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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 theRenewables.ninja service.
importdemand_ninja# `inputs` has to be a pandas.DataFrame with four columns,# humidity, radiation_global_horizontal, temperature,# and wind_speed_2minputs=pd.DataFrame(...)# `result`` will be a pandas.DataFrame# setting raw=True includes the input data and intermediate results# in the final DataFrameresult=demand_ninja.demand(inputs,raw=True)
SeeCHANGELOG.md.
ContactIain Staffell andNathan Johnson if you have questions about Demand.ninja. Demand.ninja is a component of theRenewables.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.
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