CU-BEMS, smart building electricity consumption and indoor environmental sensor datasets

Area of Science:

• Building Energy Systems
• Environmental Sensing
• Data Science Applications

Background:

• Detailed building operation data is crucial for understanding energy consumption patterns.
• Existing datasets often lack granular zone-level measurements for diverse applications.
• Office buildings represent significant energy consumers, necessitating precise operational data.

Purpose of the Study:

• To release a comprehensive dataset of building electricity consumption and indoor environmental parameters.
• To provide high-resolution (one-minute interval) data for an 18-month period.
• To facilitate research in building energy modeling, load forecasting, and control system development.

Main Methods:

• Collected one-minute interval data on electricity consumption (air conditioning, lighting, plug loads) for 33 building zones.
• Acquired indoor environmental data (temperature, relative humidity, ambient light) for the same zones.
• Ensured data availability for an 18-month period (July 1, 2018, to December 31, 2019).

Main Results:

• Detailed electricity consumption data at the zone level is now publicly available.
• Comprehensive indoor environmental measurements (temperature, humidity, light) are provided.
• The dataset covers a large, seven-story, 11,700-m² office building in Bangkok, Thailand.

Conclusions:

• The released dataset offers a valuable resource for advancing building science research.
• Applications include zone-level load forecasting, thermal model validation, and demand response algorithm development.
• This data can significantly contribute to the development of intelligent building control systems and energy efficiency strategies.