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Camus Energy’s grid orchestration platform uses artificial intelligence and machine learning to fill in grid data gaps and model the future. Today, the company announced additional venture funding that it says will help it expand its customer utility base and grow its tech partner ecosystem.
Camus’ software offers utility customers — which include Duquesne Light Company and Vermont Electric Cooperative, among others — a hub for real-time grid visibility, day-ahead forecasting, and distribution system planning insights. But before they can take advantage of that hub, Atkinson said, most Camus customers need help integrating and organizing data from across their organizations.
“Most utilities have a lot of data, they just don’t know quite how to get it to work, and they don’t necessarily have the software systems that will do that well today,” Atkinson told Latitude Media.
Camus’ data integration approach is somewhat unique in that it brings utility data and customer asset data into the same system for side-by-side visibility, Atkinson said. Once there’s a firm foundation of data, Camus builds models that can do forecasting and fill in data gaps, and ultimately provide a real-time view of current conditions.
Load growth from electric vehicles, data centers, and industrial electrification are top of mind for utilities looking to Camus for assistance, Atkinson said. In fact, dealing with load growth is a key driver of AI use cases for utilities.
“Utilities haven’t seen much load growth in a long time,” she said, which means most utilities don’t have the capabilities to know exactly how it will impact their grid, much less the fine-grained or locational data needed to outline their current or future adoption patterns.
“If you think about what we need on the grid, we need to understand more about where challenges are going to hit,” she added. “Utilities need to be able to better incorporate the data that they’ve already started to collect, to understand what that looks like today and in the future.”