Engineering Institute of Technology

Professional Certificate of Competency in Smart Grids

The course introduces engineers to the principles of smart grids in power system applications under various network conditions. The content includes smart electricity networks and the role of communication in smart grid deployment, which will develop engineers’ understanding of the overall smart grid components.

The course will discuss the basic components of smart grid systems and will look into topics of smart grid regulation and market economics, communication technologies and smart transmission/distribution grids. The application of various power electronic devices and the management of energy storage, electric vehicles, demand side management and AMI will also be covered. The computation tools for smart grid design, adaptive protection, Interoperability standards and software infrastructure will be highlighted. Furthermore, students will gain a fundamental understanding of big data and cyber security in smart grids.

After covering the necessary theory, the course will introduce practical studies involving the modelling and simulation of various system conditions using appropriate software tools. Students will also gain skills in interpreting simulation results.

Additional Credit

Upon successful completion of this Professional Certificate of Competency:

If you apply and are accepted into the Master of Engineering (Electrical Systems), you will obtain credit for the MEE605 Smart Grids unit.

Module 1

Introduction to Smart Grids and Their Market Economics

• Evolution of smart grids
• The need for policy and regulation in smart grids
• Main regulatory issues (utility disincentives, pricing inefficiencies, and cybersecurity and privacy) and challenges in the electricity market
• Electricity market structure
• Incentivizing market policy and ancillary services

Module 2

Infrastructure of Smart Grids

• Technical challenges of smart grids
• Composition of the smart grid (Standards adaptation, technical components, technical perspective, conceptual reference model perspective)
• Pathways for Designing Smart Grids

Module 3

Smart Transmission/Distribution Grids

• Distributed management systems
• SCADA systems and smart grid vision

Module 4

Applications of Power Electronics and Energy Storage Systems

• FACTS application in smart grids
• Distributed energy resources and their applications
• Energy storage systems
• Power system reliability with intelligent operation strategies
• Operation of large-scale battery storage in the energy market

Module 5

Demand Side Management and AMI

• Demand side management and response in a smart grid
• The role of smart metering in smart grids
• Use case: smart home and building automation

Module 6

Electric Vehicles (EVs) Integration and Its Grid Impact

• Intro to Electric Drive Vehicles and the Challenges to EV Adoption by Customers and Utility
• Smart grid technologies for EV load management
• EV flexibility in the grid integration
• Grid support from EVs (vehicle-to-grid, vehicle-to-building, vehicle-to-home etc.)

Module 7

Measurement and Communication Technologies

• Communication technologies and standards for smart grids
• Multiagent systems (implementation, specification, technique)
• Internet of Things (IoT) and its association with smart grids

Module 8

Computation Tools for Smart Grid Design and Adaptive Protection

• Computational challenges and protection systems under smart grid environment
• Architecture of smart grid protection systems
• Smart adaptive protection for microgrids and distribution networks

Module 9

Interoperability Standards and Software Infrastructure

• Type and characteristics of interoperability standards for smart grid
• Standards development organizations (SDOs) and key interoperability standards
• Software Architecture in Smart Grids
• IT challenges, essential smart grid software platform

Module 10

Artificial Intelligence in Smart Grids

• Big data characteristics and application in smart grids
• Cloud computing implementation in the smart grids
• Application of machine learning algorithms for performance measurements

Module 11

Cyber Security in Smart Grids

• Information security for the smart grid
• Cyberinfrastructure and security of power systems
• Smart grid cyber-security standards and challenges
• Security schemes for AMI private networks and public networks

Module 12

Project and Revision

In the final week, total course contents will be briefly discussed. Students will have an opportunity to review the contents covered so far. Opportunities will be provided for a review of student work, to clarify any outstanding issues, and to work on finalizing the major assessment report.

You are expected to spend approximately 5-8 hours per week learning the course content. This includes attending fortnightly webinars that run for about 90 minutes to facilitate class discussion and allow you to ask questions. This program has a 65% attendance requirement in the live webinars to graduate from the program. If you are unable to attend the live webinars, you have the option of watching the recording of completed webinars and sending a summary of what you have learnt from the webinar to the Learning Support officer. The summaries go towards your attendance requirement for the program.

This program is run online on an intensive part-time basis and has been designed to fit around full-time work. It will take three months to complete.

We understand that sometimes work commitments and personal circumstances can get in the way of your studies, so if at any point you feel that you are struggling with the pace of the course or finding a particular module challenging, you are encouraged to contact your designated Learning Support Officer for assistance.