All posts by Editor

Uncategorized

Artificial intelligence and waste avoidance

Effective energy waste avoidance relies crucially on the comparison of actual and ‘expected’ consumptions. Classically we do this on a weekly or monthly basis, using models for expected consumption that are linked to independent driving factors. But there are other ways to skin that cat.

Buildings will in many cases have a characteristic diurnal pattern of demand that can be expressed as a profile at, say, half-hourly intervals. With a large enough group of similar buildings, and taking account of drivers like the weather, it seems possible in theory to create a dynamic template for each building against which its demand can be assessed in near-real-time. The template is just a different way of calculating and expressing expected consumption, but it creates the realistic prospect of daily exception reports. Of course the implied excess costs need to be taken into account, because you need to be able to suppress the clutter of insignificant deviations, prioritise cases for investigation and estimate the value of resolving them, just as you would if you were using a weekly or monthly overspend league table.

The role of artificial intelligence here is to learn what ‘correct’ behaviour looks like and one advantage of this in large estates is that it obviates the need for human analysts to calibrate degree-day regression models for every meter. Another benefit would be the recognition of common abnormalities in profiles. Properly trained with correct human feedback, an AI-based pattern recognition system could in principle recognise symptoms that have occurred before elsewhere and associate them with remedies that have previously been successfully applied.

A further benefit is advanced benchmarking. In classical M&T we know that buildings can be benchmarked by comparing the slopes and intercepts respectively of their degree-day regression lines. A pattern-analysis system can take this more incisive analysis to a whole new level.

I will be interviewing James Ferguson, a keen proponent of AI in energy waste detection, on 15 July 2021 in my “Energy Conversations” series of open video calls. If this is a subject which interests you you can  request a place in the audience here.

Bogus claims

Energy recovery in lifts

Reader Chris B. had seen someone promoting a product  that could be retrofitted to passenger lifts to recover kinetic energy rather than dissipating it in friction brakes. He wrote to ask if it was a plausible offering. 

Certainly there are lift systems that use regenerative braking, that is, motors which turn into generators when switched into reverse to decelerate the descending car. It is a legitimate idea, but usually a feature designed into the installation at the outset. As such it offers other advantages such as reduced heat dissipation in machine rooms. But it’s hard to believe that it would be viable to retrofit an existing installation because the available energy is not as much as you might think, as you can see from this rough calculation making some very optimistic assumptions.

Suppose a lift drops 36 m vertically carrying an excess mass equivalent to ten 80-kg passengers. As gravitational field strength is about 9.8 N/kg its change in potential energy would be 36 x 10 x 80 x 9.8 = 282,240 joule. That’s 282,240 / (3,600 x 1,000) = 0.0784 kWh. If you could harvest all that energy it would be worth approximately one penny. Factor in some more conservative assumptions and realistic conversion efficiency, and the value of the recovered energy is totally negligible.

Why are worthless bolt-on products like this promoted? In the case of products supposedly under development, it is usually to lure naive investors. For readily-available and easily-deployed products like bogus boiler additives and fuel-line magnets, it is to lure naive franchisees.

Learn about energy-saving techniques that actually work at this tutorial: “Energy efficiency A to Z” on 26-27 May

 

Bogus claims

Microwave weirdness

IN MARCH AND APRIL this year several national newspapers, including the normally sober Economist, carried articles promoting the concept of a microwave central heating boiler which could be fitted in place of a gas-fired one. The same story appeared in H&V News, a trade journal.

The originators’ objective is to promote the idea of decarbonising your heating by substituting (renewable) electricity for gas. The articles compare two options: electrifying your existing central heating system versus installing a heat pump. The latter, quite reasonably, they consider costly and not always feasible. But somewhat disingenuously they fail to mention another electrification option which I’ll come back to at the end.

Now suppose for some reason you did want your radiators fed by an electric central boiler. Why opt for the complexity of a microwave one rather than one based on simple resistive immersion heaters? It makes no sense because either way you can only get as much heat out as you put electrical energy in. Microwave sources confer no thermodynamic advantages. The promoters justify the more complex technology because (according to the account published in the Economist) immersion heaters “…must run continuously to deliver water at a suitable temperature. That often warms water which is never used.” Well, er, no. Immersion heaters would be thermostatically controlled, and wouldn’t consume energy that is never delivered as output heat.

