Extraction of instantaneous renewable generation from net load measurements of power distribution systems

Abstract

A computer-implemented method is provided for performing energy disaggregation of a distribution system-level net-load measurements using continuous-point-on-wave (CPOW) measurement units. The method uses a processor coupled with a memory stored instructions implementing the method using neural networks including an encoder network, a feature extractor, a separator network, a decoder network stored in the memory, wherein the instructions, when executed by the processor carry out at steps of the method include generating net-load time series data from voltage and current measurements via the CPOW measurement units, generating a compressed latent space representation from the net-load time series, converting the net-load time series into time-frequency domain, passing time domain cotextual information with the converted time-frequency domain representation of net-load time series to the feature extractor, estimating two weight matrices to be multiplied with an output from the encoder network and learning temporal features of a native load and a photovoltaic (PV) generation, transforming weighted latent representation corresponding the native load and the PV generation into time-domain representations, and predicting the native load and the PV generation at distribution system-level from the transformed time domain representations corresponding to the native load and PV generations.