Gas Smart Metering - What's So Hard? Part II

In the previous post Whats so hard Part 1 you can read

Why Is Gas Smart-Metering so far behind Electricity ?There are four fundamental differences on the measuring side of the coin and far more on the management side. 

The post goes on to look at the complexity of measuring Gas Consumption.  In this post the focus is not so much on reading gas meters but making sense of the reading.

For simplicity's sake I'm going to imagine you know have data and can manipulate it as you need. (If you spend much of your time collating data as an energy manager seek help - really!! - almost all aspects of the task can be automated and your time and the need for consistent precision are far too valuable)

So for example using an adequate tool you can maybe average gas consumption by time of week (an averaged "top-hat" profile) and then chart one period against another (maybe filtering to only look at cold days etc).

Average Weekly Gas Consumption Profile

Disclosure : Pushing our own wares for one paragraph...
These examples are by kWIQly (using data from an anonymous office building in Germany) . kWIQly sources the local weather data and collates the smart meter data daily completely automatically - No installation is required and  the user simply accesses in a web browser - We can do this for any building anywhere.

We see seven fairly uniform but spikey gas consumption patterns with slightly lower use on the last day - Sunday.

Average Weekly Electricity Consumption Profile (Same building)

We see much more uniform but electircity consumption patterns with slightly lower use on the last day - Friday, and only base loads on Saturday and Sunday.

Shurely Shum Mishtake - Ed

Yup its crazy - Four points leap to mind:

1. Gas is switched off at midnight and immediately back on again (year round)
2. Though the building is unoccupied Saturdays and Sundays the boilers are fully occupied
3. There are two "jumps" in boiler activity - one when they switch them on at midnight, and another, later when they start moving heat around the building (8:00am - tooltip pops up in kWIQLY not shown in diagram).
4. The eight a.m consumption spike represents the cost of warming all the radiators one a day before they give off heat.

Learning to read these charts is a skill, and one that any energy manager can benefit from as they become more widely available, but the point made in todays blog is that Gas is fundamentally Harder to understand. If you switch a light off you stop consuming electricity  - if you close a heating circuit off, the boilers don't stop firing, instead they fire less efficiently.  Water circuits take time to heat  (also applies to wet chilling) and anything that stores heat has delayed time response to input energy.

So "Why is Gas Smart-Metering so far behind Electricity?" - simply because it is more of an art, and there are fewer practitioners, with less data, less practice and decent tools are not widely available.

I hope these early insights are interesting and that you might point other people to them who could benefit.  (Comments very welcome)

Thanks - We are in this together...

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• Smart meters: Can they save you money on your gas and electricity bills?
• Get Smart - Expert Opinion - Sainsbury's Money Matters
• Smart Metered Energy Savings - Size Matters!

Auto-congratulatory Green benchmarking

What is an auto-congratulatory benchmark?

OK it's a weird term - but the meaning is obvious once explained...

Suppose your sister has five children (mine does), and suppose she lines them up in size order (I have seen her do it) and then she awards a prize to the tallest (ok - now that seems a little unfair). But - if that was all that happened all you might say is "Hey I have a weird kid sister"- (sorry Maggs couldn't resist:)

But...suppose she tells all the parents at the next parent teacher evening that her oldest child was winning tallness awards - positively self-congratulatory right?

So do businesses practice auto-congratulation - I'm afraid so!

OK - So it sounds a little far-fetched, but I have seen an international hotel chain (One of the biggest) get excited that they had an extraordinarilty large number of hotels in the top decile of energy performance in the UK.

When I looked at the source of data (I really could not credit the results without digging a little deeper) I found that this same hotel chain was the source of over 85% of the source data in the national benchmark.

Suppose they had 85 hotels and suppose there were only 15 other hotels (not accurate). Then the probability of having one or more hotels in the top decile could be calculated as follows:

1-(15/100*14/99*13/98*12/97*11/96*10/95*9/94*8/93*7/92*6/91)  = 99.9999999827 %

or put pretty simply - certain (or less than 2 : 10 Billion would they fail on a pure chance basis)

Now that was an auto-congratulatory benchmark - the sort of award that is so safe you would let it look after your children  !

Why is this a problem... Well it extends to whole industries...

It expains why fridges are rated this way in the EU - So that it becomes hard NOT to be green or even dark green - look !

A++	A+	A	B	C	D	E	F	G
<30	<42	<55	<75	<90	<100	<110	<125	>125

refer http://en.wikipedia.org/wiki/European_Union_energy_label


When you see an unbelievable performance - you'd better believe that's exactly what it is !

at  kWIQly - we prefer a different way of looking at performance that avoids these problems

IQ Tests for Building Energy Intelligence

IQ tests are pretty unreliable, a real test of intelligence should have at least the following criteria:


Well-Defined
Quantifiable
Objective
Repeatable


and it is very obvious that so called IQ tests meet none of these with great certainty - though they do point towards a fairly well defined skill-set (that is not intelligence - can you "practice" for intelligence?)


So is it a bit flamboyant to name ourselves kWIQly. The kW aspect is obvious and the "ly"  is as in quickLY - but where do we get the "IQ"?