Event alert: “Decarbonising heat: practical realities” on 8 July. Details at https://vesma.com/z200

In the version of the story on the Guardian web site, the company claims that the electrical load “will be about the same as an electric oven”. This also makes no sense. A built-in electric oven might be rated at 3 kW while a central heating boiler could quite typically have an output of around 30 kW and an electric version would need input power to match. Indeed according to the piece in H&V News  these microwave boilers can be up to 60 kW in capacity. And therein lies a problem. Even a 30 kW appliance would need a 120-amp mains supply at 250V, and that’s on the assumption that it is a simple resistive load. To put that in context, our whole house is fed through a 100-amp supply. Microwave units, however, have notoriously poor power factor so will inevitably draw much more than 120A for the same 30kW duty, all of which makes claims of quick and easy installation ring somewhat hollow.

The coverage in H&V News is rich in whizzy-sounding technology and buzzwords. For example it says that the heart of the system is termed a “technology stack”, which they say is a “solid-state, robust RF framework that uses configurable and controllable high performance amplifiers to generate energy”. Elevating the merely meaningless to Olympian heights of drivel.  The version of their story in the Economist includes the bizarre assertion that “the pipes that carry the water are also made of microwave-sensitive materials, as is the insulation that lags them”. Microwave-sensitive? Wait… like lasagne? And if the pipes heat up under microwave radiation what’s the benefit of the insulation doing likewise?

The article in H&V News quotes a director of the company claiming that their electric boiler “would cost the same to run as a gas boiler”. At least the Guardian had the wit to expunge that remark from the on-line version of the article. The truth is, if you want to use electricity for heating and a heat pump is not an option, individual room heaters would be the obvious way to go. Apart from being cheaper to fit than a new electric boiler, they would enjoy the advantage of room-by-room controllability.

 

Bulletins (back numbers)

Bulletin 4 May 2021: building insulation; U is for uncertainty

Good morning

FEATURED EVENT: BUILDING INSULATION

This two-hour technical briefing on 19 May covers the materials and techniques currently specified for improving the thermal performance of buildings. It includes revision of basic principles, discussion of the limitations of each type of product, and a summary of relevant UK regulations and standards. Details are at https://vesma.com/z112 and as ever your readers’ discount code is EMR2012.

Other forthcoming events are listed at http://vesma.com/training.

–o–

U IS FOR UNCERTAINTY

When we plot energy consumption against driving-factor values on a scatter diagram, the points don’t fall exactly on the regression line. The degree of dispersion is described by a parameter called the ‘coefficient of determination’, commonly known as R-squared, which tells us how much of the variation in energy consumption is explained by the regression model. When all the points fall exactly on the line, the model explains all the variation in energy consumption and R-squared has a value of one. If there is no relationship between consumption and the chosen driving factor, R-squared would be zero. If R-squared is 0.9 it means that the model explains 90% of the observed variation in energy consumption with the remaining 10% being attributable to errors or factors that were not taken into account.

There are two common misconceptions about R-squared. One is that on a heating system, a low value of R-squared signifies poor control. This is not necessarily the case, as the following thought experiment will show. Consider a well-controlled heating system whose consumption is assessed against a reliable local source of degree-day data. Whatever value of R-squared is observed, if you were to substitute degree-day statistics from a more distant weather station in the regression analysis, R-squared would go down, even though the heating system continues to be well-controlled. So beware: low R-squared might be telling you more about the quality of the model and your data than about the behaviour of the thing you are monitoring.

The other common misconception is that there is a threshold for R-squared (0.75, or 0.9, or whatever) below which your regression model cannot be trusted. There is no such cut-off. If you have chosen the most relevant driving factor and a straight-line model is plausible, you have got the right model and a low R-squared value just means it is not as reliable as it could be. In practice that simply means that a deviation has to be bigger before it can be treated as something that didn’t happen by chance. By refining the model you will improve your ability to discriminate between real faults and random variation. So it’s not a question of do you trust the model or not; the question is: “given a plausible model, how much uncertainty is there in its predictions?”. Hence the idea, introduced in an earlier bulletin, of tuneable +/- control limits on charts showing the history of deviation from expected consumption.

In the next issue: V is for verification of savings. Meanwhile if you missed any earlier issues you can catch up at http://EnManReg.org/azmt

–o–

MAVCON 21: CALL FOR PAPERS

We’ll be running our measurement and verification conference again as a series on Wednesday afternoons starting on 20 October. By popular request the first two sessions will be a refresher on basic principles and good practice, and the final sessions will be aimed at advanced practitioners but open to all. If you have an idea for a presentation (even if you don’t want to do it yourself) please let me know now.

