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ASHRAE Journal Podcast Episode 11

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Left, Andy Pearson; Julie Godefroy; Hywel Davies

Encouraging Energy Use Efficiency: From Cold Stores to Office Buildings

Because energy costs have risen since the 1990s, there’s a greater willingness today to share information about energy efficiency, said Andy Pearson, Ph.D., C.Eng., Fellow ASHRAE. Join Pearson, Julie Godefroy, Ph.D., C.Eng., and Hywel Davies, Ph.D., Member ASHRAE, as they identify how careful measurements and management of energy in cold stores and office buildings can result in significant benefits for stakeholders.

Interested in reaching the global HVACR engineering leaders with one program? Contact Greg Martin at 01 678-539-1174 | gmartin@ashrae.org.

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  • Guest Bios

    Andy Pearson, Ph.D., C.Eng., Fellow ASHRAE, is Group Managing Director at the industrial refrigeration contractor Star Refrigeration, headquartered in Glasgow, Scotland. He is a professional engineer with 35 years of experience in the refrigeration business. Through his father and grandfather, he has family connections to the industry going back to 1936. He is a regular contributor to ASHRAE Journal, having written a monthly column on refrigeration topics for more than ten years.

    Julie Godefroy, Ph.D., C.Eng., works as Head of Sustainability for CIBSE where she leads work on climate action, focusing on topics such as energy efficiency, low carbon heating and building performance. She also works as an independent sustainability consultant with projects including overheating in retrofit homes and building performance evaluation. 

    Hywel Davies, Ph.D., Member ASHRAE, is Technical Director of CIBSE, the Chartered Institution of Building Services Engineers, the UK based professional body for building engineering services. He was closely involved in the development of the CIBSE guidance on ventilation measures to reduce the risks of COVID-19 transmission. Hywel leads the technical and policy development work of the Institution with a particular focus on building regulations and building safety reforms. He currently chairs the Building Regulations Advisory Committee in England.

  • Show Notes

    Because energy costs have risen since the 1990s, there’s a greater willingness today to share information about energy efficiency, said Andy Pearson, Ph.D., C.Eng., Fellow ASHRAE. Join Pearson, Julie Godefroy, Ph.D., C.Eng., and Hywel Davies, Ph.D., Member ASHRAE, as they identify how careful measurements and management of energy in cold stores and office buildings can result in significant benefits for stakeholders.

  • Transcription

    ASHRAE Journal:

    ASHRAE Journal presents.

    Hywel Davies:

    Getting people to pay more attention to energy has been a challenge for a long time. It's really unfortunate because at the most basic level, just keeping an eye on how much a business is spending on energy and then looking to manage it, and are we doing a bit better than we were a week ago or two weeks ago? Are there simple things that we could be doing to improve our energy performance? What effect is that happening? Can we see it coming through in the figures? They're not hugely difficult things to do, but I think we've really struggled to motivate.

    ASHRAE Journal:

    Episode eleven: Dr. Andy Pearson, Dr. Julie Godefroy and Dr. Hywel Davies identify how careful measurement and management of energy use in cold store and office buildings can result in significant benefits for stakeholders. They also discuss the hurdles and barriers encountered in motivating building operators to improve energy efficiency.

    Andy Pearson:

    Hello. I'm Andy Pearson. I'm the Group Managing Director at Star Refrigeration, a contractor based in Glasgow, in Scotland. I'm a chartered engineer, but possibly best known to readers of the ASHRAE Journal as the author of a monthly column on refrigeration applications. I've been doing that since 2012, when I was serving as a member of ASHRAE's refrigeration committee. And at one of the committee meetings, they asked for volunteers to contribute a monthly column. So I stepped forward and said, "Yeah, I'll give it a try if someone else is willing to step in and do the next one after that." That was 10 years ago, and I've just submitted my 121st column. I'm still waiting for the other guys to turn up. But one of these days, perhaps they'll find me out and I'll be taken off the case.

    Hywel Davies:

    I'm Hywel Davies. I'm the Technical Director of CIBSE, which is the Chartered Institution of Building Services Engineers. We're the UK-based professional body for building services, which is pretty much anything that uses energy in a building. And I've been with CIBSE for nearly 25 years now. My background is as a building scientist and as a chemist, and I started my life in what was then the government's National Research Lab. I'm also heavily involved in the development of British Standards, through our equivalent of ANSI. And I chair the Building Code Committee for England.

    Julie Godefroy:

    And I'm Julie Godefroy, also at CIBSE, where I'm head of Sustainability. My background is a chartered engineer. And at CIBSE, I lead on climate action. That includes strategic things such as net-zero definitions and quite broad ranging guidance, as well as much more detailed work on building performance in general. So, energy performance, energy efficiency, comfort, et cetera.

