Western Power has improved its forecasting methodology to better reflect changing environmental conditions and community energy use to better plan and manage the network now and in the future.
With the increase in rooftop solar, and data from growing network smarts like Advanced Metering Infrastructure (AMI), Western Power now has greater insight and understanding of future demand on key assets such as distribution transformers and distribution feeders.
Feeders are the conductors (underground cables or poles and wires) which connect from a zone substation to distribution transformers. Distribution transformers convert the medium voltage used in feeders to low voltage that’s suitable for residential use.
Both are a vital part of the electricity grid, but can come under pressure during periods of high demand or extreme weather events.
Head of Grid Transformation Ben Bristow said the methodology to predict distribution transformer load has been reviewed to take into account the changes in grid demand via customer behaviour and use patterns, including the uptake of solar PV systems.
“Using technology such as AMI, Western Power can now better understand energy consumption,” he said.
“While no network can guarantee 100 per cent reliability and outages do happen as part of normal network operations, through these updated processes we’re working to reduce the risk of people experiencing outages and minimising the duration should they occur.
“Western Power has been rolling out AMI since 2019 and now that more than 500,000 are active across the network we’ve a very good snapshot of network demand at low voltage levels where there was previously very little visibility.
“Using this new information, and other data we can estimate the loading on transformers in the distribution network. We’ve incorporated this intelligence into our systems and the results have been cross-referenced against areas with high levels of AMI visibility so we can use an improved loading estimate in our planning processes.
“This includes how we prioritise transformers for replacement and identify those that may be at risk of overloading due to high demand.