The AMBAL-based NILM Trace generator (for NILMTK)
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Updated
Aug 25, 2021 - Python
The AMBAL-based NILM Trace generator (for NILMTK)
The C++ code for my Computing MSc energy disaggregation project
NILM performance evaluation functions use in the Springer Energy Efficiency journal paper.
Master's Dissertation: Unsupervised Low-Frequency NILM for Industrial Loads
ST-NILM is a new integrated architecture based on the Scattering Transform. It has a DCN (Deep Convolutional Network) with analytical wavelet-based non-trained weights, shared with fully connected output networks that perform event detection and multi-label classification of aggregate loads.
Complete set of electrical parameters, including energy consumption, power quality, and all harmonic contents (up to 2kHz). Time-synchronous data reported from real buildings and appliances at 1 second intervals.
Electrical Devices Identification Model (EDIM) for the identification of electrical devices by analyzing their energy consumption profiles.
An aided linear integer programming (ALIP) non-intrusive load monitoring (NILM) algorithm.
A new CNN architecture to perform detection, feature extraction, and multi-label classification of loads, in non-intrusive load monitoring (NILM) approaches, with a single model for high-frequency signals.
Overview of research papers with focus on low frequency NILM employing DNNs
A reimplementation of Jack Kelly's rectangles neural network architecture based on Keras and the NILMToolkit.
Supervised NILM using multiple-choice knapsack problem (MCKP).
An Non-Intrusive Load Disaggregation method based on Neural Network. A sequence-to-sequence model and a sequence-to-point model are proposed.
A repository of awesome Non-Intrusive Load Monitoring(NILM) with code.
The super-state hidden Markov model disaggregator that uses a sparse Viterbi algorithm for decoding. This project contains the source code that was use for my IEEE Transactions on Smart Grid journal paper.
Non-Intrusive Load Monitoring Toolkit (nilmtk)
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