    Andy Pearson:

    We thought it would be good to compare notes about use of energy in buildings, comparing industrial buildings of the kind that I get involved in with the more commercial buildings that Julie and Hywel are looking at more regularly. I've been looking at cold store energy consumption since the 1990s, when the UK's Department of Energy had a sub-department called the Energy Technology Support Unit. And those guys produced a really interesting paper in 1994, which looked at cold store energy efficiency. It was called The Good Practice Guide to Cold Store Efficiency. And they proposed a metric for comparing different cold stores, which was the annual kilowatt hours figure divided by the volume of the store. And they called this “specific energy consumption.” I thought this was a great idea at the time, and tried to get some interest going in having different cold store operators file their figures so that comparisons could be made. We could have a hit parade, if you like, of cold store efficiencies. Absolutely nobody was the least bit interested in this. It took no traction whatsoever. But there was a European study done around about 2010, which looked at cold store efficiency again. And they gathered data from over 700 sites across Europe, which delivered exactly what I'd been thinking about all those years before. And it was presented a conference that I attended in Paris in 2013. They didn't quite go the whole way of calculating specific energy consumption, but they plotted the kilowatt hours per year against the store volume. So, it was actually quite easy to take the next step and divide energy by volume to get SEC. And when I did this, I was amazed to discover that they were quoting the average across Europe as being significantly higher than the 1994 best practice figure.

    The best practice figure had been about 30 kilowatt hours per cubic meter, and the average across Europe was about 50. But what was even more stunning was that the best practice from that study was only about 10. In other words, the average was five times worse than the best in class. And I really found that difficult to believe. That got me starting to think about what data is available, and how can we look at it? In the systems we've installed, we tend to measure the kilowatt hours every day and we record kilowatt hours yesterday. So I had a massive amount of data that I could go back and look at. And I took 25 different cold store sites across the UK, and about three years of data, and put it all into a big Excel spreadsheet and started crunching numbers, and concluded that the best practice figure nowadays was probably about a third of what it had been in 1994.

    We had stores that were delivering the 10 kilowatt hours per cubic meter per year without too much difficulty, but there was still quite a wide range. We didn't have anything that was as high as 50, and bear in mind that 50 was the European average. That's, again, quite stunning. I then started thinking about, well, what would influence that figure. Is it the ambient temperature? Is it the amount of product that's going through the store? And I started looking for different correlations and completely failed to find anything, pretty much. It was really quite surprising, but we were able to develop a equation based upon store volume, which is really very simple. And it allows people to compare themselves against best practice, as we called it. And the equation was simply 15,500 times the volume raised to the power minus 0.63. So, very easy to put into a spreadsheet or an algorithm and just compare very, very basic—the bigger the store, the lower the SEC number. That's what the negative in the exponent gives you.

    And it's just economies of scale, basically. The surface area is less for a bigger building. For stores below about a 100,000 cubic meters, it rises quite rapidly, but above 100,000, it's a reasonably flat curve ranging from 10 down to about five at exceptionally big stores. That then got me thinking out many, many long hours that I spent in committee meetings with Hywel when the Energy Performance of Buildings Directive first came out, discussing the CIBSE guidance that was to be published. So I thought, I wonder how this would work with office buildings? And that's when I reached out to Hywel and said, "Is anybody doing this in the same way, specific energy consumption for offices?"

    Julie Godefroy:

    I think there's a lot to unpack here, and we're going to speak specifically about benchmarks. But on the point that you found the average was five times the best in class, unfortunately even if we were to use good benchmarks, that's what we see at the moment. So, CIBSE have energy benchmarks which, they are called benchmarks, but which are actually distribution curves. And actually, the median is four and a half times our best in class example buildings. So, we still see that anyway. Moving on to offices or other types of building uses that we want to benchmark, it is done. I think for sure, we still use and the industry uses still quite a lot benchmarking per square meter, just as you would have per volume. And I think there's two key areas of value in this.

    First is that it's simple, so clients understand it. They can compare reasonably comparable buildings and get a good idea. If they always do the same type of warehouse, et cetera, it's the simplest thing that they can start with. It doesn't prevent them from going into more detail if they have more information, but it's a good place to start. And the other reason that is quite interesting for us is that UK level with the work we're doing on net zero at the moment is that it means we can work on national budgets. Because where we're trying to define net zero carbon budgets, we are doing that by saying how much zero carbon energy will we have in 2050? How much floor space of building per different sectors, and therefore what sort of rough budget could we attribute to different floor spaces?

