Ask a Modeler: Are There Strategies to Save Cost and Energy by Changing the way HVAC Load is Calculated?
HVAC units are often oversized to deal with full load, which rarely occurs. Are there strategies to save cost and energy by changing the way load is calculated?
-Mr Right Size
Dear Right Size,
Rejoice, as gone are the days of boasting about the biggest kit in town. Now is the time of the kit that is just the right size to do the right job right.
It’s obvious: good engineering strives for a working solution with ever higher efficiency by designing out waste. Coincidentally, not paying for waste also tends to make things cheaper. Great, but what’s the right size then, I hear you ask, and this is indeed where things get murky.
Pressure to Go Big
Historically (and cynically), the “right size” for an HVAC unit has been the one that fits the budget whilst promising the fewest complaints in use. After all, aren’t the HVAC services there simply to keep the building users happy? With enough money in the project purse, the path of least resistance (and lowest professional liability) leads to size-inflation, with an uncertainty here, a margin there, and a few conservative estimates both here and there. The resulting race to the top remains unchecked as most building owners with limited technical competence can only pick a value engineered option and rarely a smaller capacity. Lack of complaints in operation remains their only measure for success, and the easiest way to avoid complaints is to secure plenty of spare capacity to deal with all eventualities, real or imaginary. This preemptive risk aversion can also be cheaper in the long run, if the alternative is a costly retrofit.
Nevertheless, things start to look different as the priorities of the building industry shift. In addition to picking the largest just-affordable HVAC units, we now also need to reduce their energy cost and environmental footprint. Today we can estimate these impacts with increasing confidence. We know that most oversized units are not only expensive to install, but also expensive to run as their efficiency drops with declining utilisation. While some equipment use the same amount of energy regardless of their duty, others use even more energy if they do much less work than they are sized to do. Even so, risk aversion continues to trump over such considerations. Despite increasing energy prices, and because carbon is too damn cheap, the perceived value of high efficiency pales in comparison to the risk of affecting building users’ happiness (and productivity). As a result, oversizing remains common practice.
To complicate things further, there are also instances when oversized is the right size even after the energy, cost and environmental considerations. Certain HVAC equipment can reward operation at a reasonable part-load with higher performance, while also affording greater flexibility (for example when a pandemic requires higher ventilation rates). In such cases, looking at the whole life footprint of the HVAC systems becomes necessary, which might justify a large size as the best value option for optimal life-cycle performance.
What do we do then? At a minimum, we need to combine the emerging data from the newest generation of hyper-connected buildings with the expanding capabilities of the contemporary design tools to drive diversity, flexibility, storage and whole-life considerations in HVAC sizing exercises.
Understanding Data and Risk
We need data to tame our risk aversion. Design criteria, for example, need to stand up to scrutiny based on data from buildings in operation. We need to learn lessons from this data to establish sound diversity ranges over design criteria. Without such data, we at least have to address coincidence of loads and the benefit of storage with greater courage to inform load diversity. This makes a robust dynamic energy model a precondition for right sizing.
A sure way to oversize an HVAC system is to design it for infinite flexibility. A speculative development may need an energy intensive server room in an unknown location, and its design must be sufficiently flexible to accommodate this. This, however, does not make the building a data centre with server rooms throughout, and we should not design for such a scenario under the disguise of flexibility. Flexibility allowances should therefore also be checked against the data from the field.
Finding the Balance
We must exploit the benefit of storage to the best extent. Where demand for use is intermittent and the loads are dynamic, well-designed storage systems can deliver miracles to avoid oversizing. This is as applicable to thermal mass in architecture, as it is to buffer vessels in mechanical systems and batteries in electrical systems.
Finally, for true optimization of the system size, we need to look at the full picture. This requires a balance between the upfront, operational and the end-of-life considerations from the perspectives of fitness for purpose, cost and holistic environmental impact. Oversizing may feel like a risk-averse and future-proof strategy, yet is it really so for the 20-year life-cycle of the kit we are installing today?
Decisions informed by data on these aspects are essential to streamline HVAC systems and deliver the right size for the job at hand. Such custom tailoring takes time, diligence and experience as there is rarely an off-the-shelf, one-size-fits-all solution. The alternative is business as usual where size matters and the biggest denominator with the largest safety margin trumps.
Associate Environmental Designer, Atelier Ten
Do you have anything to add or your own answer to contribute? Please share your thoughts by emailing email@example.com; you are an expert too! Do you have your own question for the expert? Submit your question to be considered for a future column. Note that questions requiring an immediate response should be submitted to the community of experts at unmethours.com. If you are interested in replying to a question as a featured expert or have any other feedback about Ask a Modeler please email firstname.lastname@example.org.