The power of understanding how we consume energy
Ever experienced 'bill shock' when viewing your electricity account?
Ever experienced 'bill shock' when viewing your electricity account? If so, you most likely wondered exactly which of your household appliances caused the spike in your kilowatt hours. If only you’d known...
Zahraa Abdallah, a postdoctoral research fellow in applied data science and machine learning, appreciates the great value of such information. As part of an exciting industry-based project, she uses smart meter data to reveal trends and patterns in energy consumption.
"Providing customers with timely consumption information can help them alter their behaviour to reduce their total energy consumption," she explains. "Studies suggest a 3% to 10% reduction in consumption when customers are made aware of their consumption behaviour on the appliance level."
Not only that, accurate data disaggregation can help retailers design new tariffs, such as time-of-use tariffs. As we move towards intermittent renewables, we’ll need such tariffs to, for example, encourage rooftop solar to be fed into the grid at times of peak demand. This analysis of energy data will also help distribution companies understand customer patterns and better plan network capacity.
"Disaggregation technology would enable emergency measures," adds Zahraa. "If air conditioner use had been banned when the transmission towers were blown down by the recent South Australian storm, it may have prevented the state-wide blackout. We can only enforce such a ban if we have a way to detect the use of air conditioners."
Zahraa works within the Grid Innovation Hub at Monash, a unique research, training and teaching platform for digital energy. "The Hub fosters partnerships between industry leaders and world-leading university researchers," she says. "It aims to solve challenging questions vital to the future of the electricity sector."
In the big data era, we collect from many sources a high volume of data at high speed. "New powerful techniques and methods using the Internet of Things (IoT) will make it possible to analyse energy big data at scale with real-time analytics and prediction," suggests Zahraa. "And we can expect more innovation in solar, wind, tidal, biomass and geothermal technologies, as well as smart cities and virtual power stations."
And who might fulfill these prophecies? Zahraa points to Monash Alumni: "Networking with Monash graduates can provide a unique opportunity to discuss ideas, as a talent pool, for new innovations."
Good thinking. And we couldn’t agree more!