Amp up SA: Forecasting Electric Transport for Grid Resilience
How might we prepare our state for the growing electrification of the transport sector?
Go to Challenge | 3 teams have entered this challenge.
Team Capybara
In the current landscape with immense growth potential for Electric Vehicles (EVs), there is a growing need for more information regarding the benefits and challenges they bring. As a response, our team has developed the ElectroForesight Dashboard. Our objective is to illustrate a range of external factors influencing the future quantity of EVs.
We have employed data modelling to predict the impact of GDP growth on the increase in electric car sales. Furthermore, we have explored how the rising number of electric vehicles might affect the power grid's load. Employing two models based on AEMO's data, we've identified that 10 am and 7 pm are peak electricity usage hours due to behavioural patterns. We have devised separate models for Day and Night scenarios to depict the projected impact of growing EV electricity demand on the grid's power consumption. Based on our assumptions, assuming EV charging habits remain consistent with the current nighttime charging behaviour in the models, the demand could surpass the current grid capability earlier than during daytime charging.
Additionally, we have pondered the relationship between EV development and energy storage, yielding valuable insights into sustainable energy supply considerations.
Participating in the GovHack competition, our team embarked on an exciting journey to address South Australia Power Networks' challenges. Our goal was to employ data and technology creatively to tackle questions surrounding transport electrification's impact on energy demand. Here's how we, as GovHack participants, confronted these challenges head-on.
Our mission was clear: predict electric vehicle growth and its energy demand impact in South Australia. We delved into data to uncover insights shaping energy consumption's future.
Equipping ourselves for this data-driven mission, we amassed diverse sources: GDP growth, electric vehicle sales, population projections, and energy graphs from opennem.org.au. These data points held South Australia's energy landscape insights.
Connecting with the client, South Australia Power Networks, via design thinking was next. We grasped their struggles with energy spikes, wastage, and seasonal energy imports.
Through conversations, we pinpointed issues with precision. A predictive system was needed, employing machine learning to forecast peak consumption and wastage periods—a puzzle we aimed to solve.
Our understanding fueled ideation. A user-friendly website emerged as the solution, offering real-time to 2050 predictions. It covered EV growth, consumption trends, and costs.
With the vision set, we crafted a prototype using a react website template. This showcased the solution's functionality, empowering users to anticipate the energy future.
Our "ElectroForesight Dashboard" website shone as our achievement. It equipped South Australia Power Networks to navigate electrification complexities. Users grasped EV trends, consumption patterns, and energy costs.
Presenting to South Australia Power Networks was gratifying. Our "ElectroForesight Dashboard" supported their alignment with the net-zero 2050 goal, paving the way for a greener future.
In conclusion, our GovHack journey was a data-driven adventure solving intricate challenges. Our innovative website illuminated answers for South Australia Power Networks, guiding them towards an electrified, sustainable future.
Description of Use Year and GDP % per year as well as $US was collected to be compared to electric vehicle sales. All data relevant to Australia.
Description of Use use to demonstrate the population growth and to calculate the impact on the number of EV in the future.
Description of Use Used to collect the total electric vehicle sales per year from 2011 to 2022.
Go to Challenge | 3 teams have entered this challenge.