| # HOT Dataset: HVAC Operations Transfer | |
| ## Overview | |
| The **HOT (HVAC Operations Transfer)** dataset is the first large-scale open-source dataset purpose-built for transfer learning research in building control systems. Buildings account for approximately 10-15% of global energy consumption through HVAC systems, making intelligent control optimization critical for energy efficiency and climate change mitigation. | |
| ### Key Statistics | |
| - **159,744** unique building-weather combinations | |
| - **15,808** building models with controllable zone-level setpoints | |
| - **19** ASHRAE climate zones across **76** global locations | |
| - **16** commercial building types (office, retail, school, hospital, etc.) | |
| - **12** systematic occupancy patterns | |
| - **3** thermal performance scenarios | |
| - **15-minute** timestep resolution for control applications | |
| ## Dataset Description | |
| HOT addresses the critical infrastructure gap in building control transfer learning by providing systematic variations across four key context dimensions: | |
| ### 🏢 **Building Geometry** (16 Types) | |
| - **Office**: Small (511 m²), Medium (4,983 m²), Large (46,323 m²) | |
| - **Retail**: Standalone (2,294 m²), Strip Mall (2,294 m²) | |
| - **Educational**: Primary School (6,874 m²), Secondary School (19,592 m²) | |
| - **Healthcare**: Hospital (22,443 m²), Outpatient (3,805 m²) | |
| - **Hospitality**: Small Hotel (3,726 m²), Large Hotel (11,349 m²) | |
| - **Residential**: Midrise Apartment (2,825 m²), Highrise Apartment (7,063 m²) | |
| - **Food Service**: Sit-down Restaurant (511 m²), Fast Food (232 m²) | |
| - **Industrial**: Warehouse (4,835 m²) | |
| ### 🌡️ **Thermal Performance** (3 Scenarios) | |
| - **Default**: Baseline thermal properties (R_mult = 1.0) | |
| - **High Performance**: Enhanced insulation (R_mult = 2.0, U_mult = 0.5) | |
| - **Low Performance**: Minimal insulation (R_mult = 0.5, U_mult = 2.0) | |
| ### 🌍 **Climate Conditions** (76 Locations) | |
| - **Complete ASHRAE coverage**: All 19 climate zones (0A through 8) | |
| - **Global diversity**: From tropical (Ho Chi Minh) to subarctic (Fairbanks) | |
| - **Weather data types**: TMY (Typical Meteorological Year) + Real historical (2014-2024) | |
| - **Temperature range**: -44.4°C to 47.0°C | |
| - **HDD range**: 0 to 7,673 heating degree days | |
| - **CDD range**: 6 to 4,301 cooling degree days | |
| ### 👥 **Occupancy Patterns** (12 Schedules) | |
| - **Standard**: Traditional office hours (8 AM - 5 PM weekdays) | |
| - **Low/High Occupancy**: 50%/150% intensity variations | |
| - **Shift Operations**: Early (6 AM-3 PM), Late (2 PM-11 PM) | |
| - **Sector-Specific**: Retail (10 AM-9 PM), School (7 AM-4 PM + evening) | |
| - **Healthcare**: Hospital 24/7 with shift patterns | |
| - **Modern Work**: Flexible hybrid with staggered hours | |
| - **Specialized**: Gym (morning/evening peaks), Warehouse logistics | |
| - **Continuous**: 24/7 operations | |
| ## Dataset Structure | |
| HOT/ | |
| ├── data/ | |
| │ ├── base/ # Raw building models by geometry type | |
| │ │ ├── ApartmentHighRise_STD2013/ | |
| │ │ ├── ApartmentMidRise_STD2013/ | |
| │ │ ├── Hospital_STD2013/ | |
| │ │ ├── OfficeSmall_STD2013/ | |
| │ │ └── ... # 16 building geometry folders | |
| │ ├── processed/ | |
| │ │ └── base/ # Processed EPJSONs ready for control | |
| │ │ ├── ApartmentHighRise_STD2013.epJSON | |
| │ │ ├── Hospital_STD2013.epJSON | |
| │ │ └── ... # All processed buildings | |
| │ ├── variations/ # Building variations | |
| │ │ ├── occupancy/ # Occupancy schedule variations | |
| │ │ │ ├── standard/ | |
| │ │ │ ├── low_occupancy/ | |
| │ │ │ ├── hospital/ | |
| │ │ │ └── ... # 12 occupancy patterns | |
| │ │ ├── thermal/ # Thermal performance variations | |
| │ │ │ ├── default/ | |
| │ │ │ ├── high_performance/ | |
| │ │ │ └── low_performance/ | |
| │ │ └── combined/ # Multi-variable combinations | |
| │ │ ├── occupancy_24_7_thermal_default/ | |
| │ │ ├── occupancy_hospital_thermal_high_performance/ | |
| │ │ └── ... # All combinations | |
| │ ├── weather/ # Weather data files (.epw) | |
| │ │ ├── base/ # Base TMY weather files (19 locations) | |
| │ │ ├── expanded/ # Extended TMY files (57 additional locations) | |
| │ │ ├── real_base/ # Historical weather (2014-2024) | |
| │ │ └── tables/ # Weather metadata tables | |
| │ └── tables/ # Dataset metadata and combinations | |
| │ ├── buildings.csv # Building characteristics | |
| │ └── building_weather_combinations.csv # All 159,744 pairings | |
| ## Key Features | |
| ### 🎮 **Reinforcement Learning Ready** | |
| - **Controllable setpoints**: Zone-level heating/cooling temperature control | |
| - **Gymnasium interface**: Standard RL environment wrapper | |
| - **Comprehensive state space**: Zone temperatures, outdoor conditions, energy consumption | |
| - **Multi-objective rewards**: Energy efficiency + thermal comfort + control stability | |
| - **EnergyPlus integration**: Physics-based building simulation | |
| ### 🔬 **Transfer Learning Framework** | |
| - **Similarity metrics**: Quantitative compatibility assessment across 4 dimensions | |
| - **Zero-shot evaluation**: Direct policy transfer without retraining | |