Kind regards
Vilnis

Energy analysis and reporting

SECR in a nutshell

Updated 30/4/21 and 4//4/22

“Streamlined energy and carbon reporting” (SECR) is the term commonly used to describe the regime introduced with the Companies (Directors’ Report) and Limited Liability Partnerships (Energy and Carbon Report) Regulations 2018, Statutory Instrument 1155. This is not a self-contained set of regulations like ESOS; instead it consists of nothing but dozens of amendments to existing company reporting law. In short, undertakings covered by SECR simply need to collate annual total energy and emissions data and give them to their company secretary or accountant for inclusion in the annual report that they already have to prepare.

As this is an extension of financial reporting, compliance will be policed by the Financial Reporting Council, and not, as one might have thought, by the Environment Agency. The good news is that in terms of accuracy and completeness, your SECR reports need only be free of material misstatements, and according to the Government’s published guidance it is fine for a company to omit 2-5% of its energy or emissions if it considers them not to be material in the grand scheme of things.

Who is affected?

SECR applies to all quoted companies, and to unquoted companies and limited liability partnerships (LLP) which meet two of the following three criteria:

  1. At least 250 employees;
  2. £36 million annual turnover or more
  3. Balance sheet of £18 million or more

This is not quite the same as the ESOS regulations, in which an undertaking would be obliged to participate if it met criterion (1) alone.

Undertakings which consumed less than 40,000 kWh in the year being reported do not have to report their actual figures but must still state that they fell below that threshold.

It is fine for a company to omit 2-5% of its energy or emissions if it considers them not to be material

Group reports should include the figures for all subsidiaries apart from those that would be exempt. Under these circumstances a subsidiary need not report its own figures although, of course, it will still need to collate the data for group use.

What must be reported?

The requirement covers energy use and greenhouse gas emissions arising from all use of electricity, gas, and transport fuels. Incidentally the definition of “gas” is not limited to natural gas, but refers to any gaseous fuel so it even includes hydrogen. The inclusion of electricity on an equal footing with other energy sources means that SECR differs from emissions reporting, in which fuels and pirchased electricity are considered under different ‘scopes’. Somewhat bizarrely liquid and solid fuels do not have to be accounted for, unlike in CRC (which SECR supposedly replaces) ESOS and EUETS. Bought-in heat, steam and cooling are included but not compressed air.

Quoted companies must report global figures, but LLPs and unquoted companies only have to declare UK consumption and emissions.

In the main, therefore, any undertaking that already keeps even very basic monthly fuel and electricity consumption records for its fixed assets will have no trouble collating the necessary energy data. Transport fuel, of course, is a different issue. As many an ESOS participant has found, transport fuel data are disproportionately hard to collect relative to its importance in the mix. Luckily, if you can reasonably assert that your transport energy and emissions are not material to the overall picture, you can just leave them out.

My advice would therefore be to look first at transport fuels, decide whether they are material, and if so put resources into capturing the data or estimating the figures.

SECR requires emissions to be reported as well as energy consumptions. The necessary factors are published by the government and undertakings would be well advised to set up a methodical procedure for carrying out the calculations, because they must include details of their methodology alongside the data that they report.

Undertakings must report intensity metrics, of which an example would be kWh per unit of saleable product output. The idea is that stakeholders will be able to see, once a year, what progress the company is making in energy efficiency. This is actually a somewhat naïve and fanciful aim, given all the ways that such simple ratios can be distorted by external factors nothing to do with energy performance. Even more implausible is the idea of making ‘benchmarking’ comparisons between enterprises, but that is the government’s stated objective.

Companies are entitled not to report intensity metrics if, in their opinion, it would be prejudicial to their interests to do so. For example it might entail disclosing sensitive information about their sales volume. One option is to quote a metric based on financial turnover (which is already disclosed anyway). This may not be meaningful, but then neither is anything else they might report.

Finally, annual reports must now include descriptions of the principal measures taken to improve energy efficiency during the year in question, if there were any.

What is the compliance deadline?

