Households and businesses are changing their energy consumption behaviour
Households and businesses are driving a transformation in the energy system through the adoption of new efficient and smart appliances, building performance improvements, electric vehicles (EVs), solar photovoltaic (PV) and battery storage.
At the same time, Australia is replacing large synchronous coal and gas-fired generators with renewable inverter-based resources (IBR) and distributed energy resources (DER).
Our ability to maintain affordable and reliable energy services through this transformation will require forecasting and planning. We'll need good data and analysis to model our changing energy system, and:
- develop energy policy founded on a sound evidence base
- forecast infrastructure requirements in a changing world
- design effective business models that deliver value to Australian households and businesses.
Identifying and filling gaps in energy data and analysis
The National Energy Analytics Research (NEAR) program is a joint initiative of CSIRO, the Australian Energy Market Operator (AEMO) and the Australian Government, to enhance the analytical capability and data availability of the Australian energy sector.
We work with stakeholders across the Australian energy sector to identify gaps in analytical capability and data availability, and undertake innovative research and development projects to fill them.
Better evidence to support policy and planning
Through engagement with energy researchers, policy makers, regulators, market operators and consumers, and solid analytics research, the NEAR program has so far:
- improved the secure sharing of energy data among energy policymakers and planners, while protecting customer privacy and confidentiality, with data access agreements, data access platforms and data de-identification algorithms
- extracted new insights from meter data to support improved energy policy and planning, including using disaggregation methods for characterising the end-use composition of demand, and clustering methods to better target policies and programs
- analysed changes in building stock, its distribution and composition, and the subsequent impact on energy demand through remote sensor data processing
- generated a rich picture of changes in technology and consumer behaviour and their impact on energy use through consumer energy surveys
- developed improved energy forecasting methods for enhancing energy system operations, capacity planning and policymaking.