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Energy jargon buster

Absorption chiller: Cooling apparatus driven by heat alone

Accuracy: Degree to which a measurement reflects actual reality

AHU: See Air handling unit

Air curtain: Sheet of heated air projected across an open doorway to prevent discomfort from draughts; usually in retail premises

Air handling unit: Air handling unit:  assembly of fan, filters, etc  for supplying air to or extracting air from a ducted distribution system

Ammeter: Instrument for measuring electric current

amp (A): Unit of measurement of electric current

AMR: Automatic meter reading

Anemometer: Device to measure air velocity

Audit, energy: Systematic review of energy-using systems and associated procedures with a view to identifying opportunities for energy saving

For training in energy management topics see  vesma.com/training

Ballast: Component of electrical control gear in a fluorescent light fitting.

BEMS: Building energy management system:  computerised control and monitoring equipment for regulating time and temperature schedules etc

BEMS: See Building energy management system

Blending valve: See Mixing valve

Blowdown: Removal of a fraction of boiler water to enable removal of sludge and dilution of dissolved solids

BMS: See Building energy management system

Building energy management system: Computer system which controls the operation of heating, ventilation, air conditioning, lights and other energy services in buildings

For training in energy management topics see vesma.com/training

Calorific value: Energy content of fuel per unit mass or volume

Capacity charge: Rental paid for an electrical supply connection capable of carrying a certain current

CFL: Compact fluorescent lamp:  plug-in substitute for a light bulb.

Chiller: Machine for cooling air, water, etc

CHP: See Combines heat and power

CNG: Compressed natural gas

Code 5: In UK context, a meter for registering half-hourly electricity consumption for loads above 100 kW

Coefficient of performance: In refrigeration systems, the ratio of output cooling power to input electrical power.

Cogeneration: See Combined heat and power

Colour rendering: How effective a given light source is at allowing discrimination between colours

Colour temperature: Numerical value describing a light source in terms of how ‘warm’ or ‘cool’ it appears

Combined heat and power: Electricity generation in which part of the waste heat is put to use

Compensator: Control device to regulate circulating water temperature in a heating system, reducing temperature when heat demand is low and vice versa

Condensate: Water resulting from the cooling of steam

Condenser: In a refrigeration circuit, the component through which heat is rejected.

Conduction losses: Heat losses through the walls, roof, floors, doors, windows and other solid elements of the building envelope.

Constant temperature: In heating system, regime in which circulating water is maintained at a fixed temperature and control of heat output is effected by regulating flow to heat emitters

Convection losses: Heat lost in air leaving the building through draughts and deliberate ventilation

Convector, fan assisted: Heat emitter on a central heating system in which a fan blows room air across a heat exchanger

Convector, natural: Heat emitter on a central heating system, usually enclosed in a cabinet with inlet and outlet vents, which warms room air without the assistance of a fan

Cooling tower: Device in which water used for cooling something gives up some of its heat to the air, enabling it to be recirculated in a closed loop. May be ‘dry’, employing a sealed heat exchanger, or ‘wet’ in which case evaporation of the water increases the cooling effect

CoP: See Coefficient of performance

Coriolis meter: Technology for measuring the flow rate of for example dust-laden gases; the flow rate affecting the resonant frequency of a U-shaped section of vibrating pipe

Correction factor: In the context of natural gas, the factor by which its metered volume must be multiplied to account for its pressure and temperature being other than that assumed as standard

CT: In heating system:  see Constant temperature;  in metering see Current transformer

Current: Rate of flow of electrical energy

Current transformer: Device placed around one conductor of an electrical supply cable to convert the current flowing in it into a safely-measurable signal for input to a meter

Cusum: Cumulative sum of deviance

CV: See Calorific value

For training in energy management topics see vesma.com/training

Damper: Flap used to control air flow in a duct

Data logger: Device for recording data from energy meters, temperature probes and other instruments

Dead band: Switching differential between for example the activation of heating and cooling in a space; sometimes in a thermostatic control the spread between temperatures that trigger changes of state each way between on and off.

Degree days: Measure of how hot or cold the weather was over a given interval, typically a week or month, in a given location or region. Used in an analogous fashion to production output as the driving factor for heating opr air-conditioning energy consumption.

