BUILDING RESEARCH & INFORMATION (2008) 36(5), 499 –508
Energy feedback in buildings: improving the
infrastructure for demand reduction
Sarah Darby
Lower Carbon Futures, Environmental Change Institute,Oxford University Centre for the Environment,
South Parks Road,Oxford OX13QY, UK
Email: [email protected]
The concept of market transformation is being widened to include a range of processes, including information flows. The
paper argues that feedback to energy users on their consumption (via improved metering, billing and displays)
complements other tools such as energy labelling and minimum standards, increasing the likelihood that decisions on
built fabric and equipment will be grounded in the realities of daily usage. Different types of feedback to energy users,
mostly in the residential sector, are considered for their impact in the short- and long-term. Implications are examined
for energy policy in relation to feedback, including the relative importance to different actors of load control and
demand reduction, as well as the question about how priorities should be set in debates over the future of metering.
Keywords: behaviour, billing, demand management, feedback,
transformation, metering, socio-technical systems
inhabitants,
intelligent
buildings,
market
Le concept de la transformation du marché est élargi de façon à inclure une gamme de processus, notamment les flux
d’informations. D’après l’auteur, le retour d’information vers les consommateurs d’énergie concernant leur
consommation (grâce à l’amélioration des moyens de mesure, de la facturation et de l’affichage) complète d’autres
outils comme l’étiquetage de l’énergie et les normes minimales, ce qui augmente les chances que les décisions relatives
au tissu construit et aux équipements soient prises en fonction de la réalité de l’usage quotidien. L’auteur examine
différents types de retours d’information destinés aux consommateurs d’énergie, la plupart dans le secteur résidentiel,
en termes de leur impact dans une perspective plus ou moins lointaine. Les implications sont examinées dans le cas de
la politique énergétique en relation avec le retour d’information, y compris de l’importance relative pour différents
acteurs du contrôle des charges et de la réduction de la demande ainsi que la façon d’établir les priorités dans les
débats concernant l’avenir des systèmes de mesure.
Mots clés: comportement, facturation, gestion de la demande, retour d’information, habitants, bâtiments intelligents,
transformations du marché, mesure, systèmes socio-techniques
Energy demand and energy information
Technologies and materials are available that can dramatically reduce the energy demand from buildings in
temperate climates and many of them, such as
improved building insulation and more efficient cold
and wet appliances, have been deployed for some
time and are becoming more prevalent (Boardman
et al., 2005; Utley and Shorrock, 2006). Yet aggregated
energy statistics for Organisation for Economic Cooperation and Development (OECD) countries rarely
show a decline in the overall delivered energy. In the
UK, for example, overall delivered energy to homes
has remained roughly stable between 1996 and 2006,
with residential electricity consumption rising by 8%
during that period (Department of Trade and Industry
(DTI), 2007a). There is a mismatch between expectations for energy efficiency and outcomes, all the
more serious because a failure to stem growth in fuel
consumption and carbon emissions is not something
that can be managed solely by recourse to supply-side
Building Research & Information ISSN 0961-3218 print ⁄ISSN 1466-4321 online # 2008 Taylor & Francis
http: ⁄ ⁄www.tandf.co.uk ⁄journals
DOI: 10.1080/09613210802028428
Darby
solutions and carbon sequestration. This is recognized
in current policy documents: for example, direct
demand reduction (including energy efficiency)
accounts for 37 –47% of the estimated drop in
carbon emissions between present and 2020, with
supply-side developments (including carbon capture
and storage) accounting for only 3 –9% (DTI, 2007b,
table 10.1).
The growth in the numbers of households is an important factor in cancelling out efficiency gains. But there
are many other factors driving up demand, such as
changing perceptions of what constitutes thermal
comfort and desirable lighting, along with the proliferation of consumer electronics (Shove, 2003; Boardman
et al., 2005; Boardman, 2007; Cole et al., 2008; Shove
et al., 2008). Many studies over the past few decades
have pointed out the importance of including social
and behavioural considerations in the analysis of
energy use in buildings (e.g. Sonderegger, 1978;
Palmborg, 1986; Dall and Toft, 1996; Bin and
Dowlatabadi, 2005), leading to the view of energy
systems as socio-technical in nature, both socially constructed and society shaping. In such systems, information plays a crucial role.