    And the next step, that we were actually just discussing this morning in the meeting, is to say it right, in order to make sure that as a total for the country everything adds up, we start with square meters. And then per sector, we might derive different types of targets. And this is where somehow the function of the space starts to matter. In a restaurant, it might be benchmarking per meal. In an office, it would still be the way we've done it in the UK, and in Europe to some extent, and with neighbors, is still per square meter, but it's sort of adjusted based on the value of the space or the function of the space. So, per square meter and in adjustment according to occupancy hours or occupancy density. That is very much part of the UK discussions and practice for quite a few years. Maybe Hywel wants to give us the history of how we got there.

    Hywel Davies:

    I'm not sure that it would be the most interesting history lesson that anybody had ever given. I mean, it does puzzle me that we have spent so long looking at this and we don't seem to have made as much progress as we might have done. And I find myself looking at Andy's five times, Julie's four and a half times, and thinking that's a huge amount of energy that is bluntly being wasted. And what are we doing about it?

    And maybe six months ago, people would have said, "Oh well, energy is not that expensive. Think about the salaries of the people who work in the building or the value of the product that's being stored. It's really important to make sure you hit the comfort or the thermal storage requirements. And if it costs a bit more but it preserves your product or it keeps your occupants happy, it's worth it." I'm not sure people are going to be quite so keen on that argument today.

    Andy Pearson:

    The other thing is that that's just the average. There are some, half of them are worse than that. And that's the thing that really blew my mind. How can you be 10 times worse than best practice? Because we don't install enough refrigeration equipment to use that much power. I don't know what's going on in those buildings, but it's something very, very unusual to create that big a discrepancies. And you're right. The measure that was appropriate six months ago is probably off the scale now.

    But the other thing is that people who previously weren't interested are now suddenly coming to us and saying, "We want to know more about this." So, it has been a good thing in that sense. I'm actually going off the idea of the benchmark, funnily enough, because it sets a perhaps unrealistic target for some people, and their attitude seems to be, "There's no chance of me ever getting to that, so I'll not bother." Whereas what I'd rather they were doing was benchmarking against how good they were last week or last month or last year, and looking for that continual improvement. And this is the nice thing about the SEC measurement is you can benchmark against your own performance. You can benchmark against your neighbor. You can benchmark against the industry standard. I wouldn't suggest benchmarking against the average because it's so poor, but benchmarking against best practice is perhaps unrealistic, particularly for older buildings or busier buildings, or for some other reason.

    Julie Godefroy:

    You can have a benchmark of anything. You can have a benchmark of bad practice. But I agree. And this is also why we've moved to distribution curves because previously—CIBSE Guide F is still about good and typical. And not only does it get completely out of date, as you say, but also it's not aspirational enough for some, it's too hard for others due to specific constraints, et cetera. So, distribution curve drives you towards hopefully more continual improvement.

    Andy Pearson:

    We started talking about the good practice zone, which was the band between the old ETSU benchmark of 30 and our new benchmark of 15,500 times whatever. We said to people, "If you're in this zone, then that's pretty good. That's definitely well done. But you might still be able to do better. So, start monitoring on a go-forward basis and see how you can improve that." And people somehow reacted much better to that, which was interesting to see.

    Hywel Davies:

    I think one of the challenges that we've always had is getting people to do this. And you made a comment at the beginning, Andy, that you were surprised at the very low level of interest in what you were doing early on. Unfortunately, I don't think that was an unusual level of low interest. Getting people to pay more attention to energy has been a challenge for a long time. And it's really unfortunate because at the most basic level, just keeping an eye on how much a business is spending on energy and then looking to manage it, and are we doing a bit better than were a week ago or two weeks ago? Are there simple things that we could be doing to improve our energy performance? What effect is that happening? Can we see it coming through in the figures? They're not hugely difficult things to do, but I think we've really struggled to motivate.

    Andy Pearson:

    There is a difference between now and the 1990s, where I think perhaps because energy costs have gone up or perhaps because people have learned a different way of thinking about these things, but there's a greater willingness to share information. I think the reluctance back in the 1990s was partly, "I don't want my competitor to be able to tell what my energy figures are. That's secret information. I'm going to keep that confidential." But people have apparently now got a better understanding that the more they put into that kind of exercise, the more they get out of it. So they're more willing to share that data. It can still be anonymized, so it's not giving away any trade secrets, but they will get a bit more out of it. We've actually created an app now that's free to download, that people can use the app on the iPhone. They put in the volume of their cold store and the annual energy consumption. And it will show them a graph that plots their performance compared with the average of everybody that has put their information into the app. So, you get a scatter and you can see, "Yeah, I'm kind of in the middle of the bunch," or, "I'm leading the pack. I'm really doing well here." But it still prompts people to compare their own performance against how it was previously. And that's the really powerful thing. I think Julie touched on it earlier in saying that we've got to make it easy for people to do this, and having an app on an iPhone or an Android definitely helps because the information itself is not hard to get. You read it off the electric bill and you know the size of your building. It's only these two bits of information, so it's not hard to get.