Deliquescent: Dessicant material which dissolves in the water it absorbs

Delta: Connection method for three-phase devices where the load is connected from phase to phase without a neutral (cf star)

Demand, maximum: See Maximum demand

Dessicant: Material which absorbs water vapour; used for example in compressed-air dryers

Deviance : Difference between actual and expected consumption

Dew point: Air temperature at which moisture will begin to condense; also known as saturation temperature

Dichroic: Attribute of a filament spotlamp whereby the reflector allows heat to escape through the back

Direct-fired heater: Heater in which fuel is used directly, as distinct from a heat emitter on a hot-water or steam circuit with centralised combustion.

Discounted cash flow: Method of accounting for future expenditure and receipts which explicitly recognises that postponing a cash flow diminishes its value in present terms

Driving factor: Recurrent and measurable determinant of energy consumption, such as production output or degree-day value.

Dry cycling: Excessive starting and stopping of boilers, especially when supporting each other’s standing losses

For training in energy management topics see vesma.com/training

Economiser: Heat recovery unit specifically for preheating boiler water from heat in exhaust gases

Efficiency: The ratio of useful output to energy input

Electronically-commutated motor: machine, typically for DC or single-phase AC supplies, which turns a permanent-magnet rotor by synthesising of a rotating magnetic field

Embedded generation: Electricity generator owned and operated by the organisation which uses the output

EMS: See Building energy management system

Energy: Electricity, gas, oil, steam, compressed air or other like medium

Energy performance coefficient: ratio of actual to expected consumption; a numerical index of energy performance much less susceptible to distortion than specific energy ratio

Enthalpy: Total energy content of a fluid, representing both thermal and mechanical energy that could be extracted from it

Enthalpy control: Control regime in air-conditioning systems to optimise the energy requirement for regulating both humidity and temperature

Evaporator: In a refrigeration circuit, the component through which heat is absorbed

Expected consumption: rational estimate, either based on the known previous relationship between consumption and one or more relevant driving factors , or calculated from first principles

For training in energy management topics see vesma.com/training

Far infra-red: ill-defined term most commonly associated with fake energy-saving products; usually denoting heat radiated from surfaces at no more than about 80°C

Firetube: Boiler design in which combustion gases pass through submerged tubes

Flash steam: Steam resulting when hot condensate is dropped to a lower pressure

Flue: Duct through which combustion products pass en route to the chimney

Flue gas: Combustion products

Fluidised bed: Combustion not in an open flame but within a bed of loose powder

Forced draught: Fans which drive combustion air into a boiler (cf Induced draught)

Free cooling: Cooling effect achieved by drawing in cold fresh air rather than chilling recirculated air

Frost protection: Automatic application of heat to prevent freezing damage out of hours

For training in energy management topics see vesma.com/training

GCV: See Gross calorific value

Geothermal energy: Heat drawn from deep underground at sufficiently high temperature to be directly useable (cf Ground-source heat pump)

GLS: General lighting service:  conventional filament lamp

Gross calorific value: Total chemical energy content of a fuel, including what would be recovered by condensing the water vapour from the products of combustion. Also called higher calorific value. Cf Nett calorific value.

Ground-source heat pump: Reverse refrigeration cycle which cools the ground in order to provide a heating effect from its condenser (cf Geothermal energy)

GSHP: See Ground-source heat pump

For training in energy management topics see vesma.com/training

HCV: See Gross calorific value

Heat: Thermal energy which can raise something’s temperature, or melt or boil it.

Heat emitter: Radiator, convector, or other device delivering heat in a heating system

Heat exchanger: Device within which a hot fluid stream gives up heat to a cold stream while maintaining separation between the two

Heat map: Graphical display of profile data in which for example demand levels are depicted as colour contours on a matrix in which each column represents one day, midnight to midnight.

Heat pipe: Closed length of tube containing a small charge of volatile liquid and a wick; transfers heat end to end through fluid boiling at one end and condensing at the other, returning via the wick

Heat pump: Refrigeration unit operated in reverse, providing heat at moderate temperature by cooling either the outside air or the ground nearby.

Heat wheel: Form of regenerative heat recovery in which the heat storage matrix is in the form of a wheel rotating continuously between the hot and cold streams.

hertz (Hz): Unit of measurement of frequency:  cycles per second

Higher calorific value: See Gross calorific value

Historical baseline performance characteristic: Performance characteristic which applied at the outset of the energy management campaign

For training in energy management topics see vesma.com/training

Incidental gains: Heat gains in a building arising from lights, equipment, uninsulated hot surfaces, occupants, sunshine etc..