Energy, emissions, intensity metrics and associated methodologies must be stated in annual reports covering accounting years starting in April 2019 or later, so by now all companies will have had full reporting years covered by the scheme (the last wave was for reporting years ending in February 2021). Actual report submission deadlines fall six months later for public companies, nine for private companies.

See links to SECR resources

Bulletins (back numbers)

Bulletin 26 April: realities of decarbonisation; T is for targets

Good morning

FEATURED EVENT

We’re hearing a lot in the news, including ambitious government announcements, about ‘decarbonising heat’. Most of the media coverage is about the domestic sector but the chances are that, as a reader, your focus is more on commercial, public-sector or industrial buildings or larger-scale residential facilities. You may have heard that experience with biomass and heat-pump installations has not always been positive, and you will want to understand the problems and pitfalls. You may also be getting questions about how hydrogen in the public supply might play out, and need ready answers.

We’ve therefore arranged a half-day intensive workshop on the practical realities of decarbonising heat in non-domestic buildings, with a team of experienced experts to talk about the lessons that have been learned and the technical and other issues that organisations face in coming decades. Details are at https://vesma.com/z200 and as ever your readers’ discount code is EMR2012.

–o–

T IS FOR TARGETS

In energy management the word ‘target’ has two distinct meanings. The first is the ‘aspirational’ target, usually set from on high without regard to practicability, to reduce consumption by x% within a certain time. It’s not a particularly smart approach. In fact in a large organisation it is almost guaranteed to fail, and here’s why. Top management sets a reduction target of x%. There being no easy, transparent and equitable way to do anything else, all departments adopt the same x% target and pass it down the chain to the lowest-tier managers. For some of them, x% is impossible to achieve so they fail. For others it will be achievable or even easy. They will save x% and then probably stop trying. Why would they over-achieve? They have other work to worry about and anyway we all know if we beat our target our managers will just give us a harder target next time. So take the roughly x% saved by the successful ones, blend this with the lower savings achieved by the first group, and you have an aggregate failure.

For me, achievability is key, and when I talk about a performance ‘target’ I mean just maintaining the best performance you can demonstrably achieve. In other words, avoid accidental excess consumption (see next article). This may not be ambitious but it is worth doing; using regression or other modelling methods supported by cusum analysis it is possible to ensure that everything has its own achievable performance characteristic. The word ‘achievable’ is crucial: it’s much more likely to get buy-in than the megaphone-management targeting that I described earlier.

I said achievable ‘characteristic’ because my concept of a target differs from common understanding in another important respect. My ‘target’ is not expressed as an annual kWh figure, nor indeed as a performance indicator, but in terms of an expected consumption quantity dynamically linked to relevant driving factors, meaning that you can track performance at whatever interval you want.

–o–

£50 FOR THE CHARITY OF YOUR CHOICE?

If you’ve ever stumbled over something that was wasting energy in a manner that was easily avoidable, I’d like to hear about it. Every month we’ll donate £50 (or the equivalent) to the charity nominated by the person whose entry is deemed the best by our guest judge. Details at http://EnManReg.org/starspot

Kind regards
Vilnis

April fools

Make appliances rate again

DATELINE 1 APRIL, 2021: The Government is keen to nudge people to choose more energy-efficient household appliances and for many years has helped consumers by getting manufacturers to put energy labels on products, typically rating them A to G to signify that they are more or less energy efficient (a concept too complex for most people to grasp). And for people who find the concept of A, B, C etc too complex to grasp they add coloured arrows of different lengths. The shorter the arrow, the higher the efficiency.

The march of progress has caused problems because many products are now more energy efficient than the bureaucrats foresaw. They are crowded into the ‘A’ rating band, and unfortunately there are no letters before A in the alphabet so ‘A’ is now sometimes subdivided into A+, A++ and A+++. However, most people find this concept too difficult to grasp, so the efficiency scales for affected appliances will be regraded A to G so that for example what was A++ will now become B, A will become D, and so on (they will take F off).

Meanwhile a rival scheme for washer-dryers caught my attention. This gives a three-letter rating signifying the efficiencies of washing, spinning, and tumble-drying parts of the cycle. Thus a machine that is in the most efficient category in every respect gets an ‘AAA’ rating. With a bit of forethought they could have started later in the alphabet to allow room for future improvement. They could even have helped people by using the sequences W to Z for Washing, S to V for Spinning, and D to G for Drying. Then a machine currently labelled ‘ABC’ would become ‘WTF’.