    There's a further difficulty, though, when we come to things like blast freezing or food factory performance compared to just standard cold storage. And again, Julie touched on it, talking about energy per meal served in a restaurant. I think that's a great metric. In a pie factory, it might be kilowatt hours per pie that's produced. Unfortunately, we can't get people to compare their production throughput information with their refrigeration energy use information. Nobody brings those two bits of data together and puts them in the one place. In a restaurant, it might be slightly easier, but I suspect not. They'll be in different departments or different compartments of the manager's mind.

    Julie Godefroy:

    I think that's done.

    Andy Pearson:

    People doing it now? That's great.

    Julie Godefroy:

    Yeah. I've worked on hotels and restaurants. They have their own network. That's how they benchmark against each other. There's working groups across hotels, say, who compare per bedrooms, per bedroom sold, per meal. Absolutely, done. Yeah. Yeah.

    Andy Pearson:

    Good.

    Julie Godefroy:

    And in some building uses like this, utility bills, let alone now, they are a massive part of their business model. So, they are quite clued up. I agree with you that they might not share it to the outside, but they actually sometimes share it with each other. It's just not part of a wider conversation, maybe.

    I think I'm really glad that we're actually talking about energy because when you say we want people to compare the performance of their building compared to last year or compared to last week, this is one of the big reasons why CIBSE advocates for energy use to be one of the major metrics that we use when we look at buildings. Because people, so whether it's clients or consumers, can get really confused when we use metrics such as carbon. In the UK, they will think that their building has improved in the last five or 10 years, when actually all that has happened is the electricity grid has decarbonized. And unfortunately, that does happen. Many people who actually are trying to look at what's happening to their building get confused because they're using a system-dependent metric. So really, kilowatt hours obviously is not the only part of this story, but it is a really important reason why CIBSE advocate for it.

    Andy Pearson:

    Are they also looking at gas usage and water usage in the same way? It's not so relevant for the cold stores in general, but I can see for an office building or a hotel or hospital that could be really, really significant.

    Julie Godefroy:

    Yeah. Gas, absolutely. I mean, water, a bit less because water really is too cheap. And also in many cases, even more so than for other utilities, the standing charges as such that even if you made massive reductions in your usage, you wouldn't necessarily see that in your bill that much. But yes, then it is very building use-dependent. So in a hotel with swimming pools and a spa, that would be a big part of their management.

    Hywel Davies:

    And if they are measuring the energy that they're using to heat their water, they've got a proxy for hot water because there will be a connection between the energy use for hot water. And as hotels become more thermally efficient, better insulated, the proportion of water going for domestic hot water compared to other energy use for heating, the hot water will go up. And I think that's going to start concentrating minds. It won't be the direct use of water. It will be the energy consequences of the use of water.

    Julie Godefroy:

    And hot water use is a massive issue in hotels anyway, because we all behave in hotels as we wouldn't at home. So, it's a massive thing. Anyway, we all love the long, big showers.

    ASHRAE Journal:

    Thanks for listening to the ASHRAE Journal podcast. We want your ideas. What topics do you want to hear about, and who do you want to hear them from? Email us your ideas at podcast@ashrae.org. That's podcast@ashrae.org.

    Hywel Davies:

    Can I ask another question? This business of the range. And as you pointed out, Andy, if the median is four and a half, five times the best, it's a range of 10 times. How well do we think we understand what drives that? Does that give us any opportunities?

    Andy Pearson:

    I would say for cold stores, I absolutely don't understand it because the way that the equipment is sized is fairly rudimentary. You work out a kind of a heat load for the building and you put in plant that has a little bit of resilience. So, if one compressor is not working, it doesn't lose temperature control. There's a little bit of extra capacity, but there's not 10 times the capacity. Nobody can afford to put that much equipment in. So, something very odd is happening if it's using 10 times the energy. Firstly, it must be running all the time. And secondly, it must be running very inefficiently all the time. Now these are outliers, I suppose, but even at five times, it's difficult to envisage that. And there doesn't appear to be a correlation between, or there's not an easy correlation between ambient temperature and the cold store energy consumption, which seems a very odd thing to say.

