Data-driven HVAC: advances will change the landscape, and optimization is at the forefront

Given that, in the enterprise world, data-driven anything (and everything) can easily be passed off as “the next big thing,” it’s no surprise that the headline can be applied to the HVAC industry! But humor aside, it’s true, and the trend is real. In an online, increasingly Internet of Things (IoT) compliant landscape where almost every component in the value chain generates data, it’s little wonder that data-driven HVAC has been identified as one of the most significant trends in the industry.

What’s happening now is a sea-change because, historically, optimizing and modeling approaches in HVAC have been physically driven activities without the availability of reliable or extensive data sets or the means to leverage them. But the status quo is changing rapidly, and it’s worth spending a few minutes looking over the horizon to understand the basics of how the industry is evolving towards a far more effective, data-driven HVAC model.

Why the evolution of data-driven HVAC matters

For a start, why bother? What’s the incentive for change? Well, the energy efficiency of Heating, Ventilation, and Air Conditioning (HVAC) systems is crucial to reducing buildings’ energy costs and carbon footprints, and we’re all aware (a cursory glance at recently announced tax credits and incentives in the USA underlines it) that those goals matter. Data-driven HVAC has the potential to dramatically hasten progress towards meeting them.

How and why is this case, and why now? Well, we can think of HVAC systems as complex, large-scale entities that intrinsically have lag times and high thermal inertia when left to perform untouched. So, the need to optimize them is inarguable. However, that happens (maximally data-driven or not), they’re natural candidates for optimization.

The past and the future

Physically driven methods of optimization have long been used to model, control, and improve system performance, and they, too, have been data-driven. There’s nothing new in that. But their computational powers have been limited, even if they’ve demonstrated their effectiveness in fine-tuning HVAC operations.

What’s changing now is that we now have the right Information Technology (IT) tools, which hold significant potential to impact HVAC optimization for the better. Hardware costs are decreasing, data is becoming more accessible, and new technologies have made collecting and storing vast amounts of high-quality building-related data possible. Today a myriad of newly deployed sensors related to the proliferation of the IoT are collecting and making critical information available in real-time. Communications networks have evolved to make this possible. Better still, we can now process these large data sets to discover insights, trends, patterns – and anomalies.

All these factors (and others) mean that it’s become possible to create far more accurate and robust data-driven approaches to optimization than we’ve ever seen before, which can logically be applied to HVAC applications.

What might happen next?

How might the next generation of data-driven HVAC manifest itself? What might happen next? While there’s an aspect of “crystal ball” gazing to looking ahead and making predictions, the reality is that new tools are fast taking shape. Let’s briefly look at five potentially impactful areas:

1. Tools combining energy, location, and weather data related to buildings but not requiring complex simulations or labor-intensive data collection are emerging. These can provide a fast channel for more effective HVAC optimization.

2. New, data-driven approaches to quantifying savings opportunities by identifying efficiency problems (and solutions) and providing continuous monitoring are starting to appear.

3. New computational algorithms are being developed to identify key building characteristics, which then employ predictive models and use machine learning functions with the potential to fine-tune HVAC system performance.

4. Data-driven approaches for quantifying HVAC consumption savings are emerging. These involve algorithms for baseload reduction and HVAC rescheduling, and they expose the critical parameters and characteristics that determine the amount of potential savings that might be achieved.

5. Advances in data will likely impact the thermostat setpoint and increase the potential savings of a setpoint setback.

Of course, the above gives just a flavor of the industry’s direction of travel. However, HVAC is evolving in ways that only serve to underline just what a vital function optimization has become and how it’s set to become even more mission-critical in future. You might not think these trends affect you now, but ignore them at your peril, particularly if you’re not taking HVAC optimization seriously enough already.

Optimize with NexRev

At NexRev, we’ve been unlocking the power of facility and energy management data with over a million connected devices across North America. Our team of experts are focused on helping you deliver more with your budgets, infrastructure, and assets to create sustainable savings in operations and energy, reducing your risk and increasing operational confidence.

If you’re interested in learning more about our solutions can help your enterprise reduce energy costs, please send an email to: This email address is being protected from spambots. You need JavaScript enabled to view it.