| - **Systematic variations**: Single and multi-variable transfer scenarios | |
| - **Benchmark protocols**: Standardized evaluation methodology | |
| ### 🌐 **Global Climate Coverage** | |
| - **All inhabited regions**: Complete ASHRAE climate zone representation | |
| - **Real vs. synthetic**: TMY baseline + historical weather variability | |
| - **Extreme conditions**: From subarctic (-44°C) to desert (+47°C) | |
| - **Transfer analysis**: Climate adaptation and geographic deployment | |
| ### 📊 **Research Infrastructure** | |
| - **Standardized formats**: Consistent EnergyPlus epJSON structure | |
| - **Processing pipeline**: Automated building modification tools | |
| - **Validation tools**: Building model verification and testing | |
| - **Similarity analysis**: Transfer feasibility assessment toolkit | |
| ## Research Applications | |
| ### 🤖 **Reinforcement Learning** | |
| - **Multi-agent control**: Coordinate multiple HVAC zones | |
| - **Meta-learning**: Fast adaptation to new buildings (MAML, Reptile) | |
| - **Foundation models**: Pre-train on diverse building types | |
| - **Safe RL**: Constraint-aware control with comfort guarantees | |
| ### 🔄 **Transfer Learning** | |
| - **Domain adaptation**: Geographic and climate transfer | |
| - **Few-shot learning**: Minimal data adaptation for new buildings | |
| - **Cross-building generalization**: Policy transfer across archetypes | |
| - **Similarity-guided selection**: Optimal source building identification | |
| ### 📈 **Building Analytics** | |
| - **Energy benchmarking**: Performance comparison across climates | |
| - **Occupancy analysis**: Usage pattern impact on energy consumption | |
| - **Envelope optimization**: Thermal performance sensitivity analysis | |
| - **Climate resilience**: Building adaptation to changing conditions | |
| ## Dataset Statistics | |
| | **Dimension** | **Count** | **Range** | **Examples** | | |
| |---------------|-----------|-----------|--------------| | |
| | Building Types | 16 | 232-46,323 m² | Office, Hospital, School | | |
| | Climate Zones | 19 | -44°C to +47°C | 0A (Tropical) to 8 (Subarctic) | | |
| | Occupancy Schedules | 12 | 53-168 hrs/week | Office, Retail, Hospital, 24/7 | | |
| | Thermal Scenarios | 3 | 0.5-2.0× resistance | High/Default/Low performance | | |
| | Weather Files | 192 | TMY + Real (2014-2024) | Geographic + temporal variation | | |
| ## File Formats | |
| ### Building Models (`.epJSON`) | |
| - **Format**: EnergyPlus JSON input files | |
| - **Features**: Zone-level controllable setpoints, comprehensive meters | |
| - **Compatibility**: EnergyPlus 24.1+ | |
| - **Size**: ~50-500 KB per building | |
| ### Weather Files (`.epw`) | |
| - **Format**: EnergyPlus Weather format | |
| - **Frequency**: Hourly meteorological data | |
| - **Variables**: Temperature, humidity, solar, wind | |
| - **Size**: ~1-2 MB per location-year | |
| ### Metadata Tables (`.csv`) | |
| - **Buildings**: Physical characteristics, variations, file paths | |
| - **Weather**: Climate statistics, location data, file paths | |
| - **Combinations**: Valid building-weather pairings (159,744 total) | |
| ## Benchmarks and Baselines | |
| ### Control Algorithms | |
| - **Static Baseline**: Seasonal ASHRAE setpoint schedules | |
| - **PPO**: Proximal Policy Optimization with building-specific tuning | |
| ### Transfer Learning Methods | |
| - **Zero-shot**: Direct policy application without retraining | |
| - **Fine-tuning**: Limited adaptation with target building data | |
| - **Meta-learning**: MAML and Reptile for fast adaptation | |
| ### Evaluation Metrics | |
| - **Transfer Performance Ratio**: Transferred vs. target-trained performance | |
| - **Energy Efficiency**: HVAC consumption reduction vs. baseline | |
| - **Comfort Violations**: Hours outside desired temperature range | |
| - **Training Acceleration**: Reduced learning time through transfer | |
| ## Citation | |
| If you use the HOT dataset in your research, please cite: | |
| ```bibtex | |
| @inproceedings{2025hot, | |
| title={A HOT Dataset: 150,000 Buildings for HVAC Operations Transfer Research}, | |
| author={anonymous}, | |
| booktitle={x}, | |
| year={2025}, | |
| publisher={x} | |
| } | |
| ``` | |
| ## License | |
| This dataset is released under the MIT License. See `LICENSE` file for details. | |
| ## Contributing | |
| We welcome contributions to expand and improve the HOT dataset: | |
| - **New building types**: Additional commercial/residential archetypes | |
| - **Climate expansion**: More geographic locations and weather data | |
| - **Enhanced metadata**: Additional building characteristics | |
| - **Analysis tools**: Transfer learning evaluation scripts | |
| - **Bug reports**: Issues with building models or processing | |
| ## Support and Contact | |
| - **Issues**: [GitHub Issues](https://github.com/your-org/building-generator/issues) | |
| - **Discussions**: [Hugging Face Discussions](https://huggingface.co/datasets/BuildingBench/HOT/discussions) | |
| - **Email**: anonymous for now | |
| --- | |
| **HOT Dataset** - Advancing building energy research through comprehensive, standardized, and globally-representative data for intelligent HVAC control systems. |