Energy feedback systems : evaluation of meta-studies on energy savings through feedback : Energy Efficiency Directive Articles 9-11 on feedback, billing and consumer information.
Date: 2016-07-19
Institutions: Institute for Energy and Transport
Subjects: consumer information, energy consumption, energy efficiency, energy industry, energy saving, energy use, invoicing, research report

Energy Feedback Systems:  
Evaluation of Meta-studies on energy 
savings through feedback 

Energy  Efficiency  Directive 
Articles 9-11 on Feedback, 
Billing 
Consumer 
information  

and 

JRC-IET 
Renewables and Energy Efficiency Unit 

Tiago  Serrenho,  Paolo  Zangheri,  Paolo 
Bertoldi 

2015 

EUR 27992 EN 

This publication is a Science for Policy report by the Joint Research Centre (JRC), the European Commission’s science and 
knowledge service. It aims to provide evidence-based scientific support to the European policy-making process. The scientific 
output expressed does not imply a policy position of the European Commission. Neither the European Commission nor any 
person acting on behalf of the Commission is responsible for the use which might be made of this publication. 

Contact information  
Name: Tiago Serrenho 
Address: Via E. Fermi 2749 (TP 450) I-21027 Ispra (VA) – Italy 
E-mail: tiago.serrenho@ec.europa.eu 
Tel.: +(39) 033278 9628 

JRC Science Hub 
https://ec.europa.eu/jrc 

JRC99716 

EUR 27992 EN 

PDF 

ISBN 978-92-79-59778-7 

ISSN 1831-9424 

doi:10.2790/565532 

Luxembourg: Publications Office of the European Union, 2015 
© European Union, 2015 

Reproduction is authorised provided the source is acknowledged. 

How to cite: Serrenho, T.; Zangheri, P.; Bertoldi, B;  Energy Feedback Systems:  
Evaluation of Meta-studies on energy savings through feedback; EUR 27992 EN; doi:10.2790/565532 

All images © European Union 2015, except Figure 2: Page 7, 2015. Source: Opower; Figure 3: Page 9, 2015. Source: Bidgely 
and Plotwatt 

Energy Feedback Systems: Evaluation of Meta-studies on energy savings through feedback 
The Energy Efficiency Directive, in its Articles 9 to 11 focuses on the availability of accurate, up to date information to be 
provided to final energy consumers in a cost-effective way. The present study proposes a literature review on existing studies 
regarding energy feedback systems, having in consideration the type of feedback, its duration, the geographical area where 
these have been performed and the correlation from these with the type of energy carrier being used by the final consumers. 
The main objective of this report is to provide evidence of the effectiveness of direct and indirect feedback and what the 
potential savings depending on type of media chosen for the interaction with the costumers may reach. 

1 

Table of contents  

Table of contents .................................................................................................. 1 

List of Tables ........................................................................................................ 2 

List of Figures ....................................................................................................... 2 

1. Introduction ...................................................................................................... 4 

1.1. Energy Feedback ............................................................................................ 5 

1.2. Feedback on the Energy Efficiency Directive ..................................................... 11 

2. Member State NEEAP Analysis ........................................................................... 13 

3. Analysis of Meta-data studies on Feedback ......................................................... 20 

3.1 Feedback Studies Breakdown .......................................................................... 27 

4. Achieved Savings through Feedback .................................................................. 30 

4.1 Savings per consumption type and geographical area of the studies ..................... 31 

4.2 Savings per consumption and feedback type ..................................................... 32 

4.3 Savings per consumption type and the period of the study.................................. 33 

4.4 Savings per feedback type and medium............................................................ 34 

4.5 Savings per feedback type and frequency of interaction ...................................... 36 

4.6 Savings per feedback type and duration of the study ......................................... 37 

5. Conclusions and Discussion ............................................................................... 38 

References ......................................................................................................... 41 

ANNEX I ............................................................................................................. 47 

List of Tables 

Table 1 – Types of Feedback ................................................................................... 6 

Table 2: Status of main issues related to feedback reported in the MSs' NEEAPS. ........ 16 

Table 4: Summary of relevant feedback studies. ..................................................... 21 

List of Figures 

Figure 1 – Example of a Standard Energy Bill ............................................................ 7 

Figure 2 – Behavioral science insights in OPOWER Home Energy Reports ..................... 8 

Figure 3 – Example of direct feedback interface with disaggregation by appliance ....... 10 

Figure 4: Breakdown of studies taken into account. ................................................. 29 

Figure 5: Savings per consumption type and geographical area ................................ 31 

Figure 6: Savings per consumption and feedback type. ............................................ 32 

2 

 
 
 
 
 
Figure 7: Savings per consumption type and the period of the study. ........................ 33 

Figure 8: Savings per feedback and medium type ................................................... 34 

Figure 9: Average dimension of samples per feedback and medium type. ................... 35 

Figure 10: Savings per feedback type and frequency of interaction). ......................... 36 

Figure 11: Savings per feedback type and duration of the study................................ 37 

3 

 
 
 
 
 
 
1. Introduction  

The  present  study  has  been  conducted  by  the  European  Commission’s  Joint  Research 

Centre  on  behalf  of  DG  ENER  with  the  purpose  to  understand  the  potential  of  different 

energy feedback systems and how these can contribute in achieving energy savings in a 

consistent way. 

