Photo by Fré Sonneveld on Unsplash
Solar Analytics is leading a project funded by ARENA to provide data about how solar systems respond to voltage disturbances on the grid, with the aim to improve the Australian Energy Market Operator’s modelling, and therefore increase the amount of PV rooftop solar that Australia’s power system can handle.
The Australian Energy Market Operator (AEMO) released their December report on a major grid disturbance, highlighting a recommendation to source better data and analysis of rooftop PV performance.
Now Solar Analytics is helping to do just that.
With Australia’s largest and highest quality resource of distributed energy data, Solar Analytics has teamed up with AEMO and local IOT company Watt Watchers in an ARENA funded project announced by Minister Angus Taylor on Monday.
The project aims to provide detailed analysis of existing and new datasets to understand the response of rooftop PV during grid disturbance events. This will allow AEMO to continue to improve its simulation models and make informed recommendations on inverter standards so that responses to events like this have the best chance of re-stabilising the system and avoiding widespread blackouts. The project also aims to improve monitoring hardware and to help detect grid disturbances and capture additional high-quality data on the electricity grid when it is needed most.
As a user-focused BCorporation, Solar Analytics will always put customer privacy first, with resources allocated to continuing and improving our data security measures so that we can increase data utility without revealing any personal information.
It’s another way Solar Analytics is helping people to navigate the changing energy landscape, whether you’re managing your energy bills, or managing one of the most challenging electricity markets in the world!
Read more about the ARENA project here.
Dr Jonathon Dore swapped International-level trampolining for data science. Lucky for us! Jono is now our Head of Data Strategy and is responsible for the sophisticated algorithms that we use to make our monitoring system the most intelligent available.