    But particularly with the best practice stores, one of the key measures that would bring a store to the point of being considered best practice is that it's kind of inoculated, if you like, divorced from the ambient temperature, from the external influences. It's well insulated, it's got good door discipline. There's not a lot of air leakage. All of these things that would mean that the external temperature might have an influence are reduced down to the absolute minimum. Therefore, there's not a particularly strong correlation between ambient temperature on an hourly, hour by hour basis, and energy use. There is a bit of a seasonal difference. When you plot the figure on a daily basis, you can see that it does tend to be higher in the summer than the winter. But day by day, it's varying by more than plus or minus 50% on that individual day figure without any particular change in any of the obvious operating parameters.

    So, there's a huge amount of noise on the signal with no explanation for it. That still doesn't explain how something can be 10 times worse, but I console myself with the thought that in that kind of a store, it ought to be fairly obvious where the improvements can be made. So I think to your earlier point, people are just not interested. They're not going looking for these things. They're not motivated to go looking for these things. From what I've seen of office buildings, it seems to be the same in offices. There's greater scope for bad practice. You can have the cooling system fighting with the heating system, and both of them consuming energy and just scoring points off each other, which could be horrendous.

    Julie Godefroy:

    Exactly. And that's just one example. I mean in offices, as you say, you could have simultaneous heating and cooling, also systems being poly-maintained and controlled, et cetera. Plus, we add people. So one of the reasons is that some buildings will be occupied much more densely for longer hours, et cetera. There's really many more variables compared to a cold store. I think there's enough information now from post-occupancy evaluation studies that we know very well many buildings are very badly operated and managed, in addition to potential issues in the first place with the design. I think where the differences come from, we understand.

    And what's quite interesting when we look at example projects is that there is no individual measure that you would say is exceptional. What's exceptional is that they have done every single thing right, the design, the performance modeling, the quality checks during construction, the commissioning, the handover, et cetera. It's just what's exceptional is the attention to every single step and all the detail that has gone into it, and then the follow-up. But I think, yeah, we understand the combination of factors that lead to these massive differences now.

    Andy Pearson:

    I suppose a realization of the size of the prize is important as well. "In your building, you could reduce your energy bill by 10% or by 50%, or whatever the metric is, provided you do the following things," is serving it up to people in a way that they can then take that and make something of it rather than just lambasting them for being a bit rubbish at what they're doing, which doesn't really motivate anybody to do anything. You need to give a way out, a way forward.

    Hywel Davies:

    We almost need to flip the framing because instead of telling people, "Well actually, you're not doing very well," which never really motivates us, does it? We need to say to people, "Looking at your typical energy use at the moment, you've got some real opportunities here to improve it and save yourself some money," which is a slightly more encouraging way of framing it. But it does ultimately come down to the price and how much they think the prize is going to be.

    Andy Pearson:

    That line of thought led us to the next stage of our cold store energy development, which was attempting to predict what the SEC was going to be. And this, I found to be a really powerful motivator. We were taking the daily figures and trying to work out on the basis of the data gathered whether making a maintenance intervention was going to be worthwhile or not. So, gathering the daily figures, the question was, how many days of energy use do you require to make an accurate prediction of where it's headed? And we looked at the seasonality that I mentioned earlier and made an offset adjustment that in the summertime, the daily number was likely to be more than one 365th of the annual figure. And in the wintertime, it was likely to be less than, and we just applied a bit of a weighting to them.

    And that gave us a remarkably powerful tool, which even with only 10 days of data, we can have a reasonable, accurate stab at what the figure is going to be, plus or minus 30% on the basis of 10 days, plus or minus 10% on the basis of 90 days. And obviously, if we've got 365 days' data, then we have the SEC figure already, but that's entirely historic. It doesn't help us in assessing the efficiency benefits of making a maintenance intervention. So, we draw a graph which shows the 10 days' data prediction and the 90-day data prediction, the 270-day data prediction, and then the full year actual value. And if the 10-day prediction rises above the 90-day prediction, it shows us that things are getting worse. And it shows us that very quickly. We'll see that within five days of the change happening. And if the 90-day one then starts to rise as well, it suggests that something has shifted, and it has shifted in a kind of persistent way. And it raises the motivation to go and investigate and find out what has changed and to do something about it.

    And this can be used in two different ways. It can be used to spot things going wrong. The classic example in refrigeration would be that something blocks the airflow to the condenser. Nobody knows that it's there. It's a plastic bag has blown over the air inlet or whatever, but making the performance worse. And fairly quickly, you will see that in the graph and somebody can go and investigate. If you waited to look at your month-end usage figure or your, even worse, year-end figure, you could have been suffering from adverse performance for many, many weeks and paying the price for that. Whereas if you get that early flag of essentially, it's as simple as the blue line has risen above the red line, and you see the differentiation open up between the two, you can go and investigate and find out what is it that has changed and then take corrective action.