At the simple end of the spectrum, an energy system
may comprise a source of wood that is maintained
and collected by hand, a fireplace and a residue of
ash that can be used as fertilizer. The scale of the woodland resource, the management regime, the comfort
requirements of the energy users, and the type and
number of fireplaces will all have an effect on final consumption, but it will be relatively easy to establish how
the system works and to see the entire fuel cycle in
action. In an industrialized society, though, it is far
more likely that energy needs will be supplied by gas
or electricity travelling long distances through a
complex transmission and distribution network, with
the associated management systems. There will be
many end-users with a wide range of equipment and
appliances; there will also be the rules by which they
and their suppliers act, whether explicit or implicit
(Wilhite and Shove, 1998; Marvin et al., 1999; Lebot
et al., 2005). Few people understand such systems in
their entirety and they are not designed to be clear to
the end-users. For example, day-to-day usage of domestic central heating controls reveals how designers
and users of the controls fail to understand each
other (Bartram et al., 1985; Leaman, 2000; Pett and
Guertler, 2004). This matters because design, testing
and installation of the controls can ‘write the script’
for energy wastage or for thrift. Yet testing of controls
typically takes place in standardized surroundings
rather than in real-life situations, while heating installers are often not well suited to prepare householders
for life with a new system. An example is given by an
energy adviser who described what he called
‘plumber setting’ – the situation that he and colleagues
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had often observed after a plumber had installed a new
central heating system:
. . . The hot water tank thermostat will be at
908C, boiler thermostat will be at Max. . . .
[Plumbers have] got to check everything before
they go. ‘So we’ll test it at High. And we’ll
leave it at High. Put the heating on Constant,
put the water on Constant and if it’s too hot,
Missis, turn it down. And if it’s too cold, turn
it up.’ And they walk away. . . . The tenant
thinks the [thermostat] on the wall is an on-off
switch, which leads to over-heating, underheating, over-heating. . . .
(interviewed in Darby, 2003, ch. 7)
Installers do not normally stay around to see the effects
of their handiwork and advice (and neither do they
wish to make return visits); once the controls are in
use, the outcomes are not fed back adequately to
designers and installers so that they can make realistic
improvements.
There are continuing failures to design ‘reality checks’
into buildings in order to inform energy and climate
policy. Post-occupancy evaluations – a rare phenomenon – point to the need for ‘a culture of feedback
with better benchmarking and constant review
against client and design intentions’ (Bordass et al.,
2001, p. 144). Such evaluations can be used in the
short- and long-term, to inform day-to-day behaviour
of the people using a building and to improve design,
materials, construction, installation and commissioning practices (Bordass and Leaman, 2005). There are
also strong arguments for improving the infrastructure
of metering and/or billing in order to promote better
understanding and control (Williams et al., 1985;
Henryson et al., 2000; Strengers, 2008). As a first
requirement, all households need their own meters:
a shift from master-metering to individual metering
or submetering can lead to reductions in demand of
the order of 30% (Lutzenhiser, 1993). Second, there
is plenty of room for more visible, accessible information on energy use, in real time and retrospectively;
some of the evidence for such feedback information as
a tool for energy literacy1 and changed behaviour is
discussed below.
This paper argues that it is reasonable to think of
improved feedback through energy systems as an
element of market transformation in buildings, and
that the formal incorporation of feedback arrangements into policy (for example, in the recent European
Energy End-use Efficiency and Energy Services Directive (EC, 2005)) is a welcome development. It looks
at some options for developing the feedback infrastructure for energy in buildings, at the interests of different
actors and the issues raised, and concludes with some
policy recommendations.