Articles  9  and  10  of  the  Energy  Efficiency  Directive  (EED)  focus  on  providing  accurate 

and  regular  metering  information  for  final  energy  consumers  with  the  roll-out  of  smart 

metering systems being of considerable importance to this effect. The focus on providing 

reliable, timely and accurate information to consumers is considered to be crucial so that 

these  consumers  become  more  aware  of  their  consumption  patterns  and  can  act 

accordingly in order to manage their behaviour in terms of achieving energy savings with 

this information at hand. The awareness raising can be achieved through different means 

of communication between energy companies and the final consumer. 

This  report  pulls  together  findings  from  scientific  meta-studies  that  assess  energy 

feedback  projects  and  analyses  the  outcomes  of  such  studies,  having  in  consideration 

the specificities of each study in terms of geographical area of the study, type of energy 

carrier (electricity, gas  etc.), the year of the study, sample  size, type  and frequency  of 

the feedback and the medium used for the interaction between the energy company and 

the final energy consumer. 

The report also summarises the status of the implementation of Articles 9 and 10 of the 

Energy  Efficiency  Directive  on  metering  and  billing  as  reported  by  Member  States 

themselves  in  their  2014  National  Energy  Efficiency  Action  Plans  that  Members  States 

submitted in  accordance  with  the  EED,  focusing  on  the  latest  developments  of  the  roll-

out  of  Smart  Meters,  individual  energy  measurements  and  billing  in  terms  of  the 

information available to consumers and the periodicity of billing and readings, where the 

bills  need  to  be  based  on  real  consumption,  be  delivered  frequently  to  final  consumers 

and historical consumption should be made accessible.  

The outcomes of a workshop organized by the Joint Research Centre on the “Provision of 

consumption information to final customers  - EC support to the  Implementation of EED 

Article  10  in  relation  to  billing  information”  were  also  taken  into  consideration  for  this 

report  (see  Annex  I  for  a  summary  of  the  workshop  presentations).  It  has  to  be  noted 

that  in  terms  of  heat  metering,  the  Joint  Research  Centre  has  developed  a  report  on 

“Accurate metering and billing of individual consumption of heating/cooling and domestic 

hot water in multi-apartment and multi-purpose buildings”. 

Smart meters have features or functionalities that can change the paradigm in the way 

energy is being managed. The optimization of grid use and consequent efficiency of the 

4 

 
 
 
grid,  especially  the  distribution  network,  where  network  losses  are  sometimes 

significant;  the  possibility  of  accurate  and  frequent  reading,  the  possibility  of  getting 

feedback in real time and the functionality for final energy consumers to access to time 

of  use  tariffs.  The  smart  meter  roll  out  should  allow  for  a  much  greater  interaction 

between final energy consumers and energy system operators allowing the consumers to 

base  their  choices,  in  terms  of  actual  energy  consumption,  while  stimulating  energy 

savings,  providing  at  the  same  time  a  natural  increase  of  efficiency,  especially  in  the 

Distribution  System  Operators  thanks  to  the  easy  access  of  consumption  patterns, 

allowing networks to act on actual updated data in order to manage networks assets in a 

much more concerted way.  

The fact that smart meters can be connected to other devices in the “connected home” 

should  ultimately  allow  for  a  much  more  effective  energy  management  for  final 

consumers. While there may still be a long road for the full deployment of smart meters 

all over the EU, the fact that consumers  may be able to access the accurate registry of 

their  own  energy  consumption  through  individual  measurements,  receive  further 

information  on  the  types  of  tariffs  and  get  advice  on  how  to  save  energy  in  their  bills, 

presents a valid potential in order to reduce energy consumption in final consumers. 

1.1. Energy Feedback 

Energy Feedback is a way to turn a resource that until recently was more or less invisible 

to  energy  consumers  into  a  visible  one,  having  ultimately  the  possibility  of  turning 

energy consumers from a passive state into an active one.  

This  change  of  paradigm  makes  it  possible  to  trigger  energy  savings  thanks  to  the 

actions  stimulated  from  the  collected  and  processed  energy  consumption  information 

and the consequent action from the consumer when the consumer is properly engaged. 

Ultimately  there  are  two  types  of  Feedback:  Indirect  and  Direct.  There  have  been 

described sub-categories under these two types of feedback,  allowing different types of 

interaction and response from the energy providers and energy users.  

