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Martín Mosteiro Romero authored Dec 14, 2022
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This repository contains the research compendium for our paper:

> Mart\'in Mosteiro-Romero, Clayton Miller, Adrian Chong, and Rudi Stouffs (2022).
> Martín Mosteiro-Romero, Clayton Miller, Adrian Chong, and Rudi Stouffs (2022).
> Elastic buildings: Calibrated district-scale simulation of occupant-flexible campus operation for hybrid work optimization.
> Submitted to _Building and Environment_.
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│ └── electricity_kWh_2018-2020.csv # csv file containing the hourly electricity demand by for each building for the period 2018-2020
│ └── occupancy_wifi_2018-2020.csv # csv file containing the hourly number of devices connected to the WiFi network by building for the period 2018-2020
│ └── weather_2018_and_2020.csv # csv file containing measured weather station data for the years 2018 and 2020
├── CEA_model # directory containing the CEA models developed in this study; please refer to the [CEA documentation](https://city-energy-analyst.readthedocs.io/en/latest/) for the documentation of each individual file
├── CEA_model # directory containing the CEA models developed in this study; please refer to the for the documentation of each individual file
│ ├── baseline # baseline model of the university campus using archetypal CEA inputs for the years 2018 and 2020
│ │ ├── 2018 #
│ │ │ └── inputs #
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│ │ │ │ └── *.csv # csv file containing the operating schedules of a given building in the case study area
│ │ │ └── networks #
│ │ │ │ └── streets.shp, streets.* # shapefile of the streets within the site (not used in this study)
│ │ │ └── technology # CEA databases imported when creating a CEA model; please refer to the [CEA documentation](https://city-energy-analyst.readthedocs.io/en/latest/) for the documentation of each individual file
│ │ │ └── technology # CEA databases imported when creating a CEA model; please refer to the CEA documentation for the documentation of each individual file
│ │ │ │ └── archetypes #
│ │ │ │ └── assemblies #
│ │ │ │ └── components #
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│ │ │ └── weather.epw # weather file used in this scenario
│ │ │ └── future_scenarios # weather files for future climatic scenarios
│ │ │ └── weather-TMY.epw # typical meteorological year weather file
│ │ │ └── weather-2020.epw # weather file generated by using `weather-TMY.epw` as an input to the R package [epwshiftr](https://github.com/ideas-lab-nus/epwshiftr)
│ │ │ └── weather-2020.epw # weather file generated by using `weather-TMY.epw` as an input to the R package epwshiftr
│ │ │ └── weather-2040.epw # weather file generated by using `weather-TMY.epw` as an input to the R package epwshiftr
│ │ │ └── weather-2060.epw # weather file generated by using `weather-TMY.epw` as an input to the R package epwshiftr
│ │ ├── 2020 #
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│ │ │ └── ... # (see .\CEA_model\baseline\2018 for folder structure)
│ │ └── WFH-0.75-closed_buildings # scenario with 25% occupancy and elastic space allocation
│ │ └── ... # (see .\CEA_model\baseline\2018 for folder structure)
│ └── 0_daysim_binaries # [Daysim](https://github.com/MITSustainableDesignLab/Daysim) binaries required to run the CEA radiation script. These are included in the CEA installation package
│ └── location_geocode.csv # Dataset with locations and their longitude and lattitude
│ └── 0_daysim_binaries # Daysim binaries required to run the CEA radiation script
└── plots # plots generated using full_paper_workflow.ipynb
```

Please refer to the [CEA documentation](https://city-energy-analyst.readthedocs.io/en/latest/) for the description of the contents of each file in a CEA case study and each file in the CEA database. Please refer to the [epwshiftr GitHub page](https://github.com/ideas-lab-nus/epwshiftr) for documentation on that specific package.

## Requirements
This workflow requires a few different packages to be installed, most importantly the City Energy Analyst v3.27.0. CEA includes the majority of the packages required to replicate this work, except a few additional ones:

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