Abstract
This paper describes the release of the detailed building operation data, including electricity consumption and indoor environmental measurements, of the seven-story 11,700-m2 office building located in Bangkok, Thailand. The electricity consumption data (kW) are that of individual air conditioning units, lighting, and plug loads in each of the 33 zones of the building. The indoor environmental sensor data comprise temperature (°C), relative humidity (%), and ambient light (lux) measurements of the same zones. The entire datasets are available at one-minute intervals for the period of 18 months from July 1, 2018, to December 31, 2019. Such datasets can be used to support a wide range of applications, such as zone-level, floor-level, and building-level load forecasting, indoor thermal model development, validation of building simulation models, development of demand response algorithms by load type, anomaly detection methods, and reinforcement learning algorithms for control of multiple AC units.
Highlights
Background & SummaryThe global energy consumption of the building sector which includes both commercial and residential buildings is approximately 20%1
With the building sector accounting for one-third of greenhouse gases, two-thirds of halo-carbon and approximately 25–33% of black carbon emissions[3], this growing energy demand has raised significant concerns worldwide of its negative impact on the environment
Buildings are increasingly equipped with building automation systems (BAS) and smart meters which gather load and other related data at a granular level
Summary
The global energy consumption of the building sector which includes both commercial and residential buildings is approximately 20%1. Some higher resolution data are available for energy disaggregation research These are: BERDS (BERkeley EneRgy Disaggregation Dataset)[28], which includes energy consumption and outdoor temperature data of a building at 20 second intervals; BLOND (a building-level office environment dataset of typical electrical appliances)[29], which provides whole building energy measurements and appliance-level energy consumption at high sampling rate; and COMBED (the Commercial Building Energy Dataset)[30], which provides 30-second data across 200 smart meters on a university campus for one month.
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