    But the other way to use it is to say, "I'm going to spend some money on cleaning the condensers, or refurbishing the compressor, or cleaning the evaporator," whatever it is, "It'll cost me 500 pounds to clean the evaporator. What will the benefits of doing that be?" And seeing that step change in the specific energy consumption allows you to do a almost mental arithmetic level calculation that says, "I'm now saving a thousand pounds a week by having spent 500 pounds." It's an absolute no-brainer that you'd want to do that.

    Or, you can make a more significant intervention. You say, "Well, it cost me 50,000 pounds to do that, but it's saving me a thousand pounds a week. So within a year, it will have paid back for itself." It's making the case for doing it, and then giving the confirmation that a change has been achieved. But you need that rapid prediction of where it's headed in order to make that connection between the two. If you leave it too long, too many other things will change in the meantime and it kind of dissipates the message. Nobody cares about the maintenance they were doing three months ago.

    Julie Godefroy:

    I think again, it's more complicated in other sectors because we have the people factor, but there's definitely quite a lot of solutions that I have seen. I wouldn't be able to tell you the detail, but I know this kind of software exists now that is capable of gathering the really huge amount of data coming out of BMS system. Plus, all sorts of factors such as occupancy numbers, et cetera, to spot unusual patterns, whether it's against the prediction or against unexpected pattern or some other form. And whether it's at the whole building level or component level, I know this is happening. And I think this is sometimes, as you say, just based on the data coming out and what you would expect it to be, following a pattern. The obvious other trend is that there is much more now performance modeling.

    More and more at the design stage and the in-use stage, there is a model of what the energy use of the building could be, which is slightly different from what you would expect it to be given the current patterns. It's more, this is the potential of that building. How is actual usage comparing against it? And again, I'm nowhere near saying it's mainstream, but we do see more and more consultancies now doing quite detailed analysis of energy use, monthly or weekly, against what their modeling tells them it could be with calibration loops against actual occupancy patterns, et cetera. But all of that is really starting to happen due to legislation, carbon targets, energy bills, contractual performance targets, et cetera.

    Andy Pearson:

    To what extent do you think that will then reflect back into fundamental building design? We see a lot of amazing looking buildings that are absolutely horrific from a building services point of view, all glass, facing south, that kind of thing. Is that now changing?

    Julie Godefroy:

    Well, certainly we see it. Again, when you look back at the examples, I mean, there's that issue of the fully-glazed facade. The other thing that we are starting to see, and it's not just wishful thinking, me saying this, is that buildings are starting to be a little more simple. 10 years ago, we would have had submission at the CIBSE awards with just about every system on the market chucked at the buildings, and they are starting to be a little bit more simple and better integrated, I guess, more attention to how things work together, how they're going to be controlled.

    Hywel Davies:

    I mean, we are certainly seeing in London that the leading property developers are paying quite close attention to energy. And they're following the example of the Australian NABERS system, which really does encourage a focus first of all on energy use during the design stage, where there's much more attention to anticipated energy use. It's definitely a more thought through piece of energy calculation. And then in order to get the rating, you actually have to measure your energy use in operation over a period of time, and demonstrate that you are meeting the, again, the benchmark figures. Now, that has been going for many years in Australia, but it's beginning to take off, certainly in London. And I'm not sure whether it will spread provincially. Julie may know more on that.

    Julie Godefroy:

    I think the big driver as well is the investors. Is that for the first time, investors are asking for actual energy and carbon data, and that comes in large part through regulations in the EU. There are now clear pressures on various financial bodies to actually have the data on energy use and carbon across the portfolios. So, that really puts pressure on, say, the property developers, et cetera. And it's fantastic because for many years, we were in a situation where if investors were asking for anything, it was an asset rating like an EPC, which as we all know, has very little correlation with actual energy use. At the moment, there really is pressure from all side. I would say the weakest pressure is on regulations for energy performance. It seems that everybody else is putting in the right direction.

    Hywel Davies:

    We do have the challenge in the UK system that building regulations deal with what you're building, but once it's built and signed off, the code doesn't then apply. So operational energy use gets picked up by other things. There is a European Energy Performance Directive, and the UK signed up to that before we left the EU, and we still have those regulations in place. And I think that's one aspect of what we've inherited from our European era that will not be weakened. If anything, it will be strengthened and supplemented. There's already talk about an operational energy scheme in commercial offices, which again, Julie has spent a lot of time on. So, we're seeing the push towards operational energy coming from that source. And as Julie says, the financial and the corporate social responsibility angles are probably driving it much more than any simple building codes.

