United Energy using big data to identify EV charging behaviour in Melbourne's south-east

Victorian electricity distributor United Energy will work to trial new techniques to better identify electric vehicle charging patterns on its network, following a first-of-its kind competition between students at Deakin University.

United Energy, the Centre for New Energy Technologies (C4NET) and Deakin University collaborated as part of the project, with C4NET acting as the data host and facilitated the distribution of data. Ten student teams at Deakin spent two months developing models using de-identified real-world data from smart meters across the United Energy network area, in Melbourne’s south-east.

Accurately detecting EV charging behaviours on its network will allow United Energy to better upgrade its infrastructure and improve planning for the expected mass take-up of electric vehicles in coming years.

Two thousand de-identified and anonymised voltage, current and power factor load profiles were supplied to the teams, including 35 hidden electricity use patterns, known to be the result of electric vehicle charging.

Teams were asked to look at the anonymised data to determine how an automated system could detect, with high probability, data profiles consistent with those of EV owners.

The winning team developed a model that was able to accurately identify most of the EV load profiles hidden within the data, with the team’s algorithm only throwing up a handful of false positives.

United Energy and the Centre for New Energy Technologies (C4NET) helped fund the Deakin University project, with prize money of $20,000 split between the top five teams and $9000 allocated to the winners.

United Energy’s Head of Network Intelligence Tobie de Villiers said the top teams delivered very impressive results, with elements of each likely to be used in some way across United Energy’s network of 702,000 customers across Melbourne’s south-east and the Mornington Peninsula – and potentially other networks in the future.

“While EV take-up is still low within our network area, we think it’s very important to plan as best we can now to ensure we’re ready when more people decide to purchase an EV as their next car,” Mr de Villers said.

“We have been impressed by how these talented students have researched and tested potential solutions that will provide us the insight we need to accommodate more electric vehicles on our network,” Mr de Villers said.

“Knowing how customers charge their electric vehicles gives us the data we need to understand what investments we need to make in our network to support our customers. It was good to see this level of industry collaboration and how we can utilise the education sector to use real data to resolve industry problems.”

Tobie de Villiers with winning team
United Energy's Head of Network Intelligence, Tobie de Villiers, with the winning student team. PIC: Simon Fox

C4NET CEO James Seymour said the competition highlights key areas which are right at the heart of C4NET’s purpose.

“There’s a lot of data available so we need to apply smart analysis to turn this into the information that will move us efficiently through the energy transition. To do so, we need new skillsets to develop innovative solutions. These challenges are sector-wide and benefit from collaborative approaches between universities, industry and government,” Mr Seymour said.

“Initiatives like this create a unique opportunity to bring new ideas to the sector and it’s exciting to see the calibre of work delivered by the teams. Let’s hope that for some of them it will be the first step of a long career in the energy sector.”

Deakin University Business School Dean, Professor Amanda Pyman said the competition was a fantastic project, at the intersection of business, technology and sustainability and a major focus for us at Deakin Business School.

“That’s why we’re excited to be invited to work with partners like United Energy and C4NET who have presented our students and researchers with an authentic data science challenge like this one.”

“We’re incredibly proud of the work our students and their academic mentors have put into this competition and of the success of their data models. It is especially gratifying that the work of our students and academics can contribute smart solutions to deliver better outcomes for consumers, our partners and the environment.”

Winners were announced at a ceremony at Deakin University’s Burwood campus on 9 May.

Mr de Villers said the EV detection project was another way United Energy was embracing its role as a Distribution System Operator (DSO), enabling all forms of distributed energy resources (DER) while maintaining safe, reliable, and affordable electricity supplies.

“We’re working to build a crucial gateway to a clean energy future by providing seamless access to our networks and new value for all customers.”

END

The winnings Deakin University teams were:



First place team

Second place team

Third place team

Equal fourth place team

Equal fourth place team

Student members

Mr. Yotam Barazani

Mr Thuc Nguyen

Ms. Thi Hoa (Hannah) Nguyen

Mr Yang Cao

Ms Lusi Xiao

Mr. Benjamin Archbold

Mr Bao Duong

Mr. Islam Khalil

Mr Rongxin Xu

Ms Brigitta Febriani

Dr. Fatemeh Ansarizadeh

Mr. Nabeel Maqsood

Ms Xiaoyan Wang

Academic mentors

Dr Adnan Anwar

Associate Professor Lemai Nguyen

Dr. Prasad

Dr Quan Vu

Dr Ali Tamaddoni, Associate Professor of Marketing

Dr Valeh Moghaddam

Dr Thin Nguyen

Sankar Bhattacharya

Dr André Bonfrer, Professor of Marketing

Dr Sutharshan Rajasegarar