Behind-the-Meter Device Detection Using Load and Weather Data

The patent introduces an intermediary approach by using weather data (irradiance information) as a mediator to indirectly infer PV system characteristics. Instead of directly measuring behind-the-meter devices, the system uses external weather information combined with net load profiles to deduce device presence and characteristics, thus maintaining monitoring transparency while preserving energy autonomy.

The patent replaces direct mechanical measurement infrastructure with an information-processing approach. Instead of installing additional physical meters or sensors behind the meter, the system substitutes a computational model that processes net load profiles and weather data to identify devices, eliminating the need for costly physical expansions while maintaining monitoring capabilities.

The patent applies self-service by utilizing existing net load measurement data and free weather information to achieve device identification. The system serves itself by processing already-available data through mathematical models and machine learning algorithms, eliminating the need for additional measurement infrastructure while maintaining precise device identification capabilities.

The patent creates a virtual copy of the physical measurement infrastructure through computational models. Instead of physically installing new meters, the system creates a digital representation that processes net load profiles and weather data to infer device characteristics, achieving equivalent measurement precision through information processing rather than physical duplication.