October 2014

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Pushing the Envelope

Building Analytics beyond HVAC
Jim Sinopoli
Jim Sinopoli PE, RCDD, LEED AP

Managing Principal,
Smart Buildings LLC

Contributing Editor

AutomatedBuildings.com is extremely pleased that our online magazine provided quality articles like Jim’s that became chapters in this powerful book.

We also applaud Barney and Mike efforts to capture these new industry thoughts in print as quickly as they have. Great job guys!

This article is Chapter 24 in Barney Capehart’s book “Automated Diagnostics and Analytics for Buildings” by Barney Capehart and Michael Brambley, ISBN 0-88173-732-1, Fairmont Press.(For more information read this month's book review.)

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Pushing the Envelope - Building Analytics beyond HVAC

Over the recent past, the best use of an analytic software application for building systems has been fault detection and diagnostics (FDD) specific to HVAC systems. There is research and a number of case studies with verified results showing analytic software reduces energy consumption, improves the efficiency and effectiveness of building operation, and reduces building OPEX. Once used, FDD becomes a core operational tool for many facility managers.

Despite the impressive progress with FDD, the industry is in its infancy of utilizing data analytic applications in buildings. If analytics for the HVAC system has provided outstanding outcomes, we need to take that template to other building systems.

Analytic applications are based on “rules” of how the system should optimally operate, generally obtained from the original design documents and monitoring key data points in near real-time.  Essentially you compare the real-time data with the rules and if the data adheres to the rule, the system is fine; if not, the system is not running optimally and has a fault. For those systems that are not process based, applying analytics generally uses statistical monitoring of key performance indicators (KPIs) to monitor outliers. This may not provide the diagnosis of an issue, but it can identify faulty equipment for preventative maintenance.

To get a glimpse into the possibilities  and generate ideas, we asked  innovative, leading building analytic experts to contribute examples that would illustrate how other building systems can benefit from analytics. Here are their contributions.

To read the complete March 2014 article

Also included in Chapter 24 is the following from Jim Sinopoli:

The Road to Smarter Buildings: Moving to a Much Higher Level of Automation

Propelled by growing energy concerns and technology advancements the building industry has made several strides in building controls and automation.  However, despite the progress, we’re not even close to the potential of fully deploying automation in our buildings. More automation, much more than anything currently deployed, is not only possible but would provide the performance we seek and need in our buildings. At the same time automation can support facility management personnel who are challenged with progressively more complex building systems and the constantly changing skills sets and knowledge required to operate them.
An example of where we are at and where we need to go would be the software application such as fault detection and diagnostics (FDD).  This is really a cutting edge tool for buildings today and probably the most effective building analytic application on the market. In spite of that it’s only “half a loaf”. What if we had an application that not only could automatically detect faults but also automatically corrects the faults? Total automation. You could consider it something similar to an “autopilot”.

If an airplane can flight eight miles above the earth on “autopilot” why can’t a building on the ground do so? The answer is that not only can buildings have “autopilots” but they should. The origin of autopilots for airplanes is interesting and possibly instructive for buildings. The first “autopilot” instrument was invented about 100 years ago, just a few years after the first airplanes got off the ground. In the initial demonstration of his invention, a gyroscope-equipped stabilizer, the inventor Lawrence Sperry and his mechanic climbed out of the airplane’s cockpit and onto the wings, as the autopilot immediately took over and corrected the attitudinal change of the wings. Imagine the tremendous mettle and confidence of those men to sit out on the wings of the plane in flight to demonstrate Sperry’s invention.
Buildings are not airplanes but the traits of the aviation inventor, boldness, innovation and vision will be needed to increase automation in our buildings. The roadmap to advanced automated buildings involves several key issues for industry and building designers, contractors, managers and owners to address:

•    Granular Data – Building-wide or system-wide data will not be sufficient for a highly automated building. The metrics are too broad and vague. To really manage a building we need to get down to the details. The spaces within most buildings are too different regarding their orientation, use, occupancy, needs, etc. Granular data provides for more precision in properly managing specific spaces within a building, potentially resulting in squeezing out the smallest amount of excess energy consumption and improving occupant satisfaction. Going “granular” will mean more sensors, tailored controls for individual spaces and a bit more investment.

•    Detailed Policies and Logic – For a building to be fully automated it will require the “logic” or the “policies” of the automation be fully developed. These are pre-determined rules using an array of data sources and data. The building senses real time conditions and then automatically responds or adjusts, much like Sperry’s gyroscope stabilizer.

