Data Analytics for Operations at Berkeley Lab
In 2017, Berkeley Lab adopted a data analytics platform designed to collect and organize building operations data. Such platforms are also known as Energy Management & Information Systems (EMIS). The Lab currently uses SkySpark® by SkyFoundry - and calls its server SkyData. To date, more than 19,000 data streams have been integrated and brought into a standardized data model, covering HVAC equipment and sensors in the Lab’s largest mission-critical facilities and hundreds of utility meters across the Lab. Relevant building data streams and metadata are added to the platform regularly.
Using standardized metadata enables the Lab to apply previously-developed tools, such as visualizations, to newly-added data streams; conversely, new tools the Lab develops apply to all relevant data streams across the entire site. This is a major improvement over historical building management systems (BMS), inside which tools are typically developed on a building-by-building basis.
Data analytics platforms also have a high level of interoperability. At Berkeley Lab, SkyData receives data from both JCI and ALC building management systems (via BACnet), from a lighting management system, from an ION electricity metering sql database, from a local weather station, and more. Therefore, SkyData can, for example, display electricity demand along with weather information and chilled water plant equipment status.
Another improvement over typical building management systems is the ability to visualize large amounts of data, such as zone temperatures, over time. Typically, a BMS user has access to floor layouts that show a snapshot of all zone temperatures in a building, either current or historical. Because SkyData has a database that is optimized for time series and offers different visualization tools than a typical BMS, it can easily and clearly display zone temperatures in a building over an entire week.
Finally, a data analytics platform makes it easy to apply a tool to an updated, more recent data set. This makes it possible for commissioning agents, energy managers and consultants to follow up on previous analyses without having to download, pre-process and reorganize data, as is typically necessary when working with BMS data.