Induced draught: Fans which draw exhaust gases from a boiler (cf Forced draught)

Inhibitor: Chemical additive in boiler water to reduce corrosion

Insulation: Material which reduces the conduction of heat

Inverter: Electrical device for converting direct to alternating current; component of a variable-speed drive

joule (J): Unit of energy: one watt-second

For training in energy management topics see vesma.com/training

kelvin: (K) unit of temperature difference

Landfill gas: Methane emanating from waste-disposal sites and collected as a fuel

Latent heat: Heat required to melt or vaporise a substance; or heat released when a vapour condenses or a liquid solidifies. Notwithstanding the release or absorption of heat, the change of state between liquid and solid or vapour occurs without a change of temperature.

Load factor: Ratio between actual output or input and the maximum theoretically possible with continuous operation at full output or input.

Logger: See Data logger

LPG: Liquefied petroleum gas

lumen: Unit of light output power

Luminaire: Light fitting including reflector, lamp holder, control gear and lens etc

lux: Measure of the light incident on a surface per unit area

LV: Low voltage

For training in energy management topics see vesma.com/training

M&T: See Monitoring and targeting

Maximum demand: In UK context, the peak electrical power drawn over any half-hour period in a month

Mercury discharge: Type of fluorescent lamp typically used for floodlighting

Metal halide: Type of filament lamp

Mixing valve: In a Variable temperature heating circuit, the valve which regulates flow temperature by blending water from the boiler(s) with cooler water returning from the heating system. Also called a three-port valve as it has two inputs and one output connection.

Monitoring and targeting: Systematic assessment of actual against expected consumption by means of weekly (usually) overspend league table augmented by analysis tools to assist in target-setting and diagnosis of abnormal performance.

Motorised valve: Valve actuated by an electric motor under the dictates of a control system

MV: See motorised valve

For training in energy management topics see vesma.com/training

Night blind: Insulating blind on chilled display cabinet to reduce cooling requirement out of hours,

NOx: Oxides of nitrogen generated as a by-product of combustion

NTP: Normal temperature and pressure:  reference used for correcting volumes and densities (0°C and 1.013 bar); cf STP, RTP

For training in energy management topics see vesma.com/training

Optimum start: Time-control regime which postpones startup, usually of heating boilers, to the latest possible time commensurate with achieving desired internal conditions at the required time.

Orifice plate: Restriction placed in a gas, air, or steam line to create a measurable pressure drop from which flow arte can be inferred

OSC: Optimum start control

Overspend league table: Weekly (usually) or monthly report in which deviations from expected consumption are ranked in descending order of excess cost.

For training in energy management topics see vesma.com/training

Passive infra-red: Technique for detecting the presence of people in a space

Performance characteristic: Mathematical relationship between energy consumption and one or more driving factors

Phase: Alternating-current electrical supplies are either single-phase (delivered through one pair of wires) or three-phase (delivered through three wires, the current waveform in each being one-third of a cycle behind or ahead of the others).

PIR: See Passive infra-red

Polyphase: arrangement of electrical supply in which (most commonly) three lines are energised by alternating current one-third of a cycle apart

Power:  Rate of flow of energy

Power factor: In alternating-current electrical supplies, the ratio of useful power delivered to the theoretical maximum possible for the given current and voltage

Precision: Degree of resolution in a measurement

Profile: Pattern of demand over a day, week, or other chosen interval.

For training in energy management topics see vesma.com/training

Radiant: Heat transfer without physical contact

Receiver: Pressure vessel for storing compressed air.

