nilm
There are 9 repositories under nilm topic.
- Language:Python 791
ch-shin / awesome-nilm
A curated resources of awesome NILM resources
JackKelly / neuralnilm
Deep Neural Networks Applied to Energy Disaggregation
Language:Python 145OdysseasKr / neural-disaggregator
Code for NILM experiments using Neural Networks. Uses Keras/Tensorflow and the NILMTK.
Language:Jupyter Notebook 134smakonin / SparseNILM
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.
Language:Python 82zhgqcn / awesome-NILM-with-code
A repository of awesome Non-Intrusive Load Monitoring(NILM) with code.
ChristoferNal / multi-nilm
Multi-NILM: Multi Label Non Intrusive Load Monitoring
Language:Python 59- Language:Jupyter Notebook 50
- Language:Python 44
antoniosudoso / attention-nilm
An Attention-based Deep Neural Network for Non-Intrusive Load Monitoring
Language:Python 39maechler / nnilm
A reimplementation of Jack Kelly's rectangles neural network architecture based on Keras and the NILMToolkit.
Language:Python 34UCA-Datalab / nilm-thresholding
:warning: This repository is no longer actively maintained. It previously dealt with Non-Intrusive Load Monitoring (NILM), focusing on predicting household appliance status from aggregated power load data. We explored different thresholding methods and evaluated deep learning models for regression and classification tasks.
Language:Python 32louisyuzhe / MachineLearning_NILM
Undergraduate research by Yuzhe Lim in Spring 2019. Field of research: Deep Neural Networks application on NILM (Nonintrusive load monitoring) for Energy Disaggregation
Language:Jupyter Notebook 31LucasNolasco / DeepDFML-NILM
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.
Language:Jupyter Notebook 28mahnoor-shahid / nilm_analyzer
Simple, fast and handy data loaders for NILM datasets to explore the data at convenience, provided with basic transformations like resampling, normalization and extract activities by thresholding.
Language:Python 28- SynD
mukkla / LowFreq_DNN-NILM
Overview of research papers with focus on low frequency NILM employing DNNs
voelkerb / powermeter
An ESP32 based plug level electricity meter
Language:C++ 19- Language:Jupyter Notebook 18
18D070001 / Electrical-Devices-Identification-Model
Electrical Devices Identification Model (EDIM) for the identification of electrical devices by analyzing their energy consumption profiles.
Language:Jupyter Notebook 17areinhardt / antgen
AMBAL-based NILM Trace generator
Language:Python 17Henry-2000 / NILM_with_PLAID_dataset
In this repository are available codes in python for implementation of classification of loads and event detection using PLAID dataset
Language:Python 16- Language:Jupyter Notebook 13
ihomelab / dnn4nilm_overview
Overview of NILM works employing Deep Neural Networks on low frequency data
Language:Jupyter Notebook 12compsust / ALIP_NILM
An aided linear integer programming (ALIP) non-intrusive load monitoring (NILM) algorithm.
Language:MATLAB 10- Language:Python 10
SrdjanLL / SensibleNILM
Energy disaggregation - Deep learning approach.
Language:Python 10- MORED
MOREDataset / MORED
A Moroccan Buildings’ Electricity Consumption Dataset. MORED is made available by TICLab of the International University of Rabat (UIR), and the data collection was carried out as part of PVBuild research project, coordinated by Prof. Mounir Ghogho and funded by the United States Agency for International Development (USAID).
NILM performance evaluation functions use in the Springer Energy Efficiency journal paper.
Language:Python 9- Language:Python 9
Mixed-Integer Nonlinear Programming for NILM
Language:Python 8gjwo / nilm_gjw_data
Non Intrusive Load Monitoring data repository and data converter for NILMTK
Language:Jupyter Notebook 8kbodurri / NILM
Code for our MPS 2019 paper entitled "A Machine Learning Approach for NILM based on Odd Harmonic Current Vectors"
Language:Jupyter Notebook 8ST-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.
Language:Jupyter Notebook 8Presentation of Neural NILM for BuildSys 2015 conference in November 2015
Language:HTML 7Easy to implement and customize an end-to-end machine learning pipeline for training the archiecture of seq2point model for energy disaggregation. Run experiments and analyze training procedures or models with ease.
Language:Jupyter Notebook 7