Energy feedback in buildings
Market transformation
There does not seem to be a single accepted definition
of market transformation, but it is acknowledged as a
strategic approach to energy policy that embraces
several elements. An early reference to the concept
describes the task of transforming the market for cold
appliances in the European Union as a mix of initiatives, comprising information and advice (including
product labelling), financial incentives, procurement,
and minimum standards (Boardman et al., 1995,
appendix D).
The concept is being developed in various contexts.
One example is the market transformation strategy of
the California Energy Commission, which emphasizes
continual learning, with new initiatives piloted and
evaluated in an iterative manner. It aims to build
knowledge about regulatory dynamics, organizational
networks, business practices, consumer –vendor interactions, and other physical and relational aspects of
changing markets (Blumstein et al., 2000). In the UK,
recent work carried out for the Market Transformation
Programme proposes a redefinition of market transformation as:
a detailed process of transforming the rules,
resources and institutions that mediate between
lifestyle goals, commercial interests and social
policy goals.
(Jackson, 2005, p. 40)
This makes market transformation a broadly-based
project for energy policy, going beyond what are
usually considered to be ‘market’ considerations.
How valid is it to incorporate feedback information
flows into the project? There is a case for doing so
because such flows affect both the physical and the
relational aspects of markets; they are part of the
process of transforming ‘rules, resources and institutions’. Arguments for the significance of feedback
in the short- and the longer-term are summarized
below and rehearsed in more detail elsewhere, as indicated in the references. But before looking at the scope
for developments in feedback, the next section defines
and discusses some terms related to energy feedback,
gives a little theoretical background, and indicates
the range of mechanisms available to end-users.
Energy feedback to end-users: some general
considerations
‘Feedback’ is:
information about the result of a process or
action that can be used in modification or
control of a process or system . . . especially
by noting the difference between a desired
and an actual result.
(Oxford English Dictionary, s.v.)
The term can, of course, be used in relation to purely
mechanical or electronic processes (for example,
heating, cooling and ventilation systems in buildings
will normally rely on feedback mechanisms), but here
it is used in connection with systems that directly
involve humans. In a ‘building–energy– user’ system,
feedback can be received in a number of ways. For
example, what is on view (on a meter or on an associated display); what a bill or statement shows and how
it is interpreted; or what energy users perceive as
changes in comfort or satisfaction from their energy
services, following changes in building fabric, equipment, or behaviour. This last may not show up in statistics but will inevitably affect the acceptability of
attempts to reduce demand.
While a surprisingly high proportion of residential
energy users may check their bills and meters, the
quality of feedback from these is usually very limited
(Kempton and Layne, 1994; Darby, 2006a). Meters
typically only show a series of digits or dials representing cumulative consumption, while bills and statements are very unlikely to disaggregate consumption
by end-use, even in the most general way. Individuals
paying for fuel by direct debit spread their payments
evenly over the year with no indication of how heat
load or lighting consumption vary with time. Bills
based on estimated consumption prevent customers
from having realistic data on which to base decisions
about their behaviour and purchases.
Yet the literature on energy feedback and conservation
(and, increasingly, the literature on building management
and emissions reduction) points to the importance of accessible, specific information in building awareness of consumption in order to experiment and to manage it more
effectively. Feedback on its own is not always sufficient to
bring about change, but it is necessary for this learning
process (Darby, 2006b). There is ample scope for learning
in the average home, where there is huge variability in
terms of the acquisition, default setting and day-to-day
use of heating systems and appliances, and where ‘behaviour’ is central to consumption levels (Lutzenhiser, 1993).
A relatively new consideration is the potential for
feedback on building-integrated electricity generation.
A recent study of system change for domestic
micro-generation in the UK concludes that the advent of
microgeneration is an ‘ideal opportunity to kick-start
the modernisation of the UK’s meter stock . . .’ (Watson
et al., 2006, p. 3). More advanced metering does not in
itself guarantee effective feedback to consumers (see
below), but it does offer an opportunity to improve it, if
‘smart’ meters are deployed along with effective displays.