The development of this logic will not necessarily be easy; as buildings become increasingly complex the decisions regarding their performance become more complex as there are many more variables in the decision making process. Defining the logic or policies will take extensive planning which is sometimes a pitfall of typical facility management; an example being a dearth of detailed written alarm management plans, reflecting the lack of planning and forethought. The policies will need to touch on every significant building situation or scenario affecting energy, operational costs, life safety and tenant comfort. Planning will involve diverse groups within the building’s ownership and management. This is really an extensive exercise to develop the brains of the automation systems and in the process, decide exactly how the building should adapt to changes and how it should perform.

Much of the data used as the basis for “policies” will be near real-time data from the building systems however critical data and system-to-system communications are needed with the facility management systems, business systems, the utility grid and other external systems, such as weather or energy markets. A highly automated building will require numerous policies, control logic and sequences of operations taking into account a great number of variables. 

A major development in preparing policies and logic will be the evolution of facility management from a rather reactive to an assertive proactive orientation and operation. Yes, things break, alarms and emergencies happen and FM will always react to those events, but FM must embrace planning and become more proactive.
•    Data Analytics – If you are buying books or music from an internet site it’s likely that the company analyzes your purchases, creates a profile of what type of books or music, authors or performers you like and then sends you email regarding other books or music they think you may be interested in purchasing. This is an example of an industry sector “mining data” to improve their business performance. Generally facility management has not traditionally used these techniques. We’ve focused on analyzing energy consumption data and have analytic tools to optimize HVAC but there’s a lot more data out there to be generated and analyzed.

A critical component in building automation is data, because it’s the data that will be the foundation for the development and revisions to the logic or policies of the automation.  Call it data mining, business intelligence or predictive analytics; it comes down to analyzing the building data, finding trends in how the building is performing or being used,  inferring relationships between variables and creating rules; then using that information to predicted how the building perform under different scenarios. This progression is likely to bring new perspectives to the building operation and new ideas for how to operate the building. Finally, the need for data analysis is one rationale for more integrated building management systems which can provide for a unified database of building system data and facilitate the integration to many other data sources.

•    Vast Amounts of Sensors - Highly automated buildings will need many additional sensors and metering; some for energy systems (plug load, lighting, HVAC), others for air quality, building occupancy, external lighting conditions, water consumption, security, etc.  A key building metric is occupancy and it may be the most challenging building metric to obtain. It’s not because there is no technical solution to measure or sense occupancy because in fact, a number of solutions exist, each with advantages and disadvantages.  Most lighting control systems incorporate an occupancy sensor into their systems; some can even track the path the occupant is taking, others use the lighting control occupancy sensor for control of the plug load within the room or space. However, occupancy sensors attached to lighting control systems alone may not be enough.

Video cameras, access control systems, infrared sensors on door frames, RFID tags, monitoring whether the spaces’ IT equipment is on, etc. are all ways to also determine occupancy. Some systems are able to not only sense occupancy but count people. Each building owner will have to sort through options on the market for the best solution for their building.

•    Understanding the Larger Context of ICT –We can’t be constructing highly automated buildings in isolation. All around us is a society and world where people are connected in oftentimes a pervasive and hyperactive manner to other people and objects. Everyone occupying, managing and owning buildings is part of this community. In addition, we also have concepts such as the “Internet of Things” and “ambient intelligence” on the horizon, indicating the trends of technology and connectivity will not only continue to evolve but most likely accelerate.

contemporary We’ve seen the relentless penetration of IT into the “traditional” building control model. We expect information and communication technology will play a very large role in increasing and improving building automation.  Sometimes IT and FM organizations seem like two sides of the same coin, both involved with networks and systems, albeit different systems. Within each company or organization it will require greater accommodations and a stronger relationship between IT and FM to facilitate increased automation; possibly organizing both under a System Engineering banner.

This level of building automation is not illusory. You see the first steps of heightened automation in smaller and medium size companies creating new BMS platforms that will be required for this level of automation and new analytic tools such as fault detection and diagnostics. You also see it in ICT companies increased interest in buildings, energy and analytics. Enhanced automation is a device to eventually get to the nirvana of minimal energy consumption and improved performance of buildings and it’s achievable without any of us sitting out on the wings of a plane in flight to do so.


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