity that is considered to be academic fraud; including plagiarism, collusion or outsourcing any part of any assessment item to any other person.  You are expected to be honest and ethical by completing all work yourself and indicating in your work which ideas and information were developed by you and which were taken from others. You cannot provide your assessment work to others. You are also expected to provide evidence of wide and critical reading, usually by using appropriate academic references.

In order to minimise incidents of academic fraud, this course may require that some of its assessment tasks, when submitted to Canvas, are electronically checked through Turnitin.  This software allows for text comparisons to be made between your submitted assessment item and all other work to which Turnitin has access.

Assessment: Additional Requirements

Eligibility for Supplementary Assessment

Your eligibility for supplementary assessment in a course is dependent of the following conditions applying:
(a) The final mark is in the percentage range 47% to 49.4%; and
(b) The course is graded using the Standard Grading scale

Assessment: Submission penalties

Late submissions may be penalised up to and including the following maximum percentage of the assessment task’s identified value, with weekdays and weekends included in the calculation of days late:
(a) One day: deduct 5%;
(b) Two days: deduct 10%;
(c) Three days: deduct 20%;
(d) Four days: deduct 40%;
(e) Five days: deduct 60%;
(f) Six days: deduct 80%;
(g) Seven days: A result of zero is awarded for the assessment task.
The following penalties will apply for a late submission for an online examination:
Less than 15 minutes: No penalty
From 15 minutes to 30 minutes: 20% penalty
More than 30 minutes: 100% penalty

SafeUniSC

UniSC is committed to a culture of respect and providing a safe and supportive environment for all members of our community. For immediate assistance on campus contact SafeUniSC by phone: 07 5430 1168 or using the SafeZone app. For general enquires contact the SafeUniSC team by phone 07 5456 3864 or email safe@usc.edu.au.

The SafeUniSC Specialist Service is a Student Wellbeing service that provides free and confidential support to students who may have experienced or observed behaviour that could cause fear, offence or trauma. To contact the service call 07 5430 1226 or email studentwellbeing@usc.edu.au.

Study help

For help with course-specific advice, for example what information to include in your assessment, you should first contact your tutor, then your course coordinator, if needed.

If you require additional assistance, the Learning Advisers are trained professionals who are ready to help you develop a wide range of academic skills. Visit the Learning Advisers web page for more information, or contact Student Central for further assistance: +61 7 5430 2890 or studentcentral@usc.edu.au.

Wellbeing Services

Student Wellbeing provide free and confidential counselling on a wide range of personal, academic, social and psychological matters, to foster positive mental health and wellbeing for your academic success.

To book a confidential appointment go to Student Hub, email studentwellbeing@usc.edu.au or call 07 5430 1226.

AccessAbility Services

Ability Advisers ensure equal access to all aspects of university life. If your studies are affected by a disability, learning disorder mental health issue, injury or illness, or you are a primary carer for someone with a disability or who is considered frail and aged, AccessAbility Services can provide access to appropriate reasonable adjustments and practical advice about the support and facilities available to you throughout the University.

To book a confidential appointment go to Student Hub, email AccessAbility@usc.edu.au or call 07 5430 2890.

Links to relevant University policy and procedures

For more information on Academic Learning & Teaching categories including:

  • Assessment: Courses and Coursework Programs
  • Review of Assessment and Final Grades
  • Supplementary Assessment
  • Central Examinations
  • Deferred Examinations
  • Student Conduct
  • Students with a Disability

For more information, visit https://www.usc.edu.au/explore/policies-and-procedures#academic-learning-and-teaching

Student Charter

UniSC is committed to excellence in teaching, research and engagement in an environment that is inclusive, inspiring, safe and respectful. The Student Charter sets out what students can expect from the University, and what in turn is expected of students, to achieve these outcomes.

General Enquiries

  • In person:
    • UniSC Sunshine Coast - Student Central, Ground Floor, Building C, 90 Sippy Downs Drive, Sippy Downs
    • UniSC Moreton Bay - Service Centre, Ground Floor, Foundation Building, Gympie Road, Petrie
    • UniSC SouthBank - Student Central, Building A4 (SW1), 52 Merivale Street, South Brisbane
    • UniSC Gympie - Student Central, 71 Cartwright Road, Gympie
    • UniSC Fraser Coast - Student Central, Student Central, Building A, 161 Old Maryborough Rd, Hervey Bay
    • UniSC Caboolture - Student Central, Level 1 Building J, Cnr Manley and Tallon Street, Caboolture
  • Tel:+61 7 5430 2890
  • Email:studentcentral@usc.edu.au
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