Recuperator: Heat-recovery device

Reflective: property of material e.g. aluminium foil which impedes the flow of radiated energy across a transparent medium

Refractory: High-temperature insulation found in furnaces and kilns

Regenerator: In heat recovery, a pair (usually) of heat stores which take it in turns to collect heat from a hot stream and return it to a cold stream

Regression line: Best-fit line through points on a scatter diagram

Relative humidity: The ratio between the amount of water vapour present in the air and the theoretical maximum at the prevailing temperature

Repeatability: Degree to which measurements vary consistently irrespective of accuracy

Rewind: Repair of electric motor by replacement of burned-out windings

RTP: Reference temperature and pressure used for correcting volumes and densities (25°C and 1.013 bar) cf NTP, STP

Run-around coil: Split heat-recovery system in which heat is recovered to an intermediate fluid circuit, allowing heat collection and delivery to be in different places

For training in energy management topics see vesma.com/training

Sankey diagram: Diagrammatic representation of energy flows through a process or organisation in which the magnitudes of flows are represented by the widths of pathways

Saturation temperature: See Dew point

SCADA: See Supervisory, control and data acquisition

Scatter diagram: Chart showing the relationship between one value and another:  commonly showing weekly energy use (vertical or x axis) against driving factor (horizontal or y axis)

Sensible heat: Heat which when added to or removed from a body, alters its temperature

Sequencing: Usually of boilers but also applicable to chillers, compressors, and other ganged utility equipment:  a control regime which regulates how many units are enabled so as to match the load.

Smart meter: Consumption meter which is capable of recording data at frequent intervals for onward transmission, normally with two-way communication to facilitate remote disconnection of the user, reporting, etc

Smoke pump: Device to measure the level of soot present in flue gases when testing oil and coal-fired appliances

SON: Sodium discharge lamp giving a pure yellow light (commonly used for street lighting)

Specific energy ratio: simple ratio of energy input to (usually) product output. Supposedly an indicator of energy performance but highly susceptible to distortion.

Specific heat: Property of a material expressing the amount of heat required to raise its temperature by one degree

Stack: Chimney

Stand-alone control: Time or temperature control device that operates independently (as distinct from an Outstation)

Standing loss: Incidental heat loss from equipment incurred regardless of demand

Star: Connection method for three-phase devices where the load is connected between each phase and neutral (cf delta)

STP: Standard temperature and pressure:  reference used for correcting volumes and densities (15.5°C and 1.013 bar); cf NTP, RTP

Sun pipe: Internally-reflective tube used to conduct daylight into an internal space where conventional rooflights cannot be used.

Supervisory, control and data acquisition: Computerised control and monitoring equipment for industrial process plant

Survey, energy: Review of energy-using systems with a view to identifying opportunities for energy saving

Switching differential: See Dead band

Synchronous motor: AC machine with permanent-magnet rotor which rotates exactly at supply frequency or submultiple thereof; absence of rotor winding giving reduced losses

For training in energy management topics see vesma.com/training

Target performance characteristic: Performance characteristic representing the best achievable consumption relative to appropriate driving factors

Tariff: Table of charges; typically understood as applying to supplies other than those negotiated under contract

TDS: See Total dissolved solids

Temperature: Measure of how hot something is

Thermocouple: Temperature-measuring device exploiting the small voltage developed when a junction between dissimilar metals is heated

Thermostatic radiator valve: Direct-acting device for regulating heat output from a radiator

Three-port valve: See Mixing valve and diverting valve

Total dissolved solids: Measure of the concentration of dissolved salts in boiler water

Trace heating: Heating applied to pipes in order to prevent the contents solidifying

Transformer: Device for converting alternating-current electricity from one voltage to another.

TRV: See Thermostatic radiator valve

Turbine: Rotating device for converting (typically) steam into mechanical power; also found on a small scale as a fluid-metering technology

Two-port valve: Straight-through valve giving on/off or regulated flow

For training in energy management topics see vesma.com/training

U-value: Property of an element of the building envelope expressing how easily heat flows through it per square metre of surface area

Vapour-compression chiller: Cooling apparatus driven by mechanical power

Variable air volume: Regime for ventilation air distribution where the supply of cooling is regulated by changing the volume of air distributed

Variable refrigerant volume: Regime for regulating cooling power in an air conditioning system

Variable temperature: In heating system, regime in which the circulating water temperature is varied to limit heat output according to likely demand (see also Compensator)

Variable-speed drive: Electronic device which alters the mains frequency fed to an electric motor, causing it to rotate at a different speed

VAV: See Variable air volume

Venting: Removal of air from, for example, steam circuits

Venturi: Tapering constriction in pipework used as a means of inferring flow rate from the pressure drop in the throat

