Grid Connectivity

Grid Connectivity is an artificial intelligence (AI) approach to identifying inaccurate connectivity information on the distribution grid. It relies solely on advanced meter voltage data.

Maintaining an accurate connection between a transformer and an individual meter is critical for grid reliability and asset optimization. Power outage repairs can often result in the reconnection of some meters to a transformer other than the one originally connected—with meters sometimes being rerouted without a corresponding update to utility records. Over time, what you have on file and meter-to-transformer connectivity may vary enough that it becomes difficult to manage the distribution network properly, causing operational inefficiencies, significant energy losses and sharply reduced asset lifetimes.

Grid Connectivity leverages robust machine learning techniques to accurately predict correct phase and transformer connectivity, as well as correctly classify meters according to their phase even with 60-minute voltage measurements. These algorithms power a cloud solution that continuously updates the connectivity map.

Grid Connectivity allows utilities to:

• Provide end-to-end monitoring and communication to analyze each line segment from meter to feeder for revenue assurance and theft detection
• Utilize field asset management and transformer monitoring to gain valuable insight into distribution systems
• Detect power theft and high-impedance connections by comparing meter voltage to that of neighboring meters
• Find misplaced or misfiled meters