Advanced metering can also facilitate feedback on consumption and generation at the same time, to give
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householders an overview of what is happening from
moment to moment. There is already some evidence
that building-integrated electricity generation, especially
when installed with feedback displays, is associated with
demand reduction as well as with building awareness
about generation (e.g. Keirstead, 2005; Dobbyn and
Thomas, 2005). Own-generators will require metering
for overall consumption, on-site generation and exports
if they are to have a clear picture of what is happening
in their premises and if they are to be able to take part
in wholesale electricity markets (Keirstead et al., 2006).
The range of savings achieved through feedback-related
innovations points to the significance of the mode,
content, and timing of feedback in promoting learning
and change. It also means that there is a need for thorough
testing before widespread adoption of a particular application.2 From the literature to date, though, energy
savings of the order of zero to 10% have been achieved
when householders were given better indirect feedback
(usually billing or statements), and of 5–15% from
direct feedback (via the meter or an associated display).
The variation in savings has also been attributed to
factors such as social and cultural context, the characteristics of the households sampled, climate, and housing
type (Wood and Newborough, 2003; Darby, 2006b;
Mountain, 2006). The few feedback studies carried out
over a year or more show that participants did not just
change their behaviour in the short-term but formed
new habits (Darby, 2006b). The shorthand way
of describing this is to say that the ‘savings’ persisted in
comparison with control households.
At this point, though, it is worth questioning the use of
the term ‘savings’ in the policy debate. However appropriate it might be when considering short-term
changes, it loses some of its usefulness over longer
time periods. For example, if a household uses 10%
less fuel than its neighbour in 2006 following some
intervention or specific change in the energy system,
and is still using 10% less fuel than the neighbour in
2012, but more fuel than in 2006, does that represent
a continued ‘saving’, or a failure to learn from the intervention or change? Both, presumably, but the latter is
likely to be more significant than the former in the
long-term. It is arguably more productive to think in
terms of transformation to a low-fuel, low-carbon
way of life than to centre the debate on ‘savings’,
which so often turn out to be steps taken down an
upward-moving escalator. The ‘learning’ aspects of
any planned change in the system need to take a
more central place in the evaluation of its effects.
Interpretations of feedback from psychology
and learning theory
The early experiments with feedback on energy consumption in the 1970s were mostly conducted by
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psychologists and concentrated on immediate
responses to what was seen as a ‘stimulus’ or ‘intervention’, but over time they became more ‘ecological’ in
nature, being carried out in more easily-replicable conditions, on longer timescales, with more participants
and with due attention to the need to minimize possible
‘Hawthorne effects’ (that is, of participants behaving
differently because they know they are being observed).
There have also been changes in terms of interpretation
of the significance of feedback. After a few years of
experimentation, researchers began to appreciate that
feedback has an educational impact as well as directly
behavioural effects (Ellis and Gaskell, 1978). This is
backed by educational theory that argues that individuals find ways of adapting themselves to their environment, and of shaping that environment, by using
feedback (Piaget, 1972; Wadsworth, 1996).
Both learning theory and psychology have been used to
give pointers about how energy feedback ‘works’
(Darby, 2006a). They support the proposition that
improved feedback will not just produce short-term
results but will alter the way in which people think of
energy, control usage, and are able to adapt to changes
in energy systems. That is, it will have impacts on the
development of these systems by allowing energy users
to experiment and develop their own methods of
energy management, based on data that are specific to
them and that they trust. It allows them to interrogate
their own ‘building–energy–user’ system: ‘What
happens if I turn the thermostat up a degree/insulate
the walls/switch off the computer whenever it is not in
use?’ A number of possible channels for energy feedback
are discussed briefly below, in relation to recorded
outcomes and potential for learning.
