Imagine a web platform which allowed you pull apart and analyse national power usage like a giant Lego set. Sound hard? It’s this guy’s job to build it. Adam Berry is the Energy Research Group Leader of the CSIRO Grids and Energy Efficiency Systems Program.
Dr Berry leads a group of computer scientists, engineers and economists focused on the efficient integration, operation and planning of Australia’s energy systems, from small-scale air-conditioning to the national networks.
In a few words, what is the energy use data model?
CSIRO’s Energy Use Data Model (EUDM) will be a central web platform to capture Australia’s energy use, including half-hourly energy consumption, demographics, building characteristics, appliance uptake, weather and more. It will provide a way to connect all those pieces of data together to detail what influences, drives and predicts Australia’s energy behaviour.
Why has this vital piece of the energy puzzle been missing for so long?
At the moment, energy data is held by numerous parties, formatted to different standards and access is often poor or restricted. EUDM won’t just collect and publish existing data – it will deliver new datasets as well.
Who will get the most out of it?
EUDM is ultimately a one-stop shop for critical energy-use data. It will help government, industry, energy researchers, policy makers, regulators, market operators and consumers explore how we are using energy in Australia, from individual energy users to large-scale populations. The majority of data will be accessible to anyone – from energy consumers looking to understand how they use energy, to innovators looking to understand how the next amazing energy product could deliver value. However, the main audience is energy researchers.
Will it favour renewables or treat all sources equally?
The focus of EUDM is on end-use. However, with a core component of contemporary Australian end-use being local generation, we will cover how that influences the behaviour of households and businesses. There is plenty of solar data available but not enough of it helps us understand how gross solar output changes over time in the real-world, what factors best predict uptake and how our energy consumption behaviour transforms after solar is installed; for example, does energy consumption increase once a solar panel is installed?
Why are demographics important in understanding energy use?
We know surprisingly little about the energy consumption of Australian households. By linking household characteristics such as demographics, building type and appliance usage, we can help to forecast future energy use, understand how electricity prices affect consumers and see where energy products and services can deliver the most value.
Will a data model encourage energy efficiency or optimal supply of energy, or a little of both?
Accurate energy data will help us better understand Australian energy consumers and consumption. If we know our consumers, we are more likely to get every part of the energy system right – from energy efficiency through to optimal supply.
Including energy from renewables in forecasting supply will involve forecasting the weather, but how good are we at doing that?
EUDM will provide data that will improve energy forecasting by better explaining the links between energy consumer behaviour and weather. Importantly, if we link real observed solar PV output with accurate weather data, we can better understand how distributed small-scale renewables operate in the real-world and therefore forecast their impact and performance.
Who will be able to use the platform?
The EUDM platform will be a website available to anyone, but it is ultimately designed for energy researchers with a strong technical base. If you love energy data, you will love the EUDM – it is a platform built for data geeks like me!
What are some gaps you anticipate seeing when all the data is in one place?
Early on, the key gaps will likely be gross solar PV data (we will have plenty of net solar data, but gross is more difficult to acquire) and data for those living off the grid or in remote micro-grid environments. We are always looking for more data – so if EcoGeneration readers have a great source, I really do encourage them to reach out to us!
How did you end up in the job?
My whole career has been about data. My background is in computer science and artificial intelligence, which is really about how we use data to make the right choices. At CSIRO, we have always been passionate about getting the evidence right so we are a great fit for this sort of work.