AlphaBuilding-SyntheticDataset

This repository is created for the AlphaBuilding-SyntheticDataset. Details about this dataset could be found on its GitHub page.

Generate synthetic building operation data

The source code to reproduce the dataset could be found in the code directory. Follow the steps below to generate synthetic building operation data:

1. Install OpenStudio v2.9.1. Set up the full path of openstudio.rb in the create_workflow.rb script. The openstudio.rb file could be found in the installed OpenStudio folder: <paht_to_openstudio_installation>/openstudio-2.9.1/Ruby/openstudio.rb.

2. Clone the OpenStudio-Standards repository to your local machine. Set up the full path of openstudio-standards.rb in the create_workflow.rb scipt. The openstudio-standards.rb file could be found in the cloned OpenStudio-Standards repository.

3. Make sure Ruby v2.2.4 is installed.

4. Set up the arguments in the create_workflow.rb. This allows you to create models and run simulations for different building types, vintages, climate zones

   • Step 1. Select the climate zone(s) for simulation. The available climate zones are in the following array. Uncomment the line(s) to specify the climate zone(s) you want to include:

     climate_zones = [
         'ASHRAE 169-2006-1A',     # Considered in the synthetic operatin dataset
         # 'ASHRAE 169-2006-2A',
         # 'ASHRAE 169-2006-2B',
         # 'ASHRAE 169-2006-3A',
         # 'ASHRAE 169-2006-3B',
         'ASHRAE 169-2006-3C',     # Considered in the synthetic operatin dataset
         # 'ASHRAE 169-2006-4A',
         # 'ASHRAE 169-2006-4B',
         # 'ASHRAE 169-2006-4C',
         'ASHRAE 169-2006-5A',     # Considered in the synthetic operatin dataset
         # 'ASHRAE 169-2006-5B',
         # 'ASHRAE 169-2006-6A',
         # 'ASHRAE 169-2006-6B',
         # 'ASHRAE 169-2006-7A',
         # 'ASHRAE 169-2006-8A',
     ]

   • Step 2. Prepare the weather files (EPWs) and map the their folder to the climate zones. For example, this repository provides 30 years' historical and a TMY3 weather files for three U.S. cities - Chicago, Miami, and San Francicso. The weather files are saved in ./EPWs/<city name>_AMY. And the Hash below maps the climate zones of the three cities and the weather file to be used in the simulations.

     hash_climate_epw = {
         # 'climate zone option' => 'EPWs folder name', (example convention)
         'ASHRAE 169-2006-1A' => 'Miami_AMY',
         'ASHRAE 169-2006-3C' => 'SF_AMY',
         'ASHRAE 169-2006-5A' => 'Chicago_AMY',
     }

     You need to provide weather files and mapping rule for buildings in other climate zones.

   • Step 3. Select the vintages you want to consider.

     vintages = [
         # '90.1-2004',
         # '90.1-2007',
         # '90.1-2010',
         '90.1-2013'     # Considered in the synthetic operatin dataset
     ]

   • Step 4. Select the building type to consider. Please note that occupancy_simulator only works for office buildings.

       building_types = [
           ###############################################################
           ## building types that support stochastic occupancy simulation
           ###############################################################
           # 'SmallOffice',
           # 'MediumOffice',
           # 'LargeOffice',
           # 'SmallOfficeDetailed',
           'MediumOfficeDetailed',     # Considered in the synthetic operatin dataset
           # 'LargeOfficeDetailed',
           ###############################################################
           ## building types that do not support stochastic occupancy simulation
           ###############################################################
           # 'SecondarySchool',
           # 'PrimarySchool',
           # 'SmallHotel',
           # 'LargeHotel',
           # 'Warehouse',
           # 'RetailStandalone',
           # 'RetailStripmall',
           # 'QuickServiceRestaurant',
           # 'FullServiceRestaurant',
           # 'MidriseApartment',
           # 'HighriseApartment',
           # 'Hospital',
           # 'Outpatient',
       ]

   • Step 5. Set the number of stochastic occupancy simulations for each building model.

     number_of_stochastic_occupancy_simulation = 5

   • Step 6. Set the energy efficiency level (1 - low, 2 - standard, 3 - high) to run.

     efficiency_level = 2

5. Run the create_workflow.rb script with <ruby 2.2.4 command> create_workflow.rb The script will generate and run OpenStudio workflows to output the synthetic building operation data.

6. Post-processing. The above routine automatically generates OpenStudio models and runs the simulations. This Python script shows an example of extracting the raw CSV outputs and saving them in a structured way. Depending on their purpose, readers may need develop custom routines to process the simulation results.

License

Refer to License.txt