Viscosity: Property of a fluid which determines its resistance to flow

volt (V): Unit of measurement of electric potential or driving force

Vortex meter: Gas, air or steam meter in which flow rate is inferred from the frequency of eddies shed by the fluid passing over a bluff body

VRV: See Variable refrigerant volume

VSD: See Variable-speed drive

VT: See Variable temperature

watt (W): Unit of power

HVAC interlocks

It’s like a curse. Waking up last Wednesday to a view of the full moon reflected off the Adriatic in the pale light of dawn, I opened the sliding door to the hotel balcony to take a snapshot. As I did so I heard the air conditioning fan stop and there in the pale light of dawn I saw a magnetic reed switch on the door frame, evidently linked to the fan-coil unit control. “Brilliant” I thought: “a picture of that will be perfect for my session at Hotel Energy 17”.

To be fair to myself I did photograph the moonlit Adriatic first and the interlock switch later.

Hotel Energy 17 is on 11 May 2017 in Birmingham, UK.

More choice for electricity users?

When the UK’s gas and electricity industries were opened up to competition it must have irked energy suppliers that there was nothing they could do to differentiate their product from their competitors. “The same gas through the same pipes” is about as far from a unique selling proposition as it’s possible to get; but all that is set to change in the electricity industry thanks to innovative smart-energy startup Brain Power Limited.

Some of the mains supply waveforms available from BPL

BPL’s marketing experts have taken inspiration from current trends such as voltage optimisation, variable frequency drives, and power quality monitors to create exciting new electricity supply options that they describe as “fit for the age of smart meters and artificial intelligence”. Out is the bland sine-wave alternating current (top) that has been the staple for public electricity supply in the UK for 70 years or more: “in” is a spectrum of waveforms ranging from the inexpensive square wave to the edgier sawtooth (bottom) and, for the connoisseur, designer waveforms like ‘ogive’ (second from top) which co-ordinates beautifully with Victorian architectural features. “The great thing about these non-sinusoidal waveforms is that they are really rich in higher harmonics”, said a BPL spokesman.

There will be voltage options for every taste as well. 261 volts could appeal to musicians who will appreciate a voltage that equals the frequency of middle C. Nerds may go for 256 volts (because it is a “power” of 2). Initially available in single and three-phase supply only, BPL is rumoured to be releasing five and even thirteen-phase supplies after Brexit is complete, when customers will also be able to cast off the shackles of 50 cycles per second mains frequency.

Asked whether their catalogue will contain DC as well as AC options, BPL said that would be possible but only with batteries, which would be “charged extra”.


Bulletin issued on 1 April to promote Hotel Energy 17

Errors in solid-state electricity meters

Recent press reports suggest that some types of electricity meter (including so-called ‘smart’ meters) are susceptible to gross errors when feeding low-energy lamps, variable-speed drives and other equipment that generates electromagnetic interference.

According to an investigation and review by metering expert Kris Szajdzicki, such measurement errors do occur and their magnitude depends upon the current-sensing technology used by the meter, although the effect may be negligible in normal situations in the domestic market. However, potential for gross error remains in unfavourable circumstances, particularly in industrial or commercial installations or where there is deliberate intent to fool the meter.

Kris has made his assessment available here.

Fuel savings from system water treatment: limits of plausibility

Just how big a saving is it possible to achieve with a product which improves heat transfer in a ‘wet’ heating system (one which uses circulating water to feed radiators, heater batteries or convectors)?  It is an important question to answer because suspect additives claiming to reduce losses through water treatment are becoming prevalent, making claims in the range of 10-20%, while air-removal devices have been claiming up to 30%. It is possible to show that the plausible upper limit is of the order of 7%  and that this would be achievable through good routine maintenance anyway.

To work this out we first break the system into its two major components: the heating boiler (which in reality may be two or more plumbed in parallel) and the building, which represents the heat load. The first thing we can say is that if the heating in the building is maintaining the required temperatures, the thermal load which it presents to the boiler will not be affected by internal heat transfer coefficients. If heat transfer in the heat emitters is impeded, then either the circulating water temperature will rise or control valves will be open for a greater percentage of time in order to deliver the required heat output, or both; either way, the net heat delivered (and demanded from the boiler) is the same.  So water treatments will not affect the heat demanded from the boiler; their only effect will be to improve the efficiency with which the boiler converts fuel into useful heat.  Let us consider how this can be done. Consider the routes by which energy is lost in the boiler:

  1. Standing losses from the boiler casing and associated pipework and fittings;
  2. Sensible heat loss in the exhaust gases. This is the energy that was needed to elevate the temperature of the dry products of combustion (i.e. excluding latent heat);
  3. Latent heat losses, e. the energy implicitly used in converting water to vapour in the exhaust (it is this heat which is recovered in a condensing boiler);
  4. Unburned fuel (carbon monoxide or soot).

