SmarterView Demonstration

Key Takeaways

Um, but just to start off, I'll I'll kick off at a high level. We've got data from distribution centers, coffee shops, and retail stores to look in this example. And the most useful place to start is the electricity consumption used store by store across a portfolio. Um so this is useful for sustainability managers or perhaps uh those in head offices who want to highlight the energy that's being used in different buildings. And we can see here that as expected the consumption would be relatively similar given that the operation is uh retail stores owned by the same company similar uh size and terms of the operation. But what we're going to do is dig a little bit deeper and uh find find some highlights out of this data. So, what I'm going to do here is select a couple of sites to graph so we can look at how they use their data comparably um site on site. And interestingly, I've got a void unit in there. Um so, void unit, as you'd expect, using very little data, not having tenants in. Um, just as a side story, actually, we've had not one but multiple commercial units who through monitoring have identified unwanted occupants growing things that they probably shouldn't be. And the spikes in the data allowed them to take immediate action to secure the properties and manage what could have been high electricity bills and costly repairs. So, I'll come back to this data set though. And at first, if we have a look at retail unit 2, we can go into some granular data data about how the energyy's used on a daily basis. Forgive me while my screen catches up. What we can see here on the 19th of February is little bit of energy being used outside of ours as you'd expect that increasing during shop operational hours and an unusual uh data set actually at the end. You may expect the energy to drop off there. Uh perhaps staff have turned heating on for some uh uh some activity outside of outside of the normal operating hours. We can go further into that and I just need to move things around into the combined statistics page where we look at how the electricity is used on each phase. Um so for a lot of you running commercial buildings, you'll have three phases of power. What we're doing is providing a granular breakdown of where that power is used per phase so that you can identify easily the time and the phase in which that power was drawn. So real insights into uh starting that journey in in in reducing energy use. Let's look at retail unit 4. Now this was the higher consuming of the two sites. And if I go to the same day u previously, the 19th of February, you'll see that there's been active energy management. Here we go. Active energy management on this site already. So I think it's quite uh it's quite normal in terms of looking at a portfolio to pick the lowest hanging fruit first. And in this example, they're actively switching off the power at night to reduce that consumption, yet there's still the higher consuming of the sites. And the interesting learning in this for me is that whilst the first step is being taken to reduce the power at night, if I look across the rest of the portfolio, how do we share those learnings with other site managers to show how to reduce those out of hours costs? So real lesson there. I think it ties in with what Pierre was saying about the first step is management. The next step is how do you share that information? Um I think you'll find that about 20% of uh electricity used on average is out of ours. If we could cut 10% of that across your portfolio, that's a that's a significant change. Uh a small piece here on the data that we do provide. So consumption as you'd expect uh if you like to manage things in terms of cost we've got the cost per day for operating the site quite easily change that on the graph so you know on an hourly basis what it's costing. We've got power factor that is um the relationship between uh the energy drawn and how efficiently it's drawn and and it feeds directly into something called your peak demand or your KVA. uh KVA is becoming increasing increasingly important to manage. Um most of you will have a uh a standing charge on your invoice and a maximum capacity for the site. Uh and the demand is how much you're drawing. So ultimately you want some leverage between um what you're drawing and what the peak that you should be drawing is. That helps you avoid things like excess capacity charges. Um and more importantly these days if we're looking at uh reducing our gas you usage and replacing that with uh electricity appliances. How much room have you got to move before you may may need to upgrade your site? So useful in terms of the normal operation and of course if you're looking at EV charges which draw a lot of load um this data is going to really support uh the the direction that you take with that. What I also found interesting was when I reviewed the portfolio of coffee shops we had a very similar uh found very similar instances where the highest consuming site if I go into that uh the highest consuming site actively manages the energy outside of ours but that behavior hasn't yet yet being shared across the portfolio. So I'm just re [Music] um I guess reiterating that message that taking the learnings from one site and sharing the sharing across the portfolio adds real value. going to look at the detail quickly actually on um on the larger of the consuming sites and we're just going to go to look at the phases and how the power is used AC used across the phases. What we can see from this is again that active energy management, no power used until the site's turned on. And then with these three lines together, the three phases, that means that primarily the energy used on site is from three-phase equipment. And actually the findings, recent findings on this is the coffee machine that's used on site is significantly older than the others, drawing a lot more load. uh and they also had some uh heating ovens that weren't in place on other stores, but they've got down to that detail and then this data supports the return on investment to replace that to replace those appliances. Right, let's touch on distribution centers just for a a slightly different uh look and feel. So here we've got uh monitoring on water gas ampower and we will compare what happens in the gas across the across the site. So again uh same company, same square footage, very different profiles. So here we see center 3 using significantly more gas than two. And we've got the opportunity to go down and and see why that is. And the interesting finding for me here was actually the what appeared to be the lowhanging fruit, which was the highest consuming site. The first thing that we found is a site that has operating hours of 7 till 7 actually has their gas running all night for heating. So what an immediate find to reduce uh reduce the gas usage by 30 to 50%. When we look at the water data, this really verifies for us the occupancy on site. Outside of using occupancy sensors, water is a great way to do it. And the water, as we can see there, uh it's typically used for welfare services. So, no water consumed while the sites uh unoccupied. Uh and then the general welfare, water used through the day. We did actually pick up on one more thing water-wise that's really worth touching on. Uh this is on the the second site and while the site is unoccupied actually there's a water leak. So very clearly here we can see through the night there's water leaking that we wouldn't usually expect and what an opportunity that is to get on top of things quickly. not necessarily from a water bill cost but from a um from reducing the the cost to repairs for those who provide uh those who provide any billing for tenants. We have a module here which I can touch on quickly. Uh, so this is used either if you run an estate and need to invoice your tenants or if you're just looking to set a forecast for your costs before you receive your supplier bills. You simply select the month of January, the electricity cost, the gas cost and the water cost and then you can issue that statement directly to your tenants. Uh in terms of data, we have this in for visualization. Uh there's always the opportunity to export into Excel if you need to shift the data into other management systems that you have. Uh and we provide APIs of data as well daily, weekly or monthly that can go direct into your management systems uh and also to your carbon consultants to support your carbon reporting. Lastly, in terms of the monitoring, I've given you a very quick overview uh of monitoring at a building level. Of course, we can go down to more granular uh detail in monitoring estates, buildings, floors, phases within the floors. Uh so naturally the first part for our clients is understanding their total load um before venturing into that that granular detail of monitoring and how they put active controls around uh their energy consumption. So I hope that's been useful for you. Um I believe there's a necessity for energy managers, tenants and landlords to work together uh in order to achieve sustainability goals. And by aligning uh the tenants and landlords, we move beyond compliance, hello ESOS, into that real world of measurable impact. Uh and that together for us to tackle our scope 3 emissions, we need to drive meaningful uh meaningful change.