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For some people there is only one metric that matters when thinking about energy in their buildings – the bill. And the only outcome that is interesting is driving it down.

We’ve all lived with people like this. Sometimes we have argued with them over the setting for the thermostat. Or even found ourselves sitting in the dark as a light automatically switches off.

These incidents make an important point about energy efficiency: one that we know intuitively. A simple focus on the input (the energy bill) can lead to poor decisions on how a building is used. At its most extreme it can undermine the purpose of a building – to shelter its occupants and foster productivity – completely.

A more fruitful way to think about building energy efficiency is to understand what outputs we want from a building for the energy we put in. Although this is harder to do, it results in buildings that are both truly efficient and more productive for those working in them.

So if building energy efficiency means using less energy to provide the same service, how can we measure this? And what can it tell us?

Measuring true efficiency

To benchmark true efficiency you need to find metrics that can be used across a wide range of very different buildings. So it is standard in energy efficiency to talk about energy consumption per floor area and energy consumption becomes KWh/m2.

This helps with comparisons between buildings but tells you very little about why some use more energy than others – are their lights on for longer? Do they need more heating energy because they are draughty? Measuring outputs not only gives a more accurate picture of energy efficiency but it can also help identify where waste happens.

Where energy is used

Energy in buildings is turned into a lot of outputs and a complete accounting of these is impractical. How can you compare output used to charge a phone against the load required to boil a kettle?

However, the majority of energy used in commercial and domestic buildings goes on two significant and measurable outputs – keeping comfortable air quality (temperature, humidity and ventilation) and keeping the lights on. These two end uses will typically account for nearly 70% of the energy footprint in offices and homes, so if they can measured and compared, a much clearer idea of the relative energy efficiency can be produced than relying on bills alone.

In practise, this can be turned into a measurement of Kwh/m2 of usable space, where ‘usable space’ is space that meets requirements for air quality and lighting.

How Purrmetrix can help

This philosophy is already reflected in processes such as PAS2035 and post occupancy evaluations, where monitoring and verification are used to confirm that energy efficient buildings are delivering the outputs they are meant to.

For property professionals who are delivering such evaluations, our mission is to make it easy to collect the data you need on building performance and turn it into useful information.

With sensors for temperature, humidity, lighting and CO2 and a sophisticated analysis platform the data can be turned into simple metrics of building output, so you can explore how investments in energy are paying off.

Accurate and detailed data on building performance lets you go beyond benchmarking and identify opportunities for reducing energy through optimising building controls and improving building fabric.

And measuring performance before and after improvements provides evidence on what works – and what doesn’t.

Get in touch if you would like a peek at what can be done with environmental data.

With 26 million homes to upgrade by 2035 to meet the Government’s clean growth strategy, the UK faces a gargantuan task. Delivering on this date requires a home to be upgraded every two minutes, and significant upgrades in processes for assessing, procuring and managing retrofit projects.

In response, a new generation of solutions are emerging that help landlords improve ROI from their energy strategies. In this article for Housing Technology we look at how Social Housing Landlords are meeting the challenges of decarbonisation and some of the most exciting solutions being used.

Every day I speak to a lot of property professionals – FMs, building engineers, asset managers. There is a lot of interest in turning existing buildings into smart buildings and using the IoT to improve the performance of buildings but still people are stuck with the business case. Clients won’t invest in the tech unless they can see a clear ROI; property assets are so variable that guaranteeing ROI is tricky.

Frustrating for property professionals who can see big efficiency gains in their operation if they can get better data from their buildings, but who are stuck without the tools to persuade clients to invest. Frustrating for clients who are hearing a great deal about the promise of IoT but can’t relate its benefits to immediate pain points.

After three years of pilots, turning average buildings into smart buildings, we have a large estate of sensors in operation, so we’d like to offer three clear business cases to discuss with clients. Tread carefully: different clients with different types of tenure will respond better to some than others.

1. Energy savings.

Want to save 10% of your gas bill simply by changing a setting in the BMS? We’ve written about energy savings before at length but the simple message is that nearly every older building will have opportunities for saving energy at *no* cost beyond identifying where controls don’t match the operations of the building. A couple of examples:

– the call centre in North West England which saved 18k on energy by changing HVAC set points and reducing conflict between zones

– the airfield in Eastern England who identified nearly 100k of wasted gas spend from poorly controlled heating in their hangars

The business case. Most older buildings waste energy simply because the control of their heating and cooling no longer matches the operation of the business. Timings may be off, unused areas may be heated, heating and cooling may be in conflict with each other. These issues are extremely easy and cheap to fix, and lead to rapid payback, but first they must be spotted. A properly smart building uses simple sensors to confirm that the BMS is doing exactly what it should be.

