Leveraging Energy Data for Sustainable Buildings

Urban Data Lab (UDL) gained data access to live-streaming building energy datasets from UBC Energy and Water Services (EWS). The data is stored in UDL’s InfluxDB instance and made available to students, researchers and operational staff at UBC as part of UBC’s Campus as a Living Lab Initiative.

The SKYSPARK database on UDL’s InfluxDB instance provides data recorded by the meters and smart devices of each UBC building updated every 15 minutes, including HVAC equipment data, sensor measurements, and weather information. The images below show one day of data for the Pharmacy building (updated every 15 minutes) and UBC weather information (updated every 15 minutes or hourly).

One-day data of Pharmacy (updated every 15 minutes)

Weather information

The ION database on UDL’s InfluxDB instance provides higher granularity data on power, energy, water, and gas use of the buildings. EWS’s ION server follows the OPC-UA specifications and updates data every 5 seconds. UDL accesses and monitors data from the OPC server using OPC Router. Currently, every building has “energy” and “power” data streams but not all buildings have “gas” and/or “water”. The data in UDL’s InfluxDB is updated with every 2 kW change in the electricity power values but the trigger threshold can be modified in the best interest of researchers and operational staff.

One-day data of Pharmacy (updated every 15 minutes)

Hourly data of weather information

With these two datasets available to UBC students, researchers and operational staff, UDL will engage the UBC community to use the data and gather new campus data. UDL has collected the following research and operational interests.

Energy Benchmarking

UDL is now undertaking a benchmarking process to assign an energy use intensity (EUI) measure to each of the buildings on campus. This will help UBC identify poorly performing buildings and establish a baseline for improvement measurement.

Building Retrofits

UDL will conduct a case study with campus researchers, planners, and operational staff to understand the features, functions and software requirements needed to support a campus-wide retrofit scenario analysis system to support the identification, costing and capital planning for building energy efficiency retrofits on campus.

End-use Analysis

UDL will engage students, researchers, and operational staff to understand the different types of energy end-use such as lighting, HVAC, and plugs. Machine learning techniques will be applied for end-use classification, energy profiling, and energy forecasting by end-use.

Climate Scenarios

With weather information in the SkySpark dataset, UDL can develop decision-support systems to improve energy use and GHG emissions under different weather conditions and climate scenarios.

Equipment Maintenance

UDL is interested in developing real-time data solutions to detect abnormal equipment behavior to inform upgrades and maintenance.

Occupancy Analysis

UDL is interested in combining energy data with occupancy data (such as sensor data and Wi-Fi log-ins) to optimize energy consumption, class schedules, and space use.