Project profiles

Another satisfied customer

Delighted to receive this unsolicited testimonial from a client who is moving to a new job:

“Thanks so much for the fantastic service you have offered over the years.  Vesma has consistently provided [our company] with the kind of flexible, responsive service that has met our demand for an innovative approach to energy management time and again.  I will continue to recommend your training and consultancy services to others.”

Credit should go to my fellow-director Daniel Curtis who developed the innovative but simple data infrastructure we built our services on, and who was generally the front-line responder when it was needed.

Energy analysis and reporting, Uncategorized

Control charts in energy performance monitoring

Once you have discovered how to routinely calculate expected consumptions for comparison with actual recorded values, you can get some very useful insights into the energy behaviour of the processes, buildings and vehicles under your supervision. One thing you can do is chart the history of how actual and expected consumption compare. In this example we are looking at the daily electricity consumption of a large air-compressor installation:

Comparison of actual daily consumptions with what they should have been given the output of the compressors

The green trace represents expected kWh (computed by a formula based on the daily air output) and the individual points represent the actual metered kWh. Most of the time the two agree, but there were times in this case when they diverged.

It is illuminating to concentrate on the extent to which actual consumption has deviated from expected values, so in the following chart we focus on the difference between them:

The difference between actual and expected consumption.

There will always be some discrepancy between actual and expected consumptions. Part of the difference is purely random, and the limits of this typical background variation are signified by the red dotted lines. If the difference goes outside these bounds, it is probably because of an underlying shift in how the object is performing. In the above diagram there were three episodes (one moderate, two more severe) of abnormal performance. Significant positive deviations (above the upper control limit) are more usual than negative ones because consuming more energy than required for a given output is much more likely than using less.

For training in energy consumption analysis look for ‘monitoring and targeting’ at VESMA.COM

In a well-constructed energy monitoring and targeting scheme, every stream of consumption that has a formula for expected consumption will also have its own control limit. The limits will be narrow where data are reliable, the formula is appropriate, and the monitored object operates in a predictable way. The limits will be wider where it is harder to model expected consumption accurately, and where there is uncertainty in the measurements of consumption or driving factors. However, it is not burdensome to derive specific control limits for every individual consumption stream because there are reliable statistical methods which can largely automate the process.

Control charts are useful as part of an energy awareness-raising programme. It is easy for people to understand that the trace should normally fall between the control limits, and that will be true regardless of the complexity of the underlying calculations. If people see it deviate above the upper limit, they know some energy waste or losses have occurred; so will the person responsible, and he or she will know that everyone else could be aware of it as well. This creates some incentive to resolve the issue, and once it has been sorted out everyone will see the trace come back between the limits.

Energy analysis and reporting, Uncategorized

Demand visualisation with heatmap views

The principle

Widespread adoption of automatic meter reading has given many energy users a huge volume of fine-grained data about energy consumption. How best to use it? A ‘heat-map’ chart is a powerful visualisation technique that can easily show ten weeks’ half-hourly data in a single screen. This for example is the pattern of a building’s gas consumption between November and January:

Each vertical slice of the chart is one day, running midnight to midnight top to bottom, with each half-hourly cell colour-coded according to demand . This creates a contour-map effect and when you look at this specifi example, you can see numerous features:

  • Fixed ‘off’ time;
  • Optimised startup time (starts later when the building has not cooled down as much overnight);
  • Peak output during startup;
  • Off at weekends but with some heating early on Saturday mornings;
  • Shut-down over Christmas and New Year; and
  • A brief burst of consumption during the Christmas break, presumably frost protection.

Further examples

This building’s gas consumption pattern is quite similar to the previous one’s (they both belong to the same organisation), but the early-morning startup boost is much more evident and occurs even during the Christmas and New Year break:

Next we have a fairly typical profile for electricity consumption in an office building. What is slightly questionable is the higher daytime consumption near the start (April) compared with the end (June). This suggests the use of portable heaters. Note also that the peak half-hourly demands can easily be seen (Friday of the second week and Wednesday of the fiifth week). In both cases it is evident that those peaks occurred not because of any specific incident but because consumption had generally been higher than usual all day:

In this final example we are looking at short-term heatmap views of electricity feeding a set of independent batch processes in a pharmaceutical plant. The left-hand diagram is the actual measured consumption while the right-hand diagram is the expected profile based on a mathematical model of the plant into which we had put information about machine scheduling: