Datasets:

BuildingBench
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HOT

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:

@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
Discussions: Hugging Face Discussions
Email: anonymous for now

HOT Dataset - Advancing building energy research through comprehensive, standardized, and globally-representative data for intelligent HVAC control systems.

HOT Dataset: HVAC Operations Transfer

Overview