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Plexflo offers a comprehensive ecosystem of tools and libraries that lets you build Deep Learning powered applications for effective management of grid with accurate forecasting and analytics.
Non-Intrusive Load Monitoring (NILM) is the process of deducing/identifying appliances and their energy consumption in a household. With NILM, we enable energy disaggregation – Process of decomposing power consumptions levels at appliance level from the aggregate consumption at house level.
We have built an Open-Source library datastream that aids researchers and engineers to try our Deep Learning models for detection of EVs (Electric Vehicles) charging events from smart home meter data.
$ pip install plexflo
To update plexflo to the latest version, add --upgrade flag to the above
commands.
For examples an how to use the library, see the Official guide.
If you want to contribute to Plexflo, be sure to review the contribution guidelines. This project adheres to Plexflo's code of conduct. By participating, you are expected to uphold this code.