Non-Intrusive Load Monitoring Toolkit (nilmtk)

Code for NILM experiments using Neural Networks. Uses Keras/Tensorflow and the NILMTK.

A reimplementation of Jack Kelly's rectangles neural network architecture based on Keras and the NILMToolkit.

A Synthetic Energy Consumption Dataset for Non-Intrusive Load Monitoring

Metrics to assess the generalisation ability of NILM algorithms

Non-Intrusive Load Monitoring is aimed to predict the status or consumption of some domestic appliances in a household only by knowing the aggregated load of that house. In this project, we implement some models that can do both power load estimation and status prediction.

DEPS: Dataset de la Escuela Politénica Superior

This repository contains my implementation for Energy Disaggregation of appliances from mains consumption using stacked ensemble deep learning

This repository contains assignments and project work related to the course

The AMBAL-based NILM Trace generator (for NILMTK)