    Andy Pearson:

    And how has the last two years affected the whole question of energy modeling and buildings? Obviously, the COVID pandemic has meant firstly, massively reduced occupancy rates, and also people operating buildings in ways that they were never intended to be operated with regards high ventilation rates in wintertime and that kind of thing. Is that kind of destroying the database that was being built, or is it just a short-term temporary blip?

    Hywel Davies:

    I suspect it's too early to know what the impact is on the historic data. I mean, I think what we have learned from the pandemic is that a lot of buildings probably weren't really being ventilated as well as they should have been. There's not a huge amount of evidence to suggest that lots of buildings hadn't been built to be ventilated to the levels in the code. And I think it's fair to say that that's true in both the UK and Europe and in North America. I don't think we've suddenly learned that we've been designing with too low a level of ventilation. And it's back to the energy piece. What we've learned is that just as we are not very good at maintaining the energy performance of a building in use, we're probably not as good as we thought we were about maintaining the effectiveness of the ventilation system. It's there. If it's properly maintained, it will deliver the ventilation rates that it should, but we've just not been very diligent about maintaining its effectiveness or its energy efficiency.

    Julie Godefroy:

    I think the other realization that seems to have happened, at least anecdotally, is that some people did look at their quasi-empty buildings and the energy use and realized the energy use was still really high. And they thought, "Well, there's hardly anyone in this building. And it's only using maybe 50% of what it was when it was running all the time. So, what's going on?" That, I have seen. I can't say whether it's a trend, but there has been some interesting studies of people realizing just the massive background energy that seems to be swallowed by buildings without really understanding why.

    Andy Pearson:

    Do you think, Julie, that there is a metric that people are not using at home? You mentioned measuring kilowatt hours per square meter as one, and kilowatt hours per occupant as another. Is there something else that folks should be looking at?

    Julie Godefroy:

    I think it will depend on building uses. So, for example, in the case of offices, I wouldn't say per occupant, I would say per kilowatt hours. And I think that the idea of having a bit of a weighting based on occupancy density and hours is interesting. What is quite interesting is in homes, more and more, there are discussions about whether it should be per occupant or per bedroom. And I think we know that the first generation of low-energy houses, say 10 or 15 years ago, tended to be really quite large. And a lot of the time when they claimed good energy use, of course there was a lot of really good things happening on the passive design side, but it was also one or two people in a 200 square meter home, which isn't the London average. So there are more and more discussions around this, sometimes just with an engineering angle, sometimes as well about climate justice to say, "Well, we have to be a bit careful about what we say if we are giving targets to people on per square meter basis," because people who can afford it will still have quite a big budget.

    And then as I've said, in different types of buildings it could be in using whatever is relevant to that building use. So meals, bedrooms, et cetera. I think to try to always relate to square meter for the reasons I mentioned at the start is still useful even if we have these adjustments or additional ways to look at a building as an entry point is still quite useful. We shouldn't focus so much on the specific cases that we put off anyone starting somewhere, because quite a lot of the time, you still have very important similarities between buildings. So if we focus too much on the outliers, then we might just lose interest from the majority of the buildings.

    Andy Pearson:

    I think that's very true. And also getting started and gathering the data. The sooner you start, the better. I was very fortunate that we had been gathering daily kilowatt hours figures for every site that we install anyway. So, I had an absolute bucket load—

    Julie Godefroy:

    Play time.

    Andy Pearson:

    Of numbers to play with. But if you don't have that, it's a year before you can see what the SEC is going to be for your building, and getting people motivated to do something that might be beneficial in a year's time is tricky.

    Julie Godefroy:

    Yeah. Yeah, absolutely. There's so much you can do with the patterns, et cetera. And in a way, if you start to get the interest, which is what you're doing in a way with your predictions, there's so much to learn from looking at patterns of energy use. Ultimately, your benchmark is going to be a number, et cetera. But there's much more value in understanding why nighttime and daytime energy use are a certain way, or are the same when they shouldn't be, what's happening on the weekend, et cetera, than in working out what the absolute best way to benchmark your building is. I'd rather spend time on that, I think.

    Andy Pearson:

    One of the other interesting things that I've found with the cold stores was, I presented some of my findings at the International Congress of Refrigeration in Montreal in 2019, and a friend was there who runs a similar business to ours in Brisbane, Australia. And he had been doing a similar exercise, measuring kilowatt hours per day in Australian cold stores, and had come up with a curve for best practice for his stores which was almost identical to mine. It was in the same format, and the coefficients were close enough to be the same. That led to the very interesting conversation about what's different about Australia compared to the UK? And the obvious thing is, well, the ambient is much higher. But as I mentioned previously, if you're operating a best practice facility, that means that you're paying attention to door control and you're making sure the refrigeration plant is in good condition. And you're making sure that the incoming product is within temperature specification, and everything that makes it a good practice store means that you're somehow separated from the prevailing ambient temperature at any given time.

