Non Intrusive Load Monitoring in Chaotic Switching Networks

TL;DR

This paper proposes a non-intrusive load disaggregation method using kernel-based nonlinear regression to analyze chaotic switching dynamics in electric networks, aiming to improve load monitoring accuracy.

Contribution

It introduces a novel kernel-based nonlinear regression approach for load disaggregation in chaotic switching networks, advancing non-intrusive monitoring techniques.

Findings

Effective approximation of chaotic switching dynamics

Potential for improved load disaggregation schemes

Demonstrated usefulness in electric network analysis

Abstract

In this work, a non intrusive load disaggregation scheme is proposed. By using a kernel based nonlinear regression strategy, the switching dynamic of an electric network, simulated as a set of RLC circuits with chaotic switching, is approximated using a time series of the total power consumption. The results suggest that the employed methodology can be useful in the design of efficient load disaggregation schemes.