Informative billing
Informative billing is billing that is accurate (based on
readings rather than estimates), frequent, and that provides useful information in addition to total consumption and cost over the billing period. This may include a
comparison with previous periods (historic feedback),
or comparison with other energy users (comparative
feedback). Bills can be adapted to show trends graphically, such as how heating demand is spread over the
year. They can show how consumption has changed
relative to the same period of the previous year,
giving the energy user the opportunity to work out
what might have caused the change, such as new patterns of occupancy, a new boiler or appliance, insulation or an extension to the building. Bills can also
include annual ‘energy reports’, or give a breakdown
of how consumption is distributed between end-uses
in an average home. For useful overviews of the
issues, see Roberts and Baker (2003) and Iyer et al.
(2006).
Energy feedback in buildings
The most comprehensive informative billing studies to
date are those carried out in Norway during the 1990s,
which gave savings of 10% relative to a control group
by those with more frequent and accurate bills, which
were maintained over at least two years (Wilhite and
Ling, 1995). A second, larger study, in which 2000 customers telephoned in their meter readings six times a
year as the basis for accurate bills with historic feedback, was showing savings of 8% over a control
group, more than a year after the end of the experimental period, accompanied by increased energy awareness
(Wilhite, 1997). The learning from these trials
extended beyond the households and the utilities to
government, when the changes in procedure (more frequent meter readings and the insertion of a feedback
graph into the bill) were institutionalized as mandatory
quarterly informative billing for the whole of Norway.
A further development in Scandinavia has been the
Swedish regulatory requirement for monthly, accurate
bills for all customers by 2009, which is now driving
the business case for automated meter reading (Siderius
and Dijkstra, 2006).
Advanced metering and displays
The term ‘advanced’ or ‘smart meter’ is used to cover a
range of meter specifications, but it is generally accepted
that smart meters are able to measure consumption over
representative periods to legal requirements, store the
data for multiple time periods, and allow ready access
to data by consumers as well as suppliers and their
agents (having two-way communications and allowing
automated meter reading). The interface between consumer and supplier is a crucial component of the
system, affecting the extent of learning and control by
either. There is the potential for smart electricity
meters to be used by the supplier for direct load
control, for example, by switching off water heaters or
freezers for short periods at times of peak demand; or
they can be used to enable householders to manage
load themselves, in response to signals from the supplier
– an ‘interval’ electricity meter can store and communicate consumption data by time of use, paving the way
for more complex tariffs designed to reduce peak
demand. Customers can be incentivized to shift their
consumption away from peak times, being informed
via a display about when those peak times occur and
what their rate of expenditure is at any point during
the day. Owen and Ward (2006) cover these and
many related issues in their assessment of costs and
benefits of smart metering in the UK.
Internet metering combines the functionalities mentioned
above with the ability to communicate with the Internet,
allowing online transactions and related services.
It is important to note that the demand for smart
metering came in the first instance from energy
suppliers, not from their customers: it has been developed primarily as a tool for load management/peak
reduction, and for reducing the costs of customer
service, rather than for overall demand reduction.
Some of the claims made for it need to be treated
with caution: so much depends on design and
implementation. However, advanced metering makes
accurate, frequent billing much more viable and so it
improves the prospects for better billing feedback. If
the customer interface (display) allows, it can also
improve the prospects for demand reduction from
direct feedback.
Direct displays3 are typically small panels giving information about electricity consumption (although multiutility displays are now starting to appear and a gas
display was first developed some time ago for the study
described in Van Houwelingen and Van Raaij, 1989).
They can be used in conjunction with both advanced
and standard (‘dumb’) meters and are developing
rapidly at the time of writing. ‘First-generation’ displays
show real-time consumption (or own-generation); the
second generation also gives historic information over
specified time periods; and the third generation has web
interfaces, allowing for a wide range of interrogations,
access to advice, and membership of user groups. They
are designed to answer questions varying from the
simple ‘How much electricity am I using right now?’
and ‘Have I left anything switched on as I leave the
house/go to bed?’ to the more complex: ‘Are we consuming more today than yesterday?’, ‘More this month than
last month?’, ‘How does our in-house generation
compare with our consumption?’, ‘How much are
we exporting to the grid?’ and ‘How much are we consuming compared with other households?’ Consumption may
be indicated in terms of kilowatts (kW), cost or carbon
dioxide units. Some displays can be programmed to
show an alarm when the electricity load in the building
exceeds a given level, or if credit is running out.