To calculate the possible ROI here are a few basic rules of thumb:

Costs of heating (or cooling) 1 m2 each operating hour £3.60 (from CIBSE benchmarks). Put another way, for a typical office operating a 9 hour day the annualised cost of 1 hours’ HVAC psm is £32.40. Therefore in a typical 1000 sq m office reducing the heating run time by an hour would save £3,240 on your annual heating bill.

Reducing set points by 1° can produce savings varying from 3 – 7%. So for the typical 1000 sq m office above, with an annual energy bill for HVAC of £29,160, that would be an additional £874 – £2041. These figures are hugely simplified – in reality the results will be complicated by factors including external temperature, and varying amounts of savings depending on how far your building is from the external temperature.

The faster and more frequently you can find these energy savings opportunities the more money you can save – at a minimum an annual audit (not from BMS data) should give you substantial payback. Remember these are *no cost* fixes.

This is a business case that appeals most to owner occupiers of space who have some control over their building services and who are invested in reducing their energy costs.

2. Space utilisation

Fun fact: fully loaded with rent, rates, utilities etc, desks in the UK cost employers between £3000 and £15,000 each year. Yet a lot of them are empty for a lot of the time, with utilisation rates often below 60%; so if ever there was a business case for better building data it’s in space utilisation.

So if your client has a large and fluctuating workforce and a big estate then they are probably already thinking about better space utilisation and if they’re not, they should be. Although the cost reduction argument is strong its not the only one, as it is possible both to reduce space and to provide more of the most heavily used facilities so that workers are better equipped and feel supported.  The range of new options for flexible working, from providers like The Office Group and WeWork, and a huge range of digital team working tools, mean that short term staff fluctuations can be easily accommodated and folded into the organisation.

For a quick business case on utilisation audits to discuss with your colleagues:

Estimate fully loaded desk costs (calculator by region here), multiply by number of desks and then ask what level of underutilisation you would need to find to justify the audit.  Even with audit costs of £100 – £150/desk, you’ll find it’s surprisingly small.

3. Productivity improvements

This is where the big wins are. Staff costs are by far the largest cost component of most businesses, and even small improvements in staff productivity can be game changing. It’s not just call centre operatives able to handle 10% more calls each day or traders making 2% more trades but also improvements in the quality of work from creative teams, or better focus from staff tasked with safety critical jobs.

Frustratingly, its also the hardest to prove. Here’s a summary of what we do know:

– Many studies have shown that indoor environmental quality has a measurable impact on people’s productivity

– Poor temperature control can reduce productivity by up to 10% at +/- 5% around a ‘safe’ band

– Better lighting can raise productivity by 23%

– Better ventilation increases productivity by 11% (link to UCL work)

– Productivity in different tasks can be affected by different aspects of the environment (for example noise levels)

The ROI from a better working environment goes beyond enabling staff to concentrate better. A better building reduces absenteeism and staff churn, so that recruitment costs drop.

Not all of these business cases will work for every client, but nearly every client is interested in saving costs and building a stronger team. The next time your client asks you how you can do something different in tired old buildings these are the conversations to have.

This is cool: the team at LCMB have been using Purrmetrix to go beyond data gathering and get into some home brewed building control.

LCMB have been monitoring the environment in a university facility for several months using Purrmetrix CO2 and temperature sensors to look at the relationship between comfort and productivity. One space in particular caught the attention of LCMB and the university estates team: an office area which had obvious ventilation problems. With a lot of people using the space the building systems were struggling to keep up with the ventilation needed, especially in winter, when opening windows was unattractive.

It was commonplace to see CO2 levels rising above 1500 ppm, a level where concentration and decision making becomes impaired.

But rather than going for a costly building services overhaul, the LCMB team decided to go one better and implement their own fix, using ducted fans and a Raspberry Pi to keep the CO2 in the office within controlled limits.

Two fans were set up to provide good coverage across the whole space; each had their own Raspberry Pi low cost computer to read the data from API on the Purrmetrix web service and to drive the fans using a digital to analogue converter. The fans were ducted from outside so the set up also needed a heater in front of the air to temper it to the right temperature. This might not be the prettiest set up, but it’s a prototype and a big improvement on a CO2 headache.

The project took a few days of tinkering time to connect the hardware, in particular setting up the Pi and configuring the internet access for it from the university network. But once the hardware was connected and the right scripts were implemented it produced an immediate result.

There had been some concerns about noise levels and air movement – in practice the team found that to keep levels of CO2 around 700 ppm (+/- 100 ppm) the fan was operating at 50 – 60% for much of the day. This delivered a good trade off between air quality and noise level. Allowing a higher CO2 level (around 1000 – 1200 ppm, which is considered acceptable) fans could be quieter, cycling on/off most of the day. In warmer weather as windows are opened, the fans are working much less frequently.