Which of these could be affected by water treatment and which would not?  Standing heat loss is sensitive only to the extent that the external surface temperature of the boiler might differ with and without water-side scaling. As such losses would only be about 2% of the boiler’s rated output in the first place, we can safely take the effect of variations to be negligible. Latent heat losses would not be affected because they are solely a function of the quantity of water vapour in the exhaust, and that is fixed by the chemistry of combustion and in particular the amount of hydrogen in the fuel. Unburned fuel losses will not be affected either. They are determined by the effectiveness of burner maintenance in terms of air/fuel ratio and how well the fuel is mixed with the combustion air.

That just leaves sensible heat losses.  Two things can cause higher-than necessary sensible heat loss. One is to have excessive volumes of air fed through the combustion process, and the other is having a higher-than-necessary exhaust gas temperature.  Excess air is self-evidently totally unrelated to poor water-side heat transfer, but high exhaust temperatures will definitely occur if the heat transfer surfaces are dirty or scaled up.  With impaired heat transfer the boiler cannot absorb as much of the heat of combustion as it should, or to look at it a different way, higher combustion-product temperatures are needed to overcome the thermal resistance.

Elevated stack temperature, then, is the only significant symptom of water-side scaling.  So how high could that temperature go, and what are the implications?  Most people would agree that an exhaust temperature of 250°C or more would be highly exceptional and values of 130°C to 200°C more typical.  Now let us suppose for the sake of argument that the exhaust gases in a reasonably well-maintained boiler contain 4% residual oxygen in the exhaust and have a temperature of 130°C, with (to make it realistic) 200 parts per million of carbon monoxide. The stack losses under these conditions will be:

4.2% sensible heat in dry flue gases

11.2% enthalpy of water vapour

0.1% unburned gases.

This leaves a net 84.5% as “useful” heat but we should deduct a further 2% for standing losses, giving 82.5% overall thermal efficiency as our benchmark.

Now let’s suppose that the same boiler had badly fouled heat transfer surfaces, raising the exhaust temperature to 300°C —  way in excess of what one might normally expect to encounter.  Under these conditions the stack losses become:

10.4% sensible heat in dry flue gas

12.7% enthalpy of water vapour

0.1% unburned gases

So we now have only 76.9% “useful” heat which, after again deducting 2% standing losses, means an overall efficiency of 74.9%, compared with the 82.5% benchmark.  The difference in efficiency between the dirty and clean conditions is

(82.5 – 74.9) / 82.5 = 6.8%

and this figure of about 7% is the most, therefore, that one could plausibly claim as the effect of descaling a heating system whose boilers are otherwise clean and reasonably well-tuned. In fact if the observed stack temperature before treatment is lower, the headroom for savings is lower too.  At 200°C the overall efficiency would work out at 81.4% and the potential savings would be capped at about 3%.

Three points need to be stressed here. Firstly, just measuring the flue gas temperature will tell you accurately the maximum that a boiler-water additive alone could conceivably save. Secondly, you cannot be sure the problem is on the water side anyway: it may be fireside deposits. Thirdly, all these potential savings should be achievable just with good conventional cleaning and descaling.

 

Attitudes to energy: a radical survey approach

Six years or so ago I was asked to help with an energy awareness and motivation campaign at a major conference and banqueting venue. One of the elements I was responsible for was the initial attitude survey, and I decided to approach it in a slightly unusual way, inspired by two textbooks* that I use in training workshops.

There were a couple of psychological phenomena that I wanted to exploit. One was ‘social proof’, the tendency of individuals to act in a way that they think other people like them would act in the same circumstances; the other was the power of informal friendship groups, which tend to bind people more closely than any formal organisational relationships. Also, given that I was dealing with waiters, porters, cleaners, cooks and security guards, I knew from experience that an on-line survey (fashionable at the time) was not the way to go because many of them would not have been able or willing to respond that way. It had to be paper.