Displays do not have to show consumption or generation in the form of numbers, although that is the
most common mode. There have been experiments
with analogue display and with ambient feedback,
showing consumption or current cost (for time-of-day
pricing or critical peak pricing) through the colour of
a light or the size of a graphic (Lockwood and
Murray, 2005; Martinez and Geltz, 2005).
Pay-as-you-go metering
This can be seen as a transitional form of metering,
between the ‘dumb’ and the fully ‘smart’ meter. An
example is in operation in Northern Ireland, where
there are now over 155 000 residential customers
using keypad meters, a ‘pay-as-you-go’ system (Office
of Gas and Electricity Markets (Ofgem), 2006). The
keypad meter has the benefits of being portable and programmable with new tariffs. It replaces the old
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prepayment meter, but has also been taken up by many
former credit customers. Customers buy electricity
using a plastic card at a local shop or filling station, or
via their debit card over the telephone. They then key
in their code on the key pad, which displays
how much electricity they have bought and
the total credit. There is some protection against selfdisconnection, with an alarm when credit is close to
running out and an emergency supply that can be
extended if it runs out during evenings or weekends.
The meter can show instantaneous electricity usage
and give historic feedback, showing how much has
been spent on electricity during the previous day,
week and month. Some meters display the previous 13
months’ usage (Northern Ireland Electricity (NIE),
2001) and a ‘power-shift’ option now also allows for
time-of-use pricing (NIE, 2006). Ninety per cent of a
sample of 500 customers stated that the meter helped
them to manage their consumption better (Consumer
Council, 2005); an earlier survey showed electricity
savings of 4% among customers compared with the previous, pre-keypad, year (NIE, 2003). The comparable
Salt River Project in Arizona, US, claims savings of
over 12% among its pay-as-you-go customers (American Council for an Energy-Efficient Economy
(ACEEE), 2007).
Collective feedback
During the California electricity supply crisis of 2000,
the Lawrence Berkeley Laboratory set up a website
with a graph of current demand and available supply
for the whole region. It was widely consulted (with up
to two million hits a day) and credited with increasing
the level of energy-conserving behaviour (LBNL/eceee,
2001). Now this has been extended to http://current
energy.lbl.gov/, which shows real-time demand in six
areas of the US along with forecast demand, net electricity imports, and the potential cap on load. This makes
it possible for all online consumers to see the ‘big
picture’ easily and quickly, taking feedback to a new
level. Through this type of feedback, individuals can
see themselves graphically as agents in a complex,
dynamic energy system. A similar action is reported
from the Western Cape in South Africa, where electricity
customers are shown a colour-coded bar on their television screens every 15 minutes during periods of tight
supply margins and are asked to turn off appliances
according to the likelihood of blackouts (Gosling, 2006).
The impact of feedback on relationships
within energy systems
The above descriptions show something of what is
already possible in terms of transforming the
‘information infrastructure’ of energy systems. The
relationship between suppliers and consumers is also
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changed by altering the type and quantity of
information passing between them; each technical
specification for a metering system will have its own
impact. For example, a conventional meter allows
for monitoring and a ‘limited’ relationship, whilst a
smart meter with an interactive display can allow
greater user control and a more ‘devolved’ relationship
with the utility (Marvin et al., 1999). Table 1
summarizes some characteristics of advanced metering,
indicating how the benefits may be distributed.
Feedback and the European Union Energy
Services Directive
The European Union Directive on Energy End-use Efficiency and Energy Services (often referred to as the
Energy Services Directive, or ESD) was signed in May
2006 with the stated aims of improving the efficiency
of energy markets, managing demand, contributing
to environmental objectives and improving energy
security.
