Package: energy-demand
HIREwas written in Python (Python>=3.6) and developed at theEnvironmental Change Institute,
University of Oxfordwithin the
EPSRC sponsored MISTRAL programme, as part of theInfrastructure Transition
Research Consortium.More information on the model can be found in:Eggimann, S., Hall, W.J., Eyre, N. (2019): A high-resolution spatio-temporal
energy demand simulation of large-scale heat pump diffusion to explore the
potential of heating demand side management. Applied Energy, 236, 997–1010.https://doi.org/10.1016/j.apenergy.2018.12.052.1. Download input dataMost data for running HIRE are freely available online. For some input data it is necessary to request access.
For more information on all necessary input datasets seeHIRE docs)All necessary input data to run HIRE can be downloaded, where
for the restricted datasets a dummy input dataset is used instead.For data inquires, plese contactsven.eggimann@ouce.ox.ac.ukorthe consortium).
Also check whether data area available fromNISMOD.2. Initialising and running the model (local)The recommended installation method is to useconda,
which handles packages and virtual environments. First, create a conda environment:conda create --name energy_demand python=3.6and activate it:activate energy_demandIn order to run HIRE, first the model needs to be set up (Section 1.1 or Section 1.1).2.1 Model Set-Up (with complete data)Add all necessary data into a local directory such aspath/to/energy_data_folderand
download the energy_demand python code.Note: Because some data is not open source, the full data needs to be optained
from the consortium. However, the model can be run with dummy data (see Section 1)Update the paths in thewrapperconfig.inifile in the config folderNavigate to the folder where the python code is saved. Open a command and type into
a command line (in a virtual environment):python setup.py developInstall HIRE from within the console with the commandenergy_demand setup-fpath/to/config.iniThepath/to/energy_data_folderis the path to the location with
the necessary data to run the model.Note: Thesetupcommand generates new subfolders in theenergy_data_folder.2.2 Alternative Model Set-Up (with restricted dummy data)Add the minimum data requirements into a local directory aspath/to/energy_data_folderand
download the energy_demand python code.Update the paths in thewrapperconfig.inifile in the config folderNavigate to the folder where the python code is saved. Open a command and type into
a command line (in a virtual environment):python setup.py developInstall HIRE from within the console with the commandenergy_demand minimal_setup-fpath/to/config.iniExample: energy_demand minimal_setup -f  C:/Users/fred1234/data_energy_demandThepath/to/energy_data_folderis the path to the location with
the necessary minimum dummy data to run the model.Note: Theminimal_setupcommand generates new folders in theenergy_data_folder.3. Running HIRE with smifSet up the model as outlined in 1.1 ‘Model Set-Up’Install and set-up smif (seesmif instructions)pip installenergy_demandRun the energy demand model for a scenario with
the command:smif run NAME_SCENARIOTo change the logger level of an individual sector model with smif, type:smif-vrun modelrun_idorsmif-vvrun modelrun_id4. Generating plots based from simulation resultsEvery time a model gets run, the specific model simulation results
are stored in the result folder named after the timestamp of the model execution.In order to generate plots of the results, the scripts in the ‘processing’
folder needs to be used. Proceed as follows:Select all generated result folders for which you want to generate plots.Copy them into an empty folder.Configure the ‘energy_demand/processing/multiple_scenarios.py’ file,
namely the arguments of the process_result_multi_scen() function,
and execute the function.This generates all plots in the invidual result folders.Note:
In the ‘process_result_multi_scen’ function all plots
which should be generated can be configured