The Demand.ninja model delivers an hourly time-series of energy demand for a given location, for your chosen temperaure thresholds and BAIT (building-adjusted internal temperature) parameters which describe the characteristics of a building and its occupants.
This code also runs online on the Renewables.ninja service.
import demand_ninja
# `inputs` has to be a pandas.DataFrame with four columns,
# humidity, radiation_global_horizontal, temperature,
# and wind_speed_2m
inputs = pd.DataFrame(...)
# `result`` will be a pandas.DataFrame
# setting raw=True includes the input data and intermediate results
# in the final DataFrame
result = demand_ninja.demand(inputs, raw=True)See CHANGELOG.md.
Contact Iain Staffell and Nathan Johnson if you have questions about Demand.ninja. Demand.ninja is a component of the Renewables.ninja project, developed by Stefan Pfenninger and Iain Staffell.
If you use Demand.ninja or code derived from it in academic work, please cite:
Iain Staffell, Stefan Pfenninger and Nathan Johnson (2023). A global model of hourly space heating and cooling demand at multiple spatial scales. Nature Energy.
The code is available under a BSD-3-Clause license.