Navigant Research Blog

Small and Medium Building Energy Management Remains An Elusive Goal

— November 6, 2013

Intelligent building controls and energy management systems have made dramatic advances in recent years, yet most are aimed at the small fraction (between 2% and 3%) of global commercial buildings with floor space greater than 100,000 SF.  The remaining 98% of commercial buildings, which according to EIA estimates make up nearly 60% of commercial building energy consumption in the U.S, remain almost untouched by energy management technologies or services.  Why are these buildings so difficult to reach?

The characteristics of small-to-medium commercial buildings (SMCBs) are incredibly diverse in use, construction, age, and ownership.  This diversity creates two major obstacles – one technical, the other related to incentives.  First, if even a small amount of energy control system customization is required for each building, the ROI on the technology investments quickly becomes unattractive.  Secondly, many SMCBs are owned by hands-off investors, such as real estate investment trusts (REITs), managed by separate property management firms, and occupied by renters who bear the energy costs without having any control over the associated infrastructure.  Even if the ROI is good, there is no incentive for owners to make the “I” if they will not receive the “R.”

In the Big Boxes

Despite the obstacles, significant opportunities for SMCB energy management continue to emerge, driven by demographic shifts and technology advances.  The advent of national chain and big-box stores has transformed the retail and food service industries in recent years.  While considered a blight by many, the cookie-cutter nature of these buildings, along with aggregated ownership and management of thousands of sites, dramatically reduces the barriers of technical customization and split incentives.  The major controls systems vendors now have focused product and services offerings, gained mostly via acquisitions (such as Honeywell/Novar, Siemens/Site Controls, and Schneider Electric/SCL Elements), specifically addressing the multi-site enterprise market opportunity.  These solutions enable some level of energy awareness as a first step, but are increasingly enabling advanced demand response and other time-of-use based services, as well.

Building By Building

If the key to SMCB success is site aggregation and standardization, how else can these be achieved?  Some pioneering property management firms, such as Jones Lang LaSalle, and design-build-operate-maintain firms such as McKinstry, are offering advanced energy management services within their menu of services.  Utilities offer another point of possible aggregation, motivated to achieve ever-increasing energy-efficiency goals mandated by their regulators.  The key enabling technologies for both property managers and utilities include advanced analytics services that combine utility meter data and external environmental and demographic data to deliver deep energy insights without the need for any onsite technology other than the utility’s meter.  FirstFuel Software, which pioneered this approach, is increasingly targeting SMCBs, even with relatively dumb meters.  Gridium, a relative newcomer, is leveraging the growing base of smart meters to gain insight into per-building energy use.

While these approaches may not support the advanced demand response services enabled by onsite control systems, they could enable SMCBs to profitably participate in utility dynamic pricing programs that achieve many of the same goals.  And solutions providers may find the revenue growth engine they seek.


Energy Efficiency and Demand Response: Friends or Frenemies?

— October 11, 2013

Energy efficiency (EE) and demand response (DR) are usually considered two sides of the same coin to the point that even relatively energy-aware consumers may not understand the differences.  Consumer education on the opportunities and benefits of EE and DR capabilities continues.  At some point, though, EE and DR goals can come into conflict, as more efficient and lower overall energy use generally leads to less load that can be shed during a DR event. As anyone who has parented teenagers will know, navigating such “frenemy” relationships can be a challenge

DR, in its most basic form, offers customers payment for energy non-use during peak periods, or DR events, with the overall aim of reducing demand on the grid as an alternative to adding additional generating capacity. The financial payback can be enticing, as the peak demand being displaced is often the most expensive.  The challenge, of course, is proving a negative – that the energy not used would have been used if some specific action or sacrifice was not made.  The establishment of clear baselines from which demand avoidance can be measured against is a key element of DR programs, and, unsurprisingly, has been a source of abuse and even fraud.  Yet, most DR programs are reliable and effective.

Efficient Is Not Always Better

The broader issues come when energy efficiency improvements permanently lower the baselines and reduce the amount of load that can be shed for a given facility.  For example, a more efficient HVAC system can significantly reduce the average energy consumption of a building, but will also reduce the amount of energy that can be deferred during a DR event.  A similar dilemma may arise within a building energy retrofit itself.  Investments in an advanced lighting control system that automatically controls fixtures based on occupancy or other parameters can offer very quick paybacks with inefficient fixtures.  But, it may have a weaker business case if the fixtures are already very efficient, as may be the case with LEDs.

Commercial building energy managers may ultimately find themselves in the odd position of having a stronger business case for using an inefficient system, which enables lucrative DR program payments, than a more efficient, lower average energy use system.  On a broader scale, such conflicts arose earlier this year regarding proposed new water heater efficiency standards, which would effectively mandate new technologies for larger water heaters (more than 55 gallons) that would be incompatible with long-standing and effective DR programs, leading to opposition from utilities dependent on these programs for grid management.

The Long View

My recent conversations with commercial building operators and energy management solutions suppliers indicate that the potential conflicts between EE and DR goals have not yet surfaced, mostly because there is so much low-hanging fruit available for both types of programs given the poor energy management of most commercial buildings today.

The best advice for building operators and policy makers may be the kind you would give a teenager: Try to keep a longer-term perspective.  Apparently, straightforward either/or decisions, such as choosing between more efficient lighting or better lighting controls, may really be and decisions; best when deployed together and enabling both lower average energy costs and the ability to participate in more advanced DR programs as they emerge.  The longer-term building-to-grid vision of a flexible grid with transactive consumers depends upon it.


Are Your Light Bulbs Hackable?

