‘Breaking bad’ on building data
Internet sites seem to have an uncanny perception of what regular users would like to know about. Andrew Dyke of ABEC likens it to what can be achieved with a building-management system.
Strange as it sounds, the Netflix Internet streaming service for movies and episodes of TV shows can teach the building-management-systems industry an important lesson about advanced analytics. These advances in software packages for energy management are set to pave the way for a totally new approach to energy — resulting in greater occupancy comfort, longer asset life, and increased cost savings.
I’m a ‘Breaking bad’ fan [an American crime drama television series]. The trials and exploits of Walter and Jesse make for compelling viewing, and I’ve found myself tuning to Netflix night after night. While I approach the end of the final season, I find Netflix is getting me ready for my next box-set. You might like ‘Better call Saul’ or ‘House of cards’ it tells me. It’s impressive that Netflix is able to monitor and suggest what we’ll like. Box-set addicts will also know that these recommendations are getting more accurate.
In an effort to provide ever-greater predictive accuracy, organisations are concerning themselves with so-called ‘big data’.
Using the latest analytics software, companies turn the data into useable information to help them better understand their customers’ needs and desires. This data analysis is giving them insight into what the market wants to buy, what content it finds engaging, and what values it finds attractive. The result is business plans and investment decisions that are much more sophisticated and ultimately more likely to succeed.
Surprisingly, there are many parallels with building energy management.
The building energy management system (BEMS) tells us the behaviour of the building — be it heating, cooling or ventilation systems, with separate components playing the role of individual consumers.
Managing and monitoring the behaviour of the components is the primary function of the BEMS, using the data it collects from the building systems connected to it.
This ‘manage-and-monitor’ approach is set to change with the introduction of advanced analytics software into BEMS.
The information from traditional BEMS and automated monitoring and targeting (aM&T) platforms is retrospective and relatively basic; it tells you how much energy is used, and when. This allows users to make forward plans. While this is valuable, predicting energy usage trends and being able to respond to issues before they happen is much more powerful.
This is the crucial shift from traditional BEMS/aM&T operations to an analytics approach. The new systems pinpoint exactly where events are happening, minute-by-minute, and use this information to identify improvements and introduce efficiencies in real-time.
Take an example of an open-plan office with centralised heating, ventilation and air conditioning. A standard BEMS will enable you to monitor and control the temperature of the space and operation of the services against established parameters. It will operate normally until these parameters are exceeded, triggering an alarm. Usually, this will only tell you that a temperature limit has been exceeded or an item of equipment has a fault.
What it won’t necessarily tell you is the full nature of the fault or its priority in terms of comfort loss or energy waste. The time lag from this action prolongs the compromise to building comfort and efficiency brought about by any fault. It also introduces the potential of manual error when considering where to focus maintenance capital spend.
The analytics approach is far more sophisticated. The system’s intelligence means it can identify small changes in temperature and pinpoint why and where this is happening. The analytics software will identify potential problems before they happen and provide intelligence that enables immediate remedial actions based on the alert’s ranking under categories such as energy losses, discomfort and asset life reduction. As such, analytics enables the remedying actions to be identified and implemented before complaints are received, excess energy is used and, ultimately, asset life compromised.
Those in charge of organisation’s energy bills will find the ability of the software to convert efficiency loses into real-time monetary values a major advantage of analytics. Such software presents a league table of the individual cases to enable targeted focus to those larger energy offenders.
BEMS is already a powerful tool in optimising energy use. When the benefits of analytics are introduced, we have seen additional operational savings of 15 to 20% achieved. Productivity and improved maintenance planning would add to these efficiencies.
Another significant advantage of using analytics software is an informed BEMS maintenance contract based upon the individual requirement, not simply man days. Maintenance needs are flagged by the analytics software, resulting in savings. An intelligent targeted approach to maintenance, based on need rather than routine, is much more efficient.
These features are proving to be very attractive. Following the introduction of my company’s analytics service this year, we’ve seen significant interest. Working in partnership with our customers, we install the systems and monitor them from our technical support centre. Many events identified through the analytics software can be solved remotely by our trained technicians, saving time and money. Where an issue does require a technician to attend site, the data provided by analytics allows efficient use of this resource.
Analytics can be installed into a new construction or by retrofit to an existing building, and can be used with most BEMS. The benefits of a sophisticated data-based approach to building energy management are so many that we predict the users will adopt the technology quickly. Big data for buildings is most definitely here.
Andrew Dyke is technical director of building energy management specialist ABEC.
