DOI: 10.5522/04/30296803.v1
title: <b>A synthetic dataset of heating energy flexibility in UK office buildings</b>

description: <b>A synthetic dataset of heating energy flexibility in UK office buildings</b>This repository contains a <b>synthetic dataset</b> of building models and their corresponding <b>time-series heating electricity meter data</b>, designed for research and simulation studies.The dataset consists of two main components:<b>Building Models</b><b>Time-Series Heating Electricity Meter Data</b>A step-by-step guideline and the source-code to generate this dataset can be found at GitHub (https://github.com/BuildNexusX/Synthetic-data-of-heating-energy-flexibility-in-UK-office-buildings.git).Dataset Structure1. Building Models (<code>Building_Models/</code>)This component includes 2000 synthetic office buildings in the UK context, each assigned a unique ID ranging from <code>0</code> to <code>1999</code>.<b>Metadata</b><br>Metadata describing all models is provided in: (<code>Building_Models/Metadata/Metadata.xlsx</code>) This file lists 11 variables associated with each model, including HVAC SPF (SPF), Layout, Volume (Level), Orientation, Window-to-wall ratio (WWR), Age Band, Equipment Density, Occupancy Density, Constructional Components Structure, Furniture Mass Material, Furniture Density. For details and explanations of each variable, please refer to the publication. The information about the flexibility event is shown in the next bullet point.<b>Model idfs</b><br>For every building, <b>five IDFs</b> are provided in: <code>Building_Models/Model_idfs/</code> Including 1 Baseline (BL) scenario and 4 Demand Response (DRM / DRN / DRA / DRE) events, named after their Building IDs. BL heating setpoint is maintained at 23°C during working hours (07:00–20:00). The DR setpoint temperatures were varied between 19°C and 21°C during the assumed peak times, representing higher- and lower-response cases respectively. This includes a four-hour morning session (DR_M, 10:00-14:00, 21°C), a two-hour noon session (DR_N, 12:00-14:00, 19°C), a four-hour afternoon session (DR_A, 15:00-19:00, 19°C), and a two-hour evening session (DR_E, 17:00-19:00, 20°C). 500 buildings with 5 idfs each are compressed into one zip for easy download.<b>Weather File</b><br>Simulations were run using EnergyPlus <b>v9.4.0</b>, with the following weather file included: <code>Building_Models/Weather_File/GBR_LONDON-CITY_037683S_17-16_1.epw</code>2. Time-Series Heating Data (<code>Time_Series_Data/</code>)This directory contains <b>15-minute interval heating meter readings</b> for all 2000 building models.<b>Scenarios</b><br>Results are provided for: 1 Baseline (BL) scenario and 4 Demand Response (DR_M / DR_N / DR_A / DR_E) events. Each scenario is stored in a separate CSV file.<b>Units</b><br>Values represent <b>total heating energy consumption (kWh)</b> during each 15-minute interval, measured from the given timestamp to the next.<b>Notes</b><br>This data record is calculated from the simulation result of heating demand in building models (<i>OUTPUT:METER,Heating:DistrictHeating</i>)<i>,</i> divided by the assumed HVAC SPF in each building.Repository StructureBuilding_Flexibility_Dataset/├── Building_Models/│ ├── Metadata/│ │ └── Metadata.xlsx # Metadata of all 2,000 synthetic buildings│ ├── Weather/│ │ └── GBR_LONDON-CITY_037683S_17-16_1.epw # EPW weather file│ └── IDF_Models/│ ├── 0-499.zip/│ │ ├── 0BL.idf # Baseline scenario│ │ ├── 0DR_M.idf # Morning DR (10:00–14:00)│ │ ├── 0DR_N.idf # Noon DR (12:00–14:00)│ │ ├── 0DR_A.idf # Afternoon DR (15:00–19:00)│ │ ├── 0DR_E.idf # Evening DR (17:00–19:00)│ │ └── ... # Models 1–499 structured similarly│ ├── 500-999.zip/│ ├── 1000-1499.zip/│ └── 1500-1999.zip/└── Time_Series_Data/├── Heating_Electricity_BL.csv # Baseline├── Heating_Electricity_DRM.csv # Morning DR├── Heating_Electricity_DRN.csv # Noon DR├── Heating_Electricity_DRA.csv # Afternoon DR└── Heating_Electricity_DRE.csv # Evening DRRequirementsEnergyPlus v9.4.0 (for running the IDFs)Python, R, Matlab, Excel, or any preferred tool for handling the time-series CSV filesCitationIf you use this dataset in your research, please cite (PUBLICATION)ContactFor questions or contributions, feel free to open an issue or contact rui.tang@ucl.ac.uk