Non-Intrusive Load Monitoring Toolkit (nilmtk)

An Non-Intrusive Load Disaggregation method based on Neural Network. A sequence-to-sequence model and a sequence-to-point model are proposed.

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

Overview of research papers with focus on low frequency NILM employing DNNs

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.

Supervised NILM using multiple-choice knapsack problem (MCKP).

The C++ code for my Computing MSc energy disaggregation project

The AMBAL-based NILM Trace generator (for NILMTK)

Algorithmic Non-Intrusive Load Monitoring (household energy decomposed)

Electrical Devices Identification Model (EDIM) for the identification of electrical devices by analyzing their energy consumption profiles.