Note: This unit version is currently under review and is subject to change!

ELEC5208: Intelligent Electricity Networks (2019 - Semester 1)

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Unit: ELEC5208: Intelligent Electricity Networks (6 CP)
Mode: Normal-Evening
On Offer: Yes
Level: Postgraduate
Faculty/School: School of Electrical & Information Engineering
Unit Coordinator/s: Dr Qiu, Jing
Session options: Semester 1
Versions for this Unit:
Site(s) for this Unit:
Campus: Camperdown/Darlington
Pre-Requisites: None.
Brief Handbook Description: This unit aims to give students an introduction to the planning and operation of modern electricity grids, also known as "smart" grids. Traditional power networks featured a small number of large base-load plants sending power out over transmission lines to be distributed in radial lower voltage networks to loads. In response to the need to reduce carbon impact, future networks will feature diverse generation scattered all over the network including at distribution levels. Also there will be new loads such as electric vehicles and technologies including energy storage and lower voltage power flow control devices. The operation of these new networks will be possible by much greater use of information and communication technology (ICT) and control over the information networks.

The unit will cover recent relevant developments in energy technologies as well as important components of 'smart grids' such as supervisory control and data acquisition (SCADA), substation automation, remote terminal units (RTU), sensors and intelligent electronic devices (IED). Operation of these electricity grids requires a huge amount of data gathering, communication and information processing. The unit will discuss many emerging technologies for such data, information, knowledge and decision processes including communication protocols and network layouts, networking middleware and coordinated control. Information systems and data gathering will be used to assess key performance and security indicators associated with the operation of such grids including stability, reliability and power quality.
Assumed Knowledge: Electricity Networks, Control Systems and Telecommunications
Lecturer/s: Dr Qiu, Jing
Timetable: ELEC5208 Timetable
Time Commitment:
# Activity Name Hours per Week Sessions per Week Weeks per Semester
1 Lecture 2.00 1 13
2 Tutorial 2.00 1 6
3 Laboratory 2.00 1 6
4 Project Work - own time 2.00 1 5
5 Independent Study 3.00 13
T&L Activities: Tutorial: Work through exercises related to lecture material.

Laboratory: At least two laboratory exercises to help problem solving and familiarity with typical equipment.

Project: Small group work on a selected project.

Learning outcomes are the key abilities and knowledge that will be assessed in this unit. They are listed according to the course goal supported by each. See Assessment Tab for details how each outcome is assessed.

(1) Maths/ Science Methods and Tools (Level 3)
1. Understand the mathmatical models of the power and information networks as part of a cyber-physical system in a ‘smart grid’.
(2) Engineering/ IT Specialisation (Level 4)
2. Explain and evaluate the system capability, stability, reliability from a smart grid perspective.
3. Model and analyse broadly and design substantial parts of state-of-the-art smart-grid systems while appreciating the issues for further developments.
(3) Problem Solving and Inventiveness (Level 4)
4. Design and simulate decision and control systems for smart grid applications including volt-VAR control, FDIR, WAMS.
(4) Design (Level 5)
5. Demonstrate an understanding of concepts, selected analysis and design techniques in modern power systems, i.e. the interaction of large-scale generation, transmission and distribution including distributed generation, micro-grids and virtual power plants.
(5) Interdisciplinary, Inclusiveness, Influence (Level 2)
6. Undertake knowledge building by drawing on many and varied information sources specific to the power systems industry for new designs and solutions to problems.
(6) Communication and Inquiry/ Research (Level 4)
7. Communicate specific design project material through proper engineering presentations and reports.
(7) Project and Team Skills (Level 4)
8. Make a substantial contribution to a team project where members have some overlapping and complementary skills.
Assessment Methods:
# Name Group Weight Due Week Outcomes
1 Lab Report 1 Yes 5.00 Week 8 1, 2, 4, 5,
2 Lab Report 2 Yes 5.00 Week 13 1, 2, 4, 5,
3 Project Report Yes 20.00 Week 11 1, 2, 3, 4, 5, 6, 7, 8,
4 Mid-Sem Exam No 20.00 Week 7 1, 5, 6,
5 Final Exam No 50.00 Exam Period 1, 5, 6,
Assessment Description: Lab Report: 2 laboratory experiments written up in formal report style individually

Project Report: Team report written up in formal report style which contributions self-assessed

Mid-sem Exam: Closed book quiz style to test understanding of concepts

No hand-in assignments; students are expected to work on assembling their own solutions to exercises given in lectures and tutorials.

The final exam will be a variation of exercises dealt with in tutorials.
Grading:
Grade Type Description
Standards Based Assessment Final grades in this unit are awarded at levels of HD for High Distinction, DI (previously D) for Distinction, CR for Credit, PS (previously P) for Pass and FA (previously F) for Fail as defined by University of Sydney Assessment Policy. Details of the Assessment Policy are available on the Policies website at http://sydney.edu.au/policies . Standards for grades in individual assessment tasks and the summative method for obtaining a final mark in the unit will be set out in a marking guide supplied by the unit coordinator.
Policies & Procedures: See the policies page of the faculty website at http://sydney.edu.au/engineering/student-policies/ for information regarding university policies and local provisions and procedures within the Faculty of Engineering and Information Technologies.
Online Course Content: Will be provided

Note that the "Weeks" referred to in this Schedule are those of the official university semester calendar https://web.timetable.usyd.edu.au/calendar.jsp