The preamble to the Directive broadens the concept of
energy-efficiency measures to include the metering
infrastructure:
In defining energy efficiency improvement
measures, account should be taken of efficiency
gains obtained through the widespread use of
cost-effective . . . innovations, e.g. electronic
metering.
(preamble, para. 28)
and specifically aims for well-informed decisionmaking by consumers:
In order to enable final consumers to make
better-informed decisions as regards their individual energy consumption, they should be provided with a reasonable amount of information
thereon . . . consumers should be actively encouraged to check their own meter readings regularly.
(preamble, para. 29)
In this way, the familiar concept of energy efficiency is
extended in a way that has already been seen in the
extension of the concept of market transformation.
Not only does efficient technology need to be promoted: the people responsible for energy end-use
need to have the information to manage their technologies more effectively and they need the infrastructure
that will allow for that. But the document stops short
of moving from the language of efficiency (a ratio) to
the language of demand reduction (an absolute).
And, judging from the content of the many conferences
held over the past few years on the theme of advanced
metering, utilities are mainly interested in the potential
for smart metering to assist in reducing peak electricity
Energy feedback in buildings
Table 1 Range of possible functions of advanced metering
Function
Likely signi¢cant bene¢t to . . .
Automatic meter reading
Supplier: reduces the cost of reading, enquiries, complaints and
call outs
Energy user: more accurate bills, not having to be available when
the meter reader calls
Analysis of data and local display
User: improved understanding and control, partly dependent on
the quality of display
Transfer of consumption data to the supplier for accurate billing
without requiring access to the home
User plus the supplier
Facilitating payment
User plus the supplier
Measurement and recording of data on continuity and the quality
of supply
District Network Operator (DNO) plus the supplier
Remote control of consumer circuits or equipment for agreed load
management
Supplier: who pays less for peak-load generation
Users: should also bene¢t from reduced tariffs
Display of price signals for different time periods as part of
demand^response/load-control programmes
Supplier: who can facilitate load management; there might be
equity issues for customers; also confusion by multiple tariffs
Remote change of tariff, debt or other rates (if allowed by the
regulator)
Supplier: primarily
Remote disconnection and reconnection
Supplier: primarily (contentious)
Measurement of electricity export and/or generation from the
building
User plus the supplier plus the DNO
demand, to reduce the costs of billing and customer
service operations, and to allow movement into new
areas of business. The relationship between these
objectives and that of overall demand reduction is
still uncertain as utilities prepare for massive investments in new metering and billing and as they watch
the progress of those who are already implementing
major changes. Article 13 of the Directive gives some
guidance, requiring that:
Member States shall ensure that, in so far as it is
technically possible, financially reasonable and
proportionate in relation to the potential energy
savings, final customers . . . are provided with
competitively priced individual meters that accurately reflect actual energy consumption and that
provide information on actual time of use.
billing on the basis of actual consumption shall
be performed frequently enough to enable customers to regulate their own energy consumption.
Member States shall ensure that, where appropriate, the following information is made available
to final customers in clear and understandable
terms . . . in or with their bills . . .
Current actual prices and actual consumption
of energy;
Comparison of the final customer’s current
energy consumption with consumption for the
same period in the previous year, preferably in
graphical form;
Wherever possible and useful, comparisons with
an average normalized or benchmarked user of
energy of the same user category. . . .
However, while Article 13 requires accurate, frequent
measurement and billing, information on time of use,
and clearly presented feedback information, it still
leaves considerable room for interpretation. Judgements on technical possibility, potential energy
savings and ‘reasonable’ cost are left to Member
States, which were given two years within which to
enact their own legislation in compliance. That
period is almost over at the time of writing, but there
is still plenty to resolve.
