Data Driven Design – Retrofitting for a Low Carbon Future How we design and size equipment needs a modern approach as we retrofit with low carbon heating systems. All of that BAS data you’ve been archiving can help.

Brad White P.Eng, MASc President, SES Consulting Inc. Contributing Editor

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The era of real action on climate change may finally be upon us! Last month’s climate change summit saw ambitious new targets for reduced greenhouse gas emissions being announced for many countries, including Canada and the US.  Many nations are aiming for reductions on the order of 40%-50% by 2030.  With the building sector representing around a third of total emissions, the next decade is set to see a flurry of activity and investment directed at buildings to help achieve these targets.

A major focus of national climate plans is a push to dramatically reduce the carbon intensity of our electrical grids. Case in point, decarbonizing the electricity grid is a major focus of the White House’s recently announced $2 trillion infrastructure plan. As a result of all of this, commercial buildings will be increasingly pushed towards replacing fossil fuel heating systems with electrified alternatives. Wherever possible, this will mean the adoption of heat pumps as the most cost-effective use of electricity for heating. 

With that context in mind, let’s consider how we normally go about sizing heating equipment for retrofits. More often than not, the approach will be: Like for Like, rule of thumb, or “experience”. A step up in accuracy might be to reference a handbook. Better yet might be a proper load calculation or even a building model, if you’re lucky. All of these approaches, some more so than others, have a major flaw in that they rely on a lot of assumptions about how a building is working. On top of that, even a good engineer following best practices will face pressure to have generous safety margins. Why? No one wants to undersize a heating system and the headaches that creates, so oversized systems are a nice piece of insurance. Especially when the building owner is the one paying for it. Besides, more BTUs from gas or oil fired boilers are pretty cheap, so no one gets too worked up about the extra cost anyway.

Switching to heat pumps shakes up that paradigm in a big way. Below are rough costs pulled from our project database for standard and high efficiency boilers along with air to water heat pumps.

Obviously these $ values will vary somewhat location to location, but the overall trend is very clear: heat pumps cost a LOT more than boilers. Also keep in mind this is just for the equipment itself, add in the more complex installs, possible electrical and structural upgrades, and the disparity can be even greater. Suddenly, an oversized heating plant isn’t costing you $10,000 extra, it’s $100,000 or more.

But what is the best way to size our equipment? Do the usual approaches even work well? Consider the results of a study we did for a local university (pre-COVID) who were looking for low carbon options for their domestic hot water systems. For one of their buildings, we came up with the following results:

The last 2 values are based on data we extracted from a gas sub-meter connected to the BAS. As you can see, the actual building DHW load is much less than what conventional sizing approaches would say you need. We routinely see the same results for heating systems. This histogram shows the frequency that this boiler plant was operating at different loadings. Significantly, the data showed that the plant never got over about 25% loading.

Having data from gas, water and BTU meters is great if you have them. But if you don’t (and most don’t), most of this data can be pulled out of a typical BAS, either directly or through constructing a virtual energy meter. If you have supply and return water temperature sensors, you’re most of the way there already for most boiler plants. Data quality is obviously important here, you want to make sure that your sensors are calibrated! Water or air balancing on key systems might also be a good idea if it’s been a while.

Unless you’re prepared to be very patient, here’s where it really pays to have archived data handy. Data that has probably been sitting there, just waiting for someone to come along and find a use for it.  Ideally, you want to be able to look back over a full heating season or more, or at least make sure you’ve got the full range of typical weather conditions covered. I’d also recommend cross checking this data against another data source as a quality assurance check, even monthly gas bills will do.

With this data in hand, we can confidently move forward designing and optimizing equipment size against overall energy use. For example, we’re finding that in a Pacific Northwest climate, 80% or more of the heating load occurs when the outside temperature is above freezing. Sizing heat pump equipment to the load at the minimum design temp isn’t cost effective, so our heat pumps are usually sized to handle the loads that cover 80% of the heating energy, relying on cheap BTUs from the boilers for those infrequent peak loads. This kind of load matching with hybrid heating sources is a big departure from how the industry has approached equipment retrofits in the past, but I expect it to become the norm as we look for ways to significantly cut the GHG emissions from our buildings.

Of course, you can go even deeper into the data. You might decide to analyse your reheat valves and discover that 25% of your spaces represent 80% of your heating demand (based on a true story). In a case like this, zone level retrofits with VRF or split heat systems can be a more cost-effective way to reduce GHGs than trying to retrofit the central plant.

It’s time to leave the 1950s when it comes to how we approach mechanical retrofits. The push to retrofit buildings with very costly low carbon heating systems over the next decade conveniently comes at a time when our buildings are producing more data than ever before. Let’s put that data to good use by optimizing how we design these new, climate friendly, mechanical systems for our existing buildings.