Furthermore I wanted to get away from multiple-choice questions. We all know that the reply we would choose is never offered, and I was smarting from an an earlier staff survey for the Environment Agency in Wales, in which people had bombarded the free-text comment boxes with valuable thoughts. Lots and lots of valuable thoughts. So I did two things. I made the questionnaire one page, with just four open-ended questions, and I asked people to talk through the questions with their friends and come up with group responses if they could (otherwise to report dissenting views). The four questions I asked were:

  • Do you think there is significant energy waste at XXX? If so, what and where, and whose job should it be to reduce it?
  • What other aspects of work are more important than saving energy?
  • If you think energy saving is important, why?
  • Does anyone in the group feel they would benefit from special training to help them work in a more energy-efficient manner? What would they like to know more about?

Normally for an organisation with hundreds of staff you would never do this; you would go mad analysing the replies. But with group responses, you have numerically only a fraction of the material to sift through. You are also getting people to discuss the matter in hand, which in itself starts them on the path to engagement with the subject.

The results in this case were telling. Firstly, the vast majority of replies to the question whose job it should be to reduce energy waste said it was everyone’s. Even more striking was that every reply identified cost as a thing that makes energy important (just over half additionally mentioned the environment). Some suggested that the savings could be spent on bringing in more business, and thereby securing long-term employment. And when it came to what was more important than saving energy, the overwhelming majority said customer service. Not in a million years would I have thought of making ‘customer service’ one of the possible responses in a multiple-choice question but that was most groups mentioned. I’d like to quote one response in particular:

“Customers must receive a professional, efficient friendly service carried out by conscientious, smart, knowledgeable staff, who show pride in their working environment, resulting in customers returning again ”

So there we have it: waiters, porters, cleaners, cooks and security guards thinking like owners and managers. Furthermore, almost everyone believed there was energy waste at work (the only exception, tellingly, came in an individual response from a director). Not surprisingly lighting was seen as the main culprit, though other things got one or two mentions like the behaviour of event set-up crews.

On the strength of the consensus in the replies, I circulated a single-page summary back to all staff. I have no idea which of them had participated in the survey; the important thing was for everyone to see that their colleagues tended to share a common view which, from the overall project perspective, was positive. Social proof – their instinct to conform to perceived norms – would help us to the next step.


* the two textbooks that I recommend my students to read before workshops on motivation are: “Yes: 50 Secrets from the Science of Persuasion” by Goldstein, Martin and Cialdini, which is still in print; and “The Social Psychology of Industry” by J.A.C.Brown. First published in 1954 and now out of print, this is a difficult read which occasionally challenges our modern sensibilities, but it repays the effort.

Pitfalls of regression analysis: case study

I began monitoring this external lighting circuit at a retail park in the autumn of 2016. It seems from the scatter diagram below that it exhibits weekly consumption which is well-correlated with changing daylight availability expressed as effective hours of darkness per week.

The only anomaly is the implied negative intercept, which I will return to later; when you view actual against expected consumption, as below, the relationship seems perfectly rational:

 

Consumption follows the annual sinusoidal profile that you might expect.

But what about that negative intercept? The model appears to predict close to zero consumption in the summer weeks, when there would still be roughly six hours a night of darkness. One explanation could be that the lights are actually habitually turned off in the middle of the night for six hours when there is no activity. That is entirely plausible, and it is a regime that does apply in some places, but not here. For evidence see the ‘heatmap’ view of half-hourly consumption from September to mid November:

 

As you can see, lighting is only off during hours of daylight; note by the way how the duration of daylight gradually diminishes as winter draws on. But the other very clear feature is the difference before and after 26 October when the overnight power level abruptly increased. When I questioned that change, the explanation was rather simple: they had turned on the Christmas lights (you can even see they tested them mid-morning as well on the day of the turn-on).

So that means we must disregard that week and subsequent ones when setting our target for basic external lighting consumption. This puts a different complexion on our regression analysis. If we use only the first four weeks’ data we get the relationship shown with a red line:

In this modified version, the negative intercept is much less marked and the data-points at the top right-hand end of the scatter are anomalous because they include Christmas lighting. There are, in effect, two behaviours here.