    So, his metric was pretty much exactly the same as mine. I then got the data from him to apply the predictive algorithm to look at what happened in Australia. And we found that all we had to do was offset the weighting factor by 180 days and it worked as well for Australia as it did for the UK. It really did seem to be a universal thing. Now, that got me thinking, what would happen in a equatorial region, where you don't have a summer season and a winter season? You've got a completely different pattern, but I've not got enough data yet to do the same exercise for cold stores along the equator.

    Julie Godefroy:

    You won't have the same day-night variation as well, which will have an influence.

    Andy Pearson:

    I don't know for office buildings, would the same apply? Or obviously with fresh air make-up, it drives your cooling load much more, ambient temperature. Even your best practice building is subject to that. But on the other hand, if it's down to how much you are wasting, a best practice building will be wasting less. It won't be bringing in excessive fresh air and having to cool it. It will just be bringing in enough to serve the occupants. You might actually find the same thing, that the climate zone doesn't affect the result for best practice as much as you would think it would. I was really quite surprised by that.

    Julie Godefroy:

    Yeah. I mean to some extent, it will. There's big discussions about this because of Hywel mentioned the fact that NABERS from Australia has been quite influential here. People have looked a fair amount, I think, at how applicable the numbers coming out of NABERS in Australia, for example, would be as benchmarks here. And there are some areas of Australia that would be relevant enough. But I think the people who have looked at it in detail think there's still some adjustments needed to really drive best practice. And that's another adjustment that is taken into account in some ratings is year on year, degree-day adjustments. Even if it's not massive, it should still have an impact.

    Andy Pearson:

    Well, two of the stores I looked at were in Brisbane, and the third was in Cairns, which is within the tropics. So, certainly not a Scottish climate, not a UK climate, and yet the same metric and the same algorithm worked perfectly well. So, interesting.

    Julie Godefroy:

    Interesting.

    Hywel Davies:

    Yeah. I think from memory, most of comparisons that have been done between Australian offices and UK offices have used Melbourne as the comparison because that's the nearest to London, but it's not a direct comparison.

    Andy Pearson:

    Every time I've been to Melbourne, it has been raining. It's quite like Scotland in that respect.

    Hywel Davies:

    I think it has been really helpful to talk through energy use. On the face of it, you'd wonder what the similarities are between energy use in cold stores and energy use in office buildings. And you'd think, well, they're two completely different topics. But what we've identified is that careful measurement and management can yield quite significant benefits in both types of buildings. It just demonstrates the value of people measuring and paying attention and applying basic engineering principles. And after all, we are engineering bodies.

    Julie Godefroy:

    Anything that encourages people to look at energy data makes me happy.

    Andy Pearson:

    I think the surprising things that I learned from the whole exercise were firstly, that there were not correlations where I had assumed there would be correlations. There's not an easy correlation between ambient temperature and energy consumption, which of course everybody knows there must be, but there isn't when you look at the actual numbers. I'd looked at wind speed, I looked at wind direction, I looked at solar gain, I looked at wind gust, none of these correlated well. There was a bit of seasonality, as I mentioned, and we were able to smooth that out, but the day-to-day variation could not be explained.

    However, that led us to the conclusion that if you were to take even just 10 days of data, that daily variation very quickly gets smoothed out and leads you to a much more accurate forecast. So with one day's figure, we could predict SEC for the year to plus or minus 50%. With 10 days' data, it came down to plus or minus 30%. And that gathering data, maintaining it, storing it, and then reusing it is really valuable.

    And I guess the other thing I learned was that more data isn't necessarily better data. You need to have a way of simplifying without losing integrity, to deliver to the operator something that he can actually get his hands around and make use of. So, delivering the message became the most important thing, making sure that it was explained clearly, and it gave them something to aim at. And as a result, we've seen a fantastic take-up of this just in the last couple of years, that people really do now seem to be switched onto it. Which is great to see because it's as important now as it was in the 1990s. And in one sense, even higher stakes because of the way the energy prices are going. At long last, we're able to link the technology and to make use of it to deliver that advantage. It's a really exciting time just now.

    ASHRAE Journal:

    The ASHRAE Journal podcast team is editor John Falcioni; producer and associate editor, Chadd Jones; assistant editor, Kaitlyn Baich; and associate editors, Tani Palefski and Rebecca Matyasovski. Copyright, ASHRAE. The views expressed in this podcast are those of individuals only and not of ASHRAE, its sponsors or advertisers. Please refer to ashrae.org/podcast for the full disclaimer.

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