In response to federal inaction on policies to address climate change, city governments have begun to aggressively take up the mantle. In few places has this been embodied more than in New York City by Mayor Bill de Blasio’s administration. Last Thursday, the mayor outlined his plan to require thousands of buildings to comply with new energy-efficiency targets by 2030, or face stiff penalties.
The legislation would set maximum levels of energy that a building could use. For instance, market rate apartment buildings would be permitted to use 50,000 B.T.U.s of fossil fuel per square foot per year. Today, an average apartment building uses from 65,000 to 70,000, according to Michael Shaikh, a spokesman for the mayor’s office. Such buildings would need to reduce their energy consumption by about 25 percent.
The plan still needs to be approved by the City Council, and will likely face pushback from the Real Estate Board of New York and others. But regardless of what happens with this particular initiative, the trend is clear. In the absence of broad, market-driven policy at the federal level, real estate organizations will likely be forced to adhere to top-down regulation from state and local governments.
Instead of doing the bare minimum to avoid penalties, owners and operators can get ahead of the trend and make improvements on their own terms. While the focus of regulations will continue to be on energy efficiency, commercial real estate companies should take on a holistic effort to improve all aspects of building operations.
Unfortunately, in an effort to understand their options, most owners and operators are overwhelmed by a glut of information and misconceptions. Terms like cloud-based energy management technology, smart buildings, connected cities, etc. do not translate well to those on the ground in real estate companies.
However, amid the confusion lies a truth: the right technology does, in fact, deliver lower operating expenses, and can make compliance with regulations achievable even in the oldest buildings.
What this really looks like is a suite of software applications that utilize building data from a variety of sources to help operators better understand and manage building performance.
For lack of a better term, we’ll call it an operations performance system (OPS).
An OPS continuously commissions of every condition in a building, from critical equipment systems such as boilers and chillers, to environmental conditions such as indoor air quality, floods and leaks. This complementary blend of broad sources and granular data points enables full transparency into operations as they happen, something that is lacking in most commercial real estate, but absolutely necessary for maximum efficiency.
Here are 12 ways in which an operations performance system can help landlords get ahead of energy efficiency regulations (and much more) once and for all.
Looking at building-level data as a strategy is akin to diagnosing cancer by listening to a stethoscope. Like human bodies, buildings are complex and interconnected. Decisions made on one system often affect other systems elsewhere in a building.
In terms of driving consistent savings in energy consumption, even interval data would not suffice if it is only at the building level. Say there’s a spike in energy and the building operators have building-level energy data in front of them. Where are they supposed to start? They will have to rely on best guesses as to which system is the culprit, often blaming usual suspects such as HVAC or lighting. However, this lack of insight leads to abdication of responsibility because lighting and HVAC are necessary for tenant comfort, they cannot be turned off at will.
An OPS utilizes real-time energy data at the equipment level. So, in the scenario above, building operators can see consumption more holistically, view which loads contribute to the whole, and decide which systems can be shifted to different times without affecting tenant comfort.
In most portfolios, building maintenance is not optimal for a variety of reasons: Either systems are over aggressively reviewed leading to wasted time and effort or systems are maintained only in response to failure, at which point there is potential negative impact to tenants. Neither of these options are ideal.
Maintenance and repairs cost nearly as much per square foot as does energy costs. By being reactive to regulations and only focusing on energy savings, building operators are missing half of the equation. In addition to energy savings, an OPS can help transition a property to condition-based maintenance. This means that, because equipment systems are being tracked in real-time, maintenance can be performed only when conditions fall below certain performance thresholds or failure is imminent.
Unlike energy costs, which are well documented, there is no reliable data on the amount of waste in maintenance in commercial real estate. However, in manufacturing, audits have found that preventative maintenance activities were wasting 25% of every dollar spent. It’s not hard to imagine that the ratio is even higher in commercial real estate. Streamlining maintenance based on conditions, instead of schedules, can reduce this waste and deliver OpEx savings outside of energy costs at little to no additional cost.
Affordable sensors, remotely transmitting information via the Internet of Things (IoT) can produce huge amounts of data related to building operations. Combined, the data that streams from a well thought out IoT rollout can facilitate a comprehensive view of building operations and tenant comfort.
More data leads to more insights and better conclusions, improving operations without needing to replace entire systems. For example, real-time data around the temperatures in individual tenant spaces can drive better decision making around equipment runtimes. In addition, when it comes to make a full replacement, equipment sizing decisions can be accurately made based on capacity and load needs.
Every building has unique controls, unique configurations, and unique data. Only a few rules can come out of the box and apply to every building, every climate, every situation.
