Such a great short read on how Camus Energy utilizes Machine learning algorithms to quickly identify EVs and their impacts on grid and utility equipment using the Camus energy orchestration platform. In summary: To find EV chargers that haven’t been registered with the utility, their platform analyzes meter-level load data from advanced metering infrastructure (AMI). The machine learning algorithm is trained on known EV chargers to understand how an EV draws power and searches for that pattern across all meters. Typically, this can detect and report up to 70% of EVs in a given area. #evcharging #ev #orchestration #machinelearning #distributedenergyresources #gridmodernization #gridstability #AMI
Did you know: As little as 30% of all US EVs are enrolled in a utility EV program or tariff. Without clear visibility into EV adoption, utilities are vulnerable to hard-to-predict peak load spikes that can overload critical equipment, drive up operational costs, and threaten reliability. Camus' grid orchestration platform uses a machine learning algorithm to detect up to 70% of 'invisible' EVs in a given area and assess their impacts on the grid. Learn more: https://bit.ly/48vPF50
