Context

These data were collected and disseminated according to this publication: https://www.nature.com/articles/s41597-020-00582-3

All descriptors below are taken from this publication and are copyright of the authors.

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.

Background

The global energy consumption of the building sector, which includes both commercial and residential buildings, is about 20%. With the rapid increase in population as well as economic growth, energy consumption in buildings is projected to increase at the rate of 1.3% per year from 2018 to 2050; this growing energy demand has raised significant concerns worldwide of its negative impact on the environment. In order to meet the rising electricity demand, an efficient and cost effective operation is needed.

The uniqueness of the CU-BEMS dataset described in this paper is the breakdown of building-level electricity consumption (kW) into each zone and each floor of the building. The CU-BEMS dataset captures the operation of individual AC units, lighting, and plug loads in each zone of the building at one-minute intervals. These are three major loads in commercial buildings. In addition, corresponding indoor environmental sensor data (temperature, humidity, and ambient light) are also measured in each zone at one-minute intervals.

Methods

In mid-2018, CU-BEMS –the building energy management system, developed at Chulalongkorn University using an open standard IEEE1888, was installed at the seven-story academic office building located at Chulalongkorn University. The building has an area of around 11,700 square meters (126,000 sqft) with a peak load of about 700 kW. The overall CU-BEMS system comprises Energy Monitoring Units (EMU), digital meters, multi-sensors, gateways and a CU-BEMS server.

Energy Monitoring Unit (EMU) An EMU is a communicating electrical meter that can measure power consumption of up to 36 circuits and communicate via Ethernet LAN with Modbus protocol. An EMU comprises potential transformers, a microcontroller module and an Ethernet-based communication module. An EMU can connect to up to 36 external current transformers (CT, rating up to 60 Ampere). Based on current and voltage readings, the built-in microcontroller unit calculates power consumption (Watts). Then, the Ethernet module transfers the calculated electricity consumption to the CU-BEMS server using an open standard IEEE 1888 protocol.

Digital Meter Each digital meter used is a commercial off-the-shelf product (Siemens SENTRON PAC3100), which provides basic metering and monitoring applications. It provides open communications using Modbus RTU over RS485 interface. It measures current, voltage, and provides real, reactive power measurements, meeting ANSI C12.16 (accuracy class 1.0, i.e., typical error of 1%) specification for revenue meters.

Multi-sensors Multi-sensors have been designed to measure temperature (0 °C − 90 °C ± 0.4 °C), humidity (0–100%RH ± 2%RH) and ambient light (0.11 − 10000lux). Hence, it comprises temperature, humidity and ambient light sensors, as well as a Wi-Fi communication module.

Gateway CU-BEMS gateways have been developed in house to gather data from multi-sensors. Each gateway comprises a microprocessor and an Ethernet module. It has been designed to collect data at one-minute intervals.

Data Records

The entire datasets are divided into 14 comma-separated value (csv) files according to the floor and year of the data recorded. Note that one CSV file is provided for each floor of the building. This makes the total of seven CSV files for each year. Since each file does include data of each zone on a single floor, a user has the flexibility to work with any individual zones, which can be extracted (based on the column names) from the CSV files.

Each file combines the measurements available in each zone on the same floor of the building in a particular year. These measurements are the electricity consumption (kW) of individual air conditioning (AC) units, lighting loads and plug loads, as well as the environmental sensor data, including indoor temperature (°C), relative humidity (%) and ambient light (lux). Note that the monitored loads do not include the two elevators and emergency exit signs. These loads added up to about 1–2 percent of the total building loads.

Each of the 2018 data files has 264,960 rows, which indicate one-minute interval data (1,440 data points/day) for 184 days during the second half year of 2018. Each of the 2019 data files has 525,600 rows, which indicate one-minute interval data (1,440 data points/day) for 365 days during the entire year of 2019.

The number of columns is different in each file, depending on the number of data measurements on the floor.

For example, the files 2018Floor1.csv and 2019Floor1.csv have 11 data columns, and one timestamp column. These 11 data columns are: Zone 1–Power consumption (kW) of lighting loads (one column); Zone 2–Power consumption (kW) of four individual AC units, one lighting load and one plug load (six columns); Zone 3–Power consumption (kW) of one lighting and one plug loads (two columns); and Zone 4–Power consumption (kW) of lighting and plug loads (two columns). Floor 1 has no sensor.

The files 2018Floor2.csv and 2019Floor2.csv have 36 data columns, which are: Zone 1–Power consumption (kW) of the AC unit, lighting loads and plug loads, as well as indoor temperature (deg C), relative humidity (%) and ambient light condition (lux) measured in this zone (six columns). Zone 2–Power consumption (kW) of 14 individual AC units, lighting loads and plug loads, as well as indoor temperature (deg C), relative humidity (%) and ambient light condition (lux) in this zone (19 columns); Zone 3–Power consumption (kW) of lighting loads and plug loads, and indoor temperature (deg C), relative humidity (%) and ambient light condition (lux) in this zone (five columns); and Zone 4: Power consumption (kW) of the AC unit, lighting loads, plug loads and indoor temperature (deg C), relative humidity (%) and ambient light condition (lux) in this zone (six columns).

For Floor 3 to Floor 7, each floor has five zones. Each zone has one lighting load and one plug load measurements. There are a total of seven AC units and four sensors (each measuring three quantities: temperature, humidity, and ambient light) on each floor. Hence, each file has 29 data columns.

For the entire building, there are power consumption data of 55 individual AC units; power consumption of lighting loads in 33 zones of the building; power consumption of plug loads in 32 zones of the building (Zone 1 on Floor 1 does not have plug load); and temperature, humidity and ambient light readings at 24 locations (72 values) in the building.