The critical lesson we must draw is that regression analysis is just a statistical guess at what is happening: you must moderate the analysis by taking into account any engineering insights that you may have about the case you are analysing

 

Lego shows why built form affects energy performance

Just to illustrate why building energy performance indicators can’t really be expected to work. Here we have four buildings with identical volumes and floor areas (same set of Lego blocks) but just look at the different amount of external wall, roof and ground-floor perimeter – even exposed soffit in two of them.

But all is not lost: there are techniques we can use to benchmark dissimilar buildings, in some cases leveraging submeters and automatic meter reading, but also using good old-fashioned whole-building weekly manual meter readings if that’s all we have. Join me for my lunchtime lecture on 23 February to find out more

Advanced benchmarking of building heating systems

The traditional way to compare buildings’ fuel consumptions is to use annual kWh per square metre. When they are in the same city, evaluated over the same interval, and just being compared with each other, there is no need for any normalisation. So it was with “Office S” and “Office T” which I recently evaluated. I found that Office S uses 65 kWh per square metre and Office T nearly double that. Part of the difference is that Office T is an older building; and it is open all day Saturday and Sunday morning, not just five days a week. But desktop analysis of consumption patterns showed that Office T also has considerable scope to reduce its demand through improved control settings.

Two techniques were used for the comparison. The first is to look at the relationship between weekly gas consumption and the weather (expressed as heating degree days).

The chart on the right shows the characteristic for Office S. Although not a perfect correlation, it exhibits a rational relationship.

Office T, by contrast, has a quite anomalous relationship which actually looked like two different behaviours, one high one during the heating season and another in milder weather.

The difference in the way the two heating systems behave can be seen by examining their half-hourly consumption patterns. These are shown below using ‘heat map’ visualisations for the period 3 September to 10 November, i.e., spanning the transition from summer to winter weather. In an energy heatmap each vertical stripe is one day, midnight to midnight GMT from top to bottom and each cell represents half an hour. First Office S. You can see its daytime load progressively becoming heavier as the heating season progresses:

Compare Office T, below. It has some low background consumption (for hot water) but note how, after its heating system is brought into service at about 09:00 on 3 October, it abruptly starts using fuel at similar levels every day:

Office T displays classic signs of mild-weather overheating, symptomatic of faulty heating control. It was no surprise to find that its heating system uses radiators with weather compensation and no local thermostatic control. In all likelihood the compensation slope has been set too shallow – a common and easily-rectified failing.

By the way, although it does not represent major energy waste, note how the hot water system evidently comes on at 3 in the morning and runs until after midnight seven days a week.

This case history showcases two of the advanced benchmarking techniques that will be covered in my lunchtime lecture in Birmingham on 23 February 2017 (click here for more details).

Air-compressor benchmarking

Readers with reliably-metered compressed-air installations are invited to participate in an exercise using a comparison technique called parametric benchmarking.

Background

Traditionally, air-compressor installations have been benchmarked against each other by comparing their simple specific energy ratios (SER) expressed typically as kWh per normal cubic metre. However, as this daily data kindly supplied by a reader shows, there may be an element of fixed consumption which confounds the analysis because the SER will be misleadingly higher at low output:

example
Note: a four-day period of anomalous performance has been hidden in this diagram

It seems to me that the gradient of the regression line would be a much better parameter for comparison; broadly speaking, on a simple thermodynamic view, one would expect similar gradients for compressors with the same output pressure, and differences would imply differences in the efficiency of compression. The intercept on the other hand is a function of many other factors. It may include parasitic loads; it will certainly depend on the size of the installation, which the gradient should not.

I am proposing to run a pilot exercise pooling anonymous data from readers of the Energy Management Register to try “parametric” benchmarking, in which the intercepts and gradients of regression lines are compared separately.

Call for data

Participants must have reliable data for electricity consumption and air output at either daily or weekly intervals: we will also need to know what compressor technology they use, the capacity of each compressor, and the air delivery pressures.

In terms of the metered data the ideal would be to have an electricity and air meter associated with each individual compressor. However, metering arrangements may force us to group compressors together, the aim being to create the smallest possible block model whose electricity input and air output is measurable.

Please register your interest by email to moc.a1495933102msev@1495933102sinli1495933102v1495933102 with ‘compressor benchmarking’ in the subject line: once I have a reasonable group of participants I will approach them for the data.

Vilnis Vesma

4 January 2017