5 

 
 
 
 
 
 
 
 
 
Table 1 – Types of Feedback 

Sub-type 

Type of Feedback 

of 

Medium 

Type of information 

Communication 

Feedback 

Standard 

Billing 

Paper 

- Historical Energy 

consumption 

- Historical comparison 

- Energy consumption, 

One way 

communication 

- Paper 

rewards 

Enhanced 

- Electronic 

Billing 

environment (e-

- Energy Efficiency 

One way 

Advice 

communication 

bill) 

- Social comparison 

- Historical comparison 

Direct 

feedback 

with IHD 

- In-House Display 

- Web environment 

- Real-time information  

- Social comparison 

- Historical comparison 

One way 

communication 

- Real-time information 

Direct 

with 

Connected 

- In-House Display 

- Appliance 

- Web environment 

disaggregation 

Devices 

- Smart Meter 

- Social comparison 

Two-way 

communication 

- Historical comparison 

k
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a
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e
F

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e
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i
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I

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c
a
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d
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e
F

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i
D

Indirect  Feedback  Systems  are  the  most  common  systems  accessible  for  energy 

consumers,  consisting  in  energy  feedback  provided  after  the  consumption.  Indirect 

Feedback may be divided into two different sub-categories:  

a) Standard  billing: common energy bills belong to the first sub-category of Indirect 

Feedback  and  are  usually  provided  by  the  energy  retail  supplier.  This  type  of 

feedback  is  usually  only  describing  the  amount  of  energy  consumed  for  a 

determined  period  of  time  through  a  paper  bill  or  in  an  electronic  format  providing 

little information. 

b) Enhanced  billing:  the  second  sub-category  of  Indirect  Feedback  also  relates  to 

already  measured  energy  consumption,  but  this  type  of  feedback  provides  whole 

house feedback, while giving an historical and social comparison and context. It may 

6 

 
 
 
 
 
 
 
 
be provided by a third party company that analyses the information collected by the 

utility company. 

Standard  billing  a)  as  mentioned  before,  is  the  typical  energy  bill,  that  arrives  with  a 

certain  periodicity  to  the  final  consumer.  Standard  billing  is  the  least  effective  type  of 

feedback  in  terms  of  making  consumers  reduce  energy  consumption  or  energy  waste, 

but it is also a low or no cost option since consumption has to be billed in any case for 

commercial  reasons.  The  type  of  information  in  a  typical  energy  bill  does  not  go  much 

further than the presentation of the cost, type of tariff and a comparison with a similar 

period  of  time.  This  type  of  feedback,  besides  informing  the  final  consumer  to  pay  the 

bill, does not present a strong call for action in any way. It is only an informational and 

non  engaging.  In  some  countries,  the  lack  of  clarity  in  the  bill  is  noticeable,  leading  to 

confusion  and  lack  of  interest.    Annex  VII  of  the  Energy  Efficiency  Directive  gives 

guidance on the type of information to be provided to final costumer.  

Figure 1 – Example of an Italian Standard Energy Bill 

7 

 
 
 
 
  
 
 
 
 
 
The second type of indirect feedback category (b)) is an enhanced type of feedback, that 

can  be  associated  with  the  energy  bill  or  not,  and  is  provided  through  mailings  and/or 

through  a  web  environment  that  can  be  accessible  through  computer  or  mobile  apps. 

The type of information in these advanced indirect feedback systems is more elaborated 

than  the  more  common,  basic  bills,  and  generated  on  the  basis  of  a  variety  of  data 

sources  besides  the  typical  utility  data,  like  assessor  parcel  maps,  home  audits  or 

census.  The  use  of  statistical  data  is  commonly  used  by  third-party  companies  that 

develop  algorithms  to  analyse  existing  data  and  user  input  to  provide  a  more 

personalized  experience  for  the  user.  The  amount  and  quality  of  information  is  then 

much richer with household information and advice, web-based energy audits and billing 

analysis being given. Also behavioural principles are being used in order to promote the 

engagement  of  the  energy  consumers.  Tools  using  gamification  principles  like  social 

comparisons,  goal  setting,  personal  comparison  and  call-to-action  measures  are 

commonly used in these types of feedback systems. 

This  type  of  Enhanced  billing  has  been  developed  in  the  last  years  with  success  by 

companies such as OPOWER, working with utilities and applying recent findings in social 

science. Behavioural science, Big data analytics and user-centric design are seen as the 

tools  for  developing  their  energy  conservation  programs  that  are  then  used  by  the 

utilities to communicate more effectively with their customers.  

Figure 2 – Behavioral science insights in OPOWER Home Energy Reports 

As can be seen in the figure above, the way of presenting the customers performance in 

an  easy  way  to  read  and  understand,  descriptive  and  injunctive  norms  are  used  to 

motivate and reinforce positive behaviour change as the costumer can see where he/she 

stands  in  comparison  with  their  neighbours  and  receive  an  immediate  gratification  for 

example  in  the  form  of  an  emoticon  (e.g.  ).  The  same  applies  for  goal  setting  where 

the costumer is encouraged to commit to a specific goal and subsequently more likely to 

act accordingly. 

8 

 
 
 
 
 
 
Besides  the  common  use  of  a  billing  event  as  a  moment  to  communicate  with  the 

costumer,  companies  choose  also  other  key  moments  throughout  the  year.  There  are 

different moments chosen for engagement where an utility costumer receives some kind 

of communication. The type of communication is not always the same as is the case with 

standard bills, but tailored to a specific occurrence. Some of these moments are