Dr Yuanyuan Fan :Engineering Institute of Technology

Coming from an electrical background, Dr. Yuanyuan Fan has always attached significance to social and environmental impacts in her everyday work and research. She believes the future lies in the efficient utilization and management of renewable energy sources, from where smart grids incorporating technologies such as green hydrogen production and usage will then become practical and cost-effective. With extensive teaching experience to engineering students and continued pursuing of applied research, Dr. Yuanyuan Fan has publications from power system analysis to machine learning based engineering practices and education. For a sustainable energy future, she believes electrical engineers should take initiatives to broaden their knowledge and in the meanwhile to collaborate with data communication engineers, automation engineers, data scientists and policy makers.

A glance at engineering skill gaps, and how to address them

1 August, 2022

Looking at the year ahead, we approached EIT lecturers, esteemed academics and industry professionals, to share their wisdom and identify potential engineering skill gaps which could be faced in 2023. We posed the following three questions to each of our experts: What are some skill gaps engineers could possibly face...Read More

Engineering Institute of Technology’s women in engineering

10 March, 2022

There’s been a continuing influx of women studying in the field of engineering and ultimately joining the workforce and contributing to academia. There have been numerous discussions about closing the gender gap and weeding out discrimination, and sure there’s been tremendous progress made, however, the pursuit is far from complete....Read More

Using Machine Learning to Predict and Avoid Malfunctions: A Revolutionary Concept for Condition-Based Asset Performance Management (APM)

24 February, 2022

In the renewable energy industry, a single component malfunction can significantly impact the entire network's performance. Asset failures in solar and wind farms can bring down a whole network of infrastructure, affecting thousands of customers and decreasing network reliability, costing hundreds of thousands of dollars. Therefore, there is a strong...Read More

Mathematical Analysis on Harmonics Mitigation Using a Phase-Shifted Transformer based Twelve-Pulse Variable Frequency Drive

16 November, 2021

Harmonics are among the serious problems that affect the power quality of an electrical system. However, harmonics nowadays are inevitable due to the ever-increasing number of Variable Frequency Drives (VFDs), Uninterruptible Power Supply (UPS) and other non-linear loads. In this regard, IEEE519 Standard specifies the allowable Total Harmonic Distortion (THD)...Read More

Modeling and Performance Assessment of an Efficient Photovoltaic based Grid-Connected Inverter System with Integration of LCL Filter

16 November, 2021

Power converters are required to modify the intermittent power from renewable sources into smooth and stable output. However, the power electronic based components which are utilized in the converters along with their pulse width modulation property can create power quality issues. Among all of them, one of the critical aspects...Read More

Implementation of Industry Inputs in Higher Education Courses

2 July, 2021

Higher education courses must be continuously updated to catch up with the ever-changing industrial advancements. An up-to-date course benefits all parties of interest including students, employers and the education institution. This paper discusses the process of identifying industry expectations from graduates and implementing industry inputs based on two engineering courses...Read More

Evaluation of Remote or Virtual Laboratories in E-Learning Engineering Courses

18 June, 2021

The learning environment has shifted from the traditional synchronous classroom-based mode to synchronous and asynchronous online mode. However, critical aspects of engineering courses where theories meet applications, such as in the form of practical or laboratory work, are challenging to be conducted effectively online. The rise of industry 4.0 has...Read More

An automated thesis supervisor allocation process using machine learning

23 January, 2021

The higher education sector has been growing at a significant rate demanding a variety of skills and knowledge from both sides: instructors and learners. Thesis supervision is one of the main challenges as this activity combines research and teaching practices. To ensure the success of a student’s thesis project, it...Read More

Fields of Research	Electrical and Electronic Engineering Power and Energy System Engineering Industrial Automation Data Science
Research Interest	Renewable energy systems Smart grids Machine Learning and AI Engineering education

Professional Memberships	Senior Member of IEEE
Industry Affiliations	Chartered Engineer accredited by Engineers Australia
Administrative Responsibilities	Course Coordinator – Electrical Engineering Courses Course Coordinator – Capstone Master Thesis Unit Coordinator – Industry Panels and Course Advisory committees (MEE and MIA); Course Benchmarking Member – Board of Studies; Teaching and Learning Committee; Research Committee

Currently Teaching courses/programs	BSC202C Engineering Mathematics 3 ME700 Master Thesis Projects
Teaching Experience	From 2016 onwards

DEng	Development of a low cost patient intelligent assistant (DALBOT) IT / OT Convergence for increasing efficiency of resourcing and reporting processes across the business
Master’s (completed):	Best approach to upgrading a distributed control system. Case study: Kiira power station Specification design of a gas plant (Assa North Gas Plant) based on instrument asset management system
Recent Publications	Hashemnia, Y. Fan and N. Rocha, ‘Using machine learning to predict and avoid malfunctions- a revolutionary concept for condition-based Asset Performance Management (APM), accepted, IEEE PES Innovative Smart Grid Technology conference, Brisbane, 2021. Sule, M. Batool and Y. Fan, ‘Modeling and performance assessment of an efficient photovoltaic based grid-connected inverter system with integration of LCL filter’, 2021 Australasian Universities Power Engineering Conference, Perth, 2021. Fan, A. Evangelista and I. V, ‘Evaluation of remote or virtual laboratories in e-Learning engineering courses’, EDUCON2021-IEEE Global Engineering Education Conference, 2021. Fan, A. Evangelista and H. Harb, ‘An automated thesis supervisor allocation process using machine learning’, Global Journal of Engineering Education, 2021.

Dr Yuanyuan Fan

Biography

Publications and News