Real-time electric vehicle charging detection

A method, comprising:

• detecting, by a metering system comprising one or more processors and memory located on a utility grid downstream from a substation, via a sensor of the metering system, current associated with electricity consumed in the utility grid during a first time interval;
• determining, by the metering system, based on the current detected by the sensor, a current harmonic metric and a power metric associated with the electricity delivered over the utility grid in the first time interval;
• inputting, by the metering system, the current harmonic metric and the power metric into a model trained with machine learning and deployed on the metering system to determine a likelihood that at least a portion of the electricity delivered over the utility grid in the first time interval is used to charge an electric vehicle;
• and
• executing, by the metering system, an action associated with performance of the utility grid responsive to the likelihood satisfying a threshold.

A non-transitory computer-readable medium that stores processor-executable instructions that, when executed by one or more processors, cause the one or more processors to:

• detect, via a sensor of a metering system, current associated with electricity consumed in a utility grid during a first time interval;
• determine, based on the current detected by the sensor, a current harmonic metric and a power metric associated with the electricity delivered over the utility grid in the first time interval;
• input the current harmonic metric and the power metric into a model trained with machine learning and deployed on the metering system to determine a likelihood that at least a portion of the electricity delivered over the utility grid in the first time interval is used to charge an electric vehicle;
• and
• execute an action associated with performance of the utility grid responsive to the likelihood satisfying a threshold.