Policy issues
The extent to which regulators should hold utilities
responsible for improving feedback to their customers
and reward them for any savings attributable to such
improvements is still under intense discussion. More
generally, there is increasing debate about the role of
suppliers in relation to their customers – ‘consumers’,
some of whom are becoming ‘co-generators’ – and
about the acceptable uses of new technologies. For
example, how much power should an electricity
505
Darby
supplier have to control load, change tariff or to disconnect customers remotely? Who should have access
to detailed information on consumption: are advanced
meters, in effect, ‘spies in the home’? The technical specification of metering systems and their associated
communications, the subject of so much urgent
debate, is far from being socially neutral.
A further set of issues centres on the distribution of
quantitative risks and benefits from implementing
different types of metering (for an overview for the
UK, see Owen and Ward, 2007). As the technology
for implementing more complex pricing regimes
becomes widely available, there is debate about the
amount of ‘shiftable’ load and the distribution of risk
between supplier and customer in paying for electricity
generated at different times of day at varying marginal
cost. There is a risk of confusing customers with a
plethora of competing tariffs, and there are also
equity concerns: is the ability to shift load linked
with income in any consistent way? How does timeof-use electricity pricing affect demand and the ability
to pay in all-electric buildings, especially as these are
often the homes of customers on low incomes?
These are some of the main concerns from the customer’s perspective, but there are further difficult
decisions to be faced by government and suppliers in
planning for gas and electricity distribution in the
future and for the integration of renewable supply
into networks. There is also the need for clear standards for smart meter interoperability in liberalized
markets, so that customers can switch supplier
without needing to change their meter. Should the
aim be for single or multi-utility meters? Where
should the ‘smartness’ (the communications technology) reside – in the meter or alongside it? The more liberalized the market, and the more complex the
technologies involved, the greater the need for clarity.
In all this it needs to be remembered that feedback
systems for demand reduction do not have to be
complex to be effective. The basic requirements for
good information flows through an energy system,
for a better understanding of the system by end-users,
and above all for continuing demand reduction, are
in danger of being lost in the arguments over equipment specification.
and to own-generators. The literature indicates significant demand reduction in the short- to medium-term
and a continued ability to develop energy literacy in
the longer-term. The latter is the most important
‘transformational’ characteristic of feedback.
However, there are many issues related to the extent to
which feedback technologies can be used to control
energy end-users or to empower them. The European
Union Energy Services Directive is an example of a
policy move towards improved feedback, but it offers
a wide scope for interpretation. There is still much to
be done to ensure that feedback to end-users is recognized as part of market transformation – not only as
a method of achieving ‘savings’ – and that it effectively
complements other policy tools such as energy
labelling and minimum standards that apply at the
design stage and at point of sale or point of lease.
If there is a single salient lesson from experience so far,
at this stage of the debate it is that feedback does not
need to be complex to be effective. There is a danger
that the debate over the future of metering, with all
its complexity, overshadows the need to test and
build up feedback mechanisms as and where possible,
with a view to incorporating them within smart
meter systems as these evolve.
Acknowledgements
This paper was completed thanks to an interdisciplinary research fellowship awarded by the Economic
and Social Research Council (ESRC). It draws on
work carried out for the ‘Building Market Transformation’ project, an inquiry into policy and market framework options with the aim of reducing carbon
emissions from UK buildings to 50% of 1990 levels
by 2030 (Building Market Transformation (BMT),
2006). The project is funded by the Engineering and
Physical Sciences Research Council (EPSRC) and
Carbon Trust (Grant No. GR/S94292/01), as part of
the Carbon Vision programme. The comments of
Brenda Boardman, Gavin Killip and the anonymous
referees are gratefully acknowledged.
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Endnotes
1
Energy literacy is: ‘a dimension . . . reflecting different patterns of
beliefs and knowledge about energy conservation . . . [those with
low energy literacy] lack the decisional freedom typical of the
more energy literate, who through greater knowledge have
more options available with which to respond to new situations’
(Gaskell et al., 1982, p. 2).
2
A number of trials are under way at present, and findings are
being collated by the European Smart Metering Alliance.
3
While the term ‘smart meter’ is often used to describe a display, it
is important to note that the two are not the same.