— September 4, 2013

Just as autumn follows summer, the introduction of new networked devices for smart homes and buildings – embodiments of the Internet of Things (IoT) – are followed by reports of diabolical hacks of these smart devices.  Recent plots have involved hacked toilets and light bulbs, and even columnist/humorist Joe Queenan has warned of hackers replacing your car’s music playlist with “Rod Stewart Chants the Gregorian chant Songbook, Volume 19.”  Personally, I avoided purchasing a Wi-Fi enabled bed this summer, though it had more to do with my wallet than fears of hackers turning my slumber into a chiropractic nightmare.

The public imagination is informed by movies such as 2003’s The Italian Job, where city traffic control and transit systems are hacked from an airport luggage cart, or the security system hacks shown in Ocean’s Eleven.  While these might be dismissed as sensationalized scenes (come on, a stable Wi-Fi signal in an airport baggage claim area?), there are legitimate cases of life imitating art.  So should we fear a world of smart, networked devices?

The recent hoopla over the hack of Philip’s Hue Smart LED light bulbs, which offer efficient and programmable home lighting from your smart phone, is an interesting case.  Apparently the bridge device connecting Hue’s ZigBee-based bulbs to the consumer’s Wi-Fi network was hacked via the Wi-Fi link, yielding control of the lighting system.  Of course, this is a legitimate concern: lighting is critical to safety and security in homes, in commercial buildings, and outdoors.  However, as Philips has noted, the apparent weakness originates in the customer’s Wi-Fi network, not the Hue’s control network.  It doesn’t take much wardriving to understand how many unsecured home Wi-Fi networks exist.  There are likely more high-value hacker targets in these homes (bank records, user passwords, etc.) than the lighting system, but clearly consumer education on proper Wi-Fi security and how this might ultimately impact physical security seems a prudent first line of defense.

The larger issue is that the risks posed by not understanding how security of the underlying network for ‘things’ influences physical security goes well beyond smart bulbs for the home.  Commercial building control systems and smart city systems (lighting, parking, traffic control, etc.) are increasingly based on standard networking technologies.  I recently toured a state-of-the-art smart building where the facility manager was very knowledgeable and justifiably proud of the building’s systems and energy performance.  However, when asked to show us the control network components (such as Ethernet switches, etc.), we received a blank stare.  He not only didn’t know where the network was located but didn’t really understand that it even existed, seeing it as just part of “the Honeywell system” that was installed.   On one hand, this level of transparency indicates good reliability (I wish my home Wi-Fi network was this transparent), but you can’t secure something you don’t know exists.  And this “invisible” network likely was handling all of the climate, lighting, security, access, elevators, and other systems in the building, making life easier for would-be hackers.Slowly awakening to these concerns, the building controls vendor community will need to find ways of engaging the hacker community, following the lead of IT technology suppliers.  Interestingly, there is a growing hacker community for Philip’s Hue system, driven less by malicious intent and more by wanting to do cool things.  Security concerns aside, this is a marketer’s dream come true. 

While it may be fun to joke about the consequences of hacked light bulbs, toilets, and beds, the reality is the Internet of Things, as embodied in smart buildings, cities, and homes, increasingly needs to be viewed as part of the critical infrastructure begging for greater cyber-security awareness – as my colleague, Bob Lockhart, has been writing about for years.


The Fog of Big Data

— August 14, 2013

Big Data and the analytics to extract useful information from it have great potential for smart buildings technology.  As these terms are used more broadly, though, they risk losing their original meanings.  For many people, Big Data means “a lot of data” and analytics is diluted to mean “processing a lot of data.”  These general usages risk blurring the real opportunities afforded by Big Data and analytics in the smart buildings sector.

This was reinforced at two June vendor conferences I participated in: Realcomm’s IBcon conference in Orlando and Schneider Electric’s Xperience Efficiency event in Washington D.C.  Schneider marketing director Kent Evan’s trends presentation at Xperience Efficiency cited the early definition of big data, as described by META Group (now Gartner) analyst Doug Laney in a 2001 research report.  That is, Big Data has three attributes: volume, velocity, and variety.  But Evans reminded the audience that not every data problem in buildings is a Big Data problem – there’s plenty of work we need to do to make better use of the small data we have available to us.

Faster, Faster

While I generally agree with this assessment, it is still worth reviewing how smart building data volume, velocity, and variety are challenging traditional building management systems.  Certainly, data volume is growing as building control systems with hundreds of control points morph into complex systems with many thousands of points, driven by more granular sensors and controls. The velocity of this data is also increasing as sensors are sampled more frequently and denser submetering deployments provide more information to systems operations.  The variety of the data is growing as well, especially as different systems – ranging from HVAC to lighting to security (including video) – become data sources for an increasing range of potential applications.  Building data may not suffer from as many structured versus unstructured data challenges as experienced in other industries, but existing applications are often straining to process this data.  More importantly, new types of processing offer new insights and control optimizations.

This processing issue gets to the second part of my concern about the imprecision of the term “analytics.”  There were dozens of software vendors at the IBcon conference hawking buildings analytics packages, and on the surface, the marketing messages blur the distinction between them.  At the risk of oversimplification, these packages can be sorted into two buckets: those that use complex rules to effectively sort through lots of data to discover the desired information, and those that algorithmically fuse disparate data sets together to infer new actionable information and insights.  Products in both buckets can perform impressive and useful tasks, but the latter is the class of applications that are best described as true analytics.

Perhaps the best advice for building operators trying to sort through the Big Data and analytics hype is to focus on the specific problems at hand and understand how the proposed solutions offered arrive at their answers.  Whether they involve Big Data or little data, analytics or advanced rules engines, solving problems is the ultimate goal.


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