“We can leverage the data of today to manage the grid of tomorrow.”
Astrid Atkinson, CEO and co-founder of Camus Energy, proclaims this to be true - and she would know. Astrid spent 15 years at Google where she led framework infrastructure engineering for all of Google’s products, building the company’s high-reliability computing platform. She is a leading expert on large-scale distributed systems architecture, reliability engineering, and organizational leadership. She co-founded Camus Energy to create software that enables high-performance, low-complexity management of the electric grid.
As more rooftop solar, electric vehicles, and other distributed energy resources connect to the grid, management strategies must evolve to address the staggering increase in complexity and variability. However, traditional tools are insufficient for coordinating the growing number of devices, while newer DER management systems (DERMS) target only part of the problem – lacking awareness of real-time grid conditions. In this variable landscape marred by glaring data gaps and siloed systems, distribution operators are left with limited - and often lagging - visibility.
Enter Astrid and the Camus team.
By leveraging proven machine-learning techniques, the Camus platform fills data gaps to create a comprehensive, real-time view of the distribution grid. In the recent webinar “Real-time data and distribution system operations” hosted by the Energy Systems Integration Group (ESIG), Astrid shares three key strategies that distribution utilities can use to leverage existing data to bridge key data gaps - and create the real-time visibility needed to manage complex distribution grid operations.
Grab some popcorn (it’s an hour long) and dive into the webinar today 👇
For questions, you can reach Astrid at email@example.com.