Week Description
Week 1 Introduction to the Conventional Power Distribution Systems
Week 2 Power System Basics (Power flow problems, power system stability, major blackout, load modeling, generator modelling, and exciter modelling)
Week 3 Emerging Technologies and Renewable energy (wind and solar power, biomass, impacts, benefits and solutions)
Week 4 Battery Energy Storage System and Electric Vehicle
Week 5 Demand Response (Demand management, load following, load shaping, smart home management, virtual power plant)
Week 6 Control in Smart Grid (Control principles, classical and modern control theories, centralised and distributed control, frequency and voltage control )
Week 7 SCADA, EMS/DMS, and Smart Grids (Parallel computing, grid computing, cloud computing, big data analysis)
Assessment Due: Mid-Sem Exam
Week 8 Communication in Smart Grid (Smart meters, home area network, access network, backbone/core network, and data/control center)
Assessment Due: Lab Report 1
Week 9 Computing in Smart Grid (Intelligent optimisation algorithms, parallel computing, grid computing, cloud computing, big data analysis)
Week 10 Micro-Grid (Planning and operation of micro-grid)
Week 11 New Market Business Model (Trans-active energy, 'prosumer', distribution markets)
Assessment Due: Project Report
Week 12 Project Discussion and Feedback
Week 13 Guest Lecture or Project Discussion and Feedback
Assessment Due: Lab Report 2
Exam Period Assessment Due: Final Exam

Course Relations

The following is a list of courses which have added this Unit to their structure.

Course Year(s) Offered
Electrical (till 2014) 2012, 2013, 2014
Electrical (Bioelectronics) (till 2012) 2012
Electrical Engineering (Bioelectronics) / Law 2012
Electrical (Computer) (till 2014) 2012, 2013, 2014
Electrical Engineering (Computer) / Law 2012, 2013, 2014
Electrical (Power) (till 2014) 2012, 2013, 2014
Electrical (Telecommunications) (till 2014) 2012, 2013, 2014
Electrical Mid-Year 2016, 2017, 2018, 2019, 2020
Electrical/ Project Management 2019, 2020
Electrical 2015, 2016, 2017, 2018, 2019, 2020
Electrical / Arts 2016, 2017, 2018, 2019, 2020
Electrical / Commerce 2016, 2017, 2018, 2019, 2020
Electrical / Medical Science 2016, 2017
Electrical / Music Studies 2016, 2017
Electrical / Project Management 2016, 2017, 2018, 2020
Electrical / Science 2016, 2017, 2018, 2019, 2020
Electrical/Science (Health) 2018, 2019, 2020
Electrical (Computer) 2015
Electrical / Law 2016, 2017, 2018, 2019, 2020
Electrical (Power) 2015
Electrical (Telecommunications) 2015
Software Mid-Year 2016, 2017, 2018, 2019, 2020
Software/ Project Management 2019, 2020
Software 2015, 2016, 2017, 2018, 2019, 2020
Software / Arts 2016, 2017, 2018, 2019, 2020
Software / Commerce 2016, 2017, 2018, 2019, 2020
Software / Medical Science 2016, 2017
Software / Music Studies 2016, 2017
Software / Project Management 2016, 2017, 2018
Software / Science 2016, 2017, 2018, 2019, 2020
Software/Science (Health) 2018, 2019, 2020
Software / Law 2016, 2017, 2018, 2019, 2020
Software Engineering (till 2014) 2012, 2013, 2014
Electrical/Science (Medical Science Stream) 2018, 2019, 2020
Graduate Diploma in Complex Systems 2017, 2018, 2019, 2020
Master of Complex Systems 2017, 2018, 2019, 2020
Master of Engineering 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020
Master of Engineering (Electrical) 2012
Master of Engineering (Network) 2012
Master of Engineering (Power) 2012
Master of Engineering (Wireless) 2012
Master of Professional Engineering (Accelerated) (Electrical) 2019, 2020
Master of Professional Engineering (Accelerated) (Power) 2019, 2020
Master of Professional Engineering (Electrical) 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020
Master of Professional Engineering (Power) 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020
Software/Science (Medical Science Stream) 2018, 2019, 2020

Course Goals

This unit contributes to the achievement of the following course goals:

Attribute Practiced Assessed
(1) Maths/ Science Methods and Tools (Level 3) No 24%
(2) Engineering/ IT Specialisation (Level 4) No 7%
(3) Problem Solving and Inventiveness (Level 4) No 6%
(4) Design (Level 5) No 42%
(5) Interdisciplinary, Inclusiveness, Influence (Level 2) No 16%
(6) Communication and Inquiry/ Research (Level 4) No 3%
(7) Project and Team Skills (Level 4) No 2%
(8) Professional Effectiveness and Ethical Conduct (Level 3) No 0%

These goals are selected from Engineering & IT Graduate Outcomes Table 2018 which defines overall goals for courses where this unit is primarily offered. See Engineering & IT Graduate Outcomes Table 2018 for details of the attributes and levels to be developed in the course as a whole. Percentage figures alongside each course goal provide a rough indication of their relative weighting in assessment for this unit. Note that not all goals are necessarily part of assessment. Some may be more about practice activity. See Learning outcomes for details of what is assessed in relation to each goal and Assessment for details of how the outcome is assessed. See Attributes for details of practice provided for each goal.