ihomelab's repositories
dnn4nilm_overview
Overview of NILM works employing Deep Neural Networks on low frequency data
RAPT-dataset
code for the iHomeLab RAPT dataset
effect-of-sampling-rate-on-PV-self-consumption
Estimate the potential for increasing PV self-consumption through load-shifting. This is done by simulating load-shifting
Language:Jupyter Notebook000
snm-dataset
code for the SmartNIALMeter dataset
Language:PythonMIT000