Hundreds of data streams, collected in real time, cannot possibly be analyzed by humans. As data are collected, machine learning can learn the unique characteristics of a building as well as make comparisons against aggregated data to continuously deliver insights.
There is a lot of talk about artificial intelligence in real estate. While general intelligence (machines being able to make decisions completely independently) is still far off, machine learning focuses on teaching computers to make and improve predictions based on the data available without being explicitly programmed. When applied to real estate operations, machine learning produces the ability to interpret and react to data that has never been seen before, which is a core requirement for processing vast amounts of data from equipment that is similar, but not identical.
As IoT solutions collect more data around operations and tenant comfort for building monitoring systems, machine learning will be able to predict equipment failures before they happen more accurately and find deeper efficiencies than could be determined purely by human analysis.
Most of today’s building management systems are designed specifically to control the building’s systems; not as tools to analyze and trend data. Often, because not all data are available and because of a building’s preexisting conditions, engineers using a BMS to deliver energy savings will have to rely on imperfect data to arrive at solutions.
A comprehensive energy efficiency strategy can be implemented with or without a building management system. If there is already a BMS in place, an OPS can be used to determine if the complex set of controls originally programmed after installation is optimized to the occupancy rates of the building. If there is no BMS in place, operators can use an OPS to manually set equipment schedules with precision.
Not all energy saving techniques require reducing overall consumption. In many utility service areas, commercial properties are charged based on the consumption of the 15-minute interval at any point during a billing period.
As mentioned earlier, building operators can’t do anything about some of the major contributors to peak demand, such as HVAC and lighting. However, by continuously commissioning the energy consumption of every equipment system, building operators can start “peak demand shaving,” to find opportunities to reduce peak demand, and extrapolate those savings across the entire billing period.
As regulations get more sophisticated, there is likely going to be more weight put on time of use (TOU), instead of overall consumption. Owners and operators that have already implemented processes for peak demand usage will be able to comply with future TOU regulations with very little additional effort.
Optimization strategies can work well on their own, but buildings need to combine those strategies with fault detection and diagnostics. Even the best operations strategy and equipment schedules are at risk of being thrown off by human error.
Every operator can relate to a situation in which a schedule was changed to perform maintenance, and then accidentally never switched back, wasting energy and money. Sometimes, inefficiencies can be as simple as a vendor working in the mechanical room accidentally bumping the on/off switch on another system.
It’s naïve to think that these situations can be avoided completely. Buildings that implement an OPS and operators that are notified of anomalies as they happen will make sure that operational expense reduction initiatives are not sabotaged by human error.
Even the best software applications need teams on the ground to act on the insights. Many operators fear technology from their experience with building management systems, which require assembling building engineers, controls contractors, mechanical contractors, and others to be useful. Needing a range of subject matter experts to review and analyze mined data should not be required to maximize operational efficiency.
Instead, an OPS can serve as an effective communicator between the various groups involved in buildings operations. As portfolios have become more focused on sustainability, the energy savings team and traditional operations and maintenance staff have become siloed. Through data and insights (that don’t require a PHD in engineering to understand), both sides of operational performance can be brought closer together.
Within a portfolio, the executives in charge of operations oversee building managers with a range of experience and talent. An OPS creates an effective way to spread the best practices of experienced building managers to the rest of the team. When the effects of certain actions or strategies can be visualized with data and shared among the team, the training process can be sped up dramatically.
Even experienced operators have an opportunity improve their performance by using an OPS, the data sets and real-time fault notifications will require some training and process changes. But the investment in moving away from reactive break/fix scenarios to proactive fault detection and predictive maintenance is minor compared to the productivity gains.
Most CRE organizations don’t have the data or software to view their buildings side by side. One of the most persistent challenges for companies dedicated to improving operations is allocation of staff and resources effectively.
There are often so many emergency repairs that operations managers have little time to act strategically. Without a way to view the aggregate data of issues that have arisen across different buildings, it can be difficult to establish effective and reliable response processes.
Because data streams are cloud-connected and based on open protocols, the data generated for an OPS are not “trapped” in each building. This means that software can benchmark each building in a portfolio in one view to help operators determine the true needs and capabilities of their assets.
An OPS can provide persistent performance improvements and operational savings, but without commitment to execute on the insights, it’s not going to deliver all the results building owners want, need, and demand.
A comprehensive commissioning strategy is only effective when combined with a commitment to excellence. With great power, comes great responsibility.
Enertiv's Asset Intelligence tool utilizes all of these techniques to deliver consistent insights and drive improved operations performance. Schedule a demo today to see how it works!