In this post we will see if we can come up with a definition of Building Energy Intelligence that is meaningful as a metric and fits the criteria listed above. Most important it must be OBJECTIVE - we may suggest it, but we cannot claim it . Why ? - because metrics are simply ideas - which are good to share !


Lets look at some professional metrics...
BTW wikipedia : Profession provides a nice definition from which we can know that stockbrokers and footballers are examples of what professions aren't !


Account - The Books Balance
Doctor - The Patient Survives
Architect - The Building Stands
Energy Manager - ?? - erm  Energy is like  kinda "managed" I guess.


So long as we don't know if energy is "managed" - we cannot even provide a pass/fail let alone a performance metric.


Taking this from another angle energy is used for various purposes.  If the purpose is known and necessary, (eg heating a cubic meter of dry air by 1 Celsius) we know how much energy it takes (Laws of Physics) if done optimally. If we know the efficiency of the process we can predict from the task the energy that is to be used.


So ultimately, if we know what we are doing, and can justify these things - we know how much energy it should take to do it. Nice simple idea.


We argue that in so far as an energy manager knows what must be achieved he can predict how much energy it should take given his available facilities.  Otherwise the energy manager does not know either "what he or she is doing" or "how efficiently it is being done".


We suppose the first metric for Building Energy Intelligence should be the Mean Absolute Deviation (MAD) between primary energy consumption and that predicted at a particular time resolution (eg daily).


To standardize this value is simple (divide MAD / Mean power), and it can easily be applied to benchmarking (per sqft in hospitals etc)


It has been said before that - "you can't manage what you can't measure", but measuring is not managing, and measurement for measurement sake is futile.


Measurements should build on a grasp of the activities occurring and expected (or unexpected) in a building, and the implications that these measurements have. To the extent that energy is managed the implications are known and documented - and it can be said that there is a degree of "Building Energy Intelligence"

Energy Efficient Buildings - Do it for less.

If you want to travel from here to Timbuktu efficiently (and therefore languorously) and are granted choice of :

• Model T Ford (16–25 mpg) 
• F430 Ferrari (11–16 mpg)

It is clear that the car of preference is the Model T Ford - because it (can) travel further on one gallon of fuel. 

But it may not. 

A Model T sitting at traffic lights burns fuel slowly at 0mpg. In doing so it is less fuel efficient than the F430 with rubber burning and pedal crammed to the floor. Think about it benefit vs. fuel spent ! (maybe the F430 gets bonus for a "throaty" growl - but surely not for timeless class and industrial significance).

The point is obvious - energy efficiency depends greatly on how you use the tools you have and not only which tools you have (this makes a potential nonsense of many building benchmarking tools if they aren't applied to reality).

Supply side energy management is commodity management - how do we deliver kWh as efficiently as possible to the point of use, and at the time of use?  It rather assumes an efficient market, and data fed back into that market (demand and supply elasticity) are all beneficial. Smart, however, it is not; any more than a stock-ticker moving across a trading desk is smart. The action of increasing demand, whether real or speculative increases price and volume supplied - and the market is pretty responsive. Old idea - not particularly smart!

Demand side energy management is the opposite of commodity management - a commodity is fungible, meaning that one "bit" of electricity or oil is very like another, and really you buy from the best value supplier (which basically means cheapest). 

The perspective of the energy manager or building operator is different, it is reasonable that they may respond to energy prices rising by switching off least-essential use (ie they must differentiate on the basis of purpose). However, it is only reasonable to assume that they will if there is an element of price elasticity. That is if they are price sensitive.

The traditional concept of "Smart-Meters" is that there is some preference to save energy (motivation), and that the metering provides a flag to show a user how to.  This assumes that either the user watches the "Smart-Meter" like a hawk (which may become tedious), or that control systems start to adjust use automatically verses price (a "smart thermostat") while being able to weigh up lost (or deferred) building services against the financial benefit of so doing.  It sound pretty naive to assume this will happen any time soon in my opinion - not because we lack the technology, or motivation, but because we simply have not established values and metrics for comfort.

Again in my opinion, what may precede this is metering analysis at sufficient diagnostic resolution to know when expenditure is wholly wasted (like the Model T at the traffic lights).

If you look at consumption rates of a gas-fired boiler in the context of demand (the weather, time of day etc), it is largely obvious when it is "sitting at the traffic lights" - there is even a control term for the behaviour dry-cycling which occurs when under no load the boiler switches on and off rapidly (like an unused iron on an ironing board - Note simple smart iron idea !).  This like many inefficiency patterns can be recognised by observing profiles of energy consumption and is the underlying approach at kWIQly.

So to conclude - So long as energy efficiency is about "Doing it for less", the first question should be "Why do it at all?" - If there is no good reason to "keep the engine running", turn it off. If we can diagnose problems remotely and in a scalable fashion from meter data only then energy saving is easy - Bring it on !

Gas vs. Electricity Smart Meter - What's So Hard?

If you are an energy manager, you may have been getting high time resolution monitoring of electricity meter usage for a long time.  Not so much with gas!

Why Is Gas Smart-Metering so far behind Electricity ?