‘Once we had the data from Purrmetrix it was irresistible to have a go at creating a solution.’ explains Tom Cudmore, senior consultant at LCMB, ‘We considered using the alerts system within Purrmetrix to create a HTTP call that would activate the fan, but in the end we decided to keep the alerts for exceptions and take the data direct from the API every two minutes. It took a few weeks to source the right fan product and write the scripts, but we think the results speak for themselves – we’d be happy to work in this environment now.’

If you have a problem office and would like to re-create this low cost solution, to trial the impact in your workplaces, here are the components you will need:

– Fan (we used Helios RR-EC in-line duct fan) sized according to the room volume and desired conditions
– Ducting and window blanking plate
– Heater to put in front of the fan and temper the outside air
– Power supply for fan and heater
– Wiring from analogue convertor to fan
– Digital to analogue convertor – we used a LucidControl device
– Raspberry Pi with internet access and configured for remote access
– Purrmetrix kit – in this case with CO2 sensor

And if you want a copy of the script that LCMB developed, just get in touch.

Proptech. AI. IOT. Space as a service. Smart Buildings.

There’s increasing noise in the property industry about the importance of technology. You’re probably sick of the phrase ‘Data is the new oil’, especially if you’re tasked with trying to persuade a sceptical boss to invest in it.

Not surprisingly we have a lot of conversations about the ROI from environmental data, which can get complicated as there are many ways in which better insights into your environment create value. So we thought we might create a short series where we could share examples of what our customers are doing with this data and how they get ROI.

First up – how to reduce hvac energy waste

Fact: the energy consumption of commercial buildings tends to drift up over time. If you look at the lifecycle of a typical modern building over time the energy used to run this building will tend to trend upwards unless regular interventions – shown by the green line – are made to review and fix the problems that arise.

Why these occur is complex, but one of the most common and low cost causes is control drift, and that’s what we’re interested in. Studies in the US of over 600 commercial buildings show more than 50% have controls problems and that fixing these produces a simple payback within a year. These are very simple issues like scheduling, run time, set point adjustments, eliminating zone conflicts.

Further more, fixing them – recommissioning the building – is generally a very low cost win, requiring no new investment. So this looks like an attractive target for improving energy efficiency in any building, but to do this first you have to find the problems.

Causes of control drift

So it’s a common problem, it is low cost to fix – why don’t people pay more attention to it?

I think part of the problem is that, unlike lighting, HVAC control issues are invisible – the BMS is unlikely to flag it up as an alert, and identifying it requires expertise and time. If your buildings supports multiple schedules and set points – and we have come across academic set ups where there are hundreds of schedules for heating and cooling – then manual checking isn’t practical.

Furthermore many facilities managers are a bit sceptical of data reported from a BMS because they know sensors can drift without recalibration and they are often located away from the occupants. If managers don’t trust the data the BMS is producing, then they are less likely to invest the time in an audit.

The value of environmental data in these situations is that, unlike metering data, it is easy to locate exactly which part of the system is running out of control and implement the right adjustments.

The case for recommissioning

A quick back of the envelope highlights why this is worth doing – heating and cooling commercial space is typically 25 – 35% of the overall energy budget for a building. That means, at its simplest, that if the building systems are running for 10 hours where they could be running for 9, that extra hour is 2-3% of the energy budget for the whole building. Running at weekends is ruinous and not uncommon. In fact, based on experience, I’d go so far as to say if you have a building of more than 3 years old, its a stone cold certainty that parts of the HVAC will not be well matched to the operations in the building.

Fixing control drift – real world cases

Over the past two years we’ve seen so many examples of this, and not just in offices:

1) the 10 year old office building in a campus setting with conflicting HVAC zones and heating that was regularly 2 or 3 degrees above set point. Changes to reduce zone conflict and lower temperatures produced a 20% reduction on an annual 80k energy bill

2) a school with a large number of Victorian school houses and a wet radiator system that had extensive challenges with timing heating, incorrect sensor readings and furniture in front of radiators. Fixing these problems produced a 10% reduction in their gas consumption for these buildings.

3) an aircraft hangar with substantial overheating issues and heating systems running out of working hours. Purrmetrix data demonstrates that upgrading controls will create savings of over £100,000 across the whole estate.

Think you might have a silent controls problem? Get in touch  and let’s talk about how we can help.

How much data is your building generating? Are you getting any value from it?

Even if you are not operating state of the art smart buildings with nearly 30,000 sensors, the chances are that you will soon be swimming in data. Industry estimates suggest that we’re well past 500 million end points from commercial buildings, and heading towards 3.5 billion in the next three years (thanks, Gartner). That’s end points…each one delivering a data stream at rates potentially of many times a minute.

Its a crazy amount of data, and it won’t be tractable without some deep thinking on applications and analytics. If properly harnessed it offers huge scope to improve the efficiency of buildings and their capacity to deliver comfort and improve productivity for the people working in them. For that to happen, though, building operators need to get a bit cleverer about their data and clearer about what their data strategy needs to be.

Where to start with data in your building

A good data strategy will clarify the value of the data being collected and ensure it is fit for purpose – sadly not the case in so many buildings right now. A simple example – consider the difference between a supply air temperature sensor 3M up in an office ceiling and a desk level comfort sensor. This difference is not just location, but also the rate of update and data availability for analysing previous periods. Lower data rates may be good for control applications, but there are certain applications that are only possible with higher data rates.

So data strategy should help flush out what you want from your data, which drives some important decisions about what, where and how frequently to measure.

The best – and simplest – first step is to assess what your goals are for data. What are the really valuable applications? For most commercial buildings the two major categories of time related data – metering data and building management systems – have obvious lead applications – settling energy bills and controlling building services, but they typically need some enhancement to be able to support detailed building analytics.

Data goals for buildings

I’ve been around in the smart building market for some years, and as it overlaps with green building objectives a number of clear applications are beginning to emerge that support the efficiency of buildings and the comfort of occupiers: 

• Optimise energy performance – Match energy usage to the buildings activity
• Additional (retro) commissioning – Providing a regular review of the buildings systems to check they are working as they should
• Measurement and verification – Demonstrating that improvements are performing as anticipated
• CO2 reporting – For external and internal communications
• Permanent environmental monitoring – Ensuring energy efficiency does not compromise building’s delivery of comfort. Identifying wasted space and opportunities for supporting improved productivity
• System innovation in design – Identifying new opportunities for energy savings and improved productivity by making major changes to environment.

From green to brown – how value of data can trickle down

The evidence is that these applications add real value to buildings – green buildings are typically 25 – 35% lower to operate and occupiers report 4% more productivity from staff. Excitingly, it seems there is potential to apply some of these to buildings that haven’t originally been conceived as green or smart, to improve them.

As a quick, scaleable win for occupiers and operators of commercial, data has huge potential, if it is structured correctly. Purrmetrix can help fill in gaps and support your analytics – if you want to know more, do get in touch.

How easy is it to fool a movement sensor?

I can’t be the only person who has been working late at night in an office when suddenly I am left sitting in darkness, because the PIRs (passive infrared) movement sensor that controls the lighting has decided I’m too still.

In fact I know I’m not the only person, because an FAQ from customers who want to use our new movement sensors for measuring office space usage is how sensitive they are. And so we decided to do a little experiment in our office with two sensors, some software engineers and a very bouncy visitor.

We wanted to look at a range of activity levels and locations for sensors, including

• distinguishing between one very active person (moving furniture around), several people talking and interacting and the classic ‘stationary deep thought’ pose beloved of software engineers
• looking at the effect of location, in particular the difference between ceiling and wall mounted sensors. The ceiling mounted sensor was 2.7m off the ground in the middle of the workspace, and the wall mounted sensor was 1.5m off the ground on a column in a direction that covered half the office space.

Over a week, we found the ceiling sensor accurately reported all presence in the office. It is difficult to distinguish short, vigorous bursts of activity from one person – they look very like a few people interacting – but they did typically tend to be shorter in duration.

Meanwhile the wall mounted sensor did exactly what was expected and recorded all activity in the half of the office it could see. In the analysis below it is the light green trace:

Most usefully, our tests reveal it’s very unusual for anyone working at a desk to go for many minutes without some small adjustments of their body or working environment. Perhaps reaching for a pen, scratching your nose, or moving a mouse. It’s perfectly possible for someone who is focussed on their work (take a bow my software colleagues) to record no movement for a minute or more but if data is aggregated in 5 minute or larger buckets then we had a close fit between occupancy and movement.

To avoid over sensitivity, our movement sensors work with a target concept that is about the size of a human limb, so, if you are in Tom Cruise mode the best way not to trigger the sensor may be to practise moving one finger at a time at less than 1 m/minute. You might not get any work done, but that’s OK…no one will know you’re at work.

If you want a slightly more technical explanation of the sensitivity and range of our movement sensors you can find the data sheet here.

I would say it’s a long story…but it isn’t.

Bear in mind when we first started Purrmetrix the thing we were most interested in was temperature. It’s not surprising that organisations spend a lot on maintaining the right temperature – not only is temperature critically important for many processes, it protects expensive assets and can affect productivity. On the other hand, it is variable enough to carry a great deal of information: you can learn a lot about a building from an effective heat map. So it was the perfect place to start in producing useful building analytics.

And yet, we didn’t want to come across as too clinical. It didn’t seem very, well, comfortable. Which was kind of the point.

What is comfortable and also expert at identifying hot spots, is a cat.

And thus the idea of Purrmetrix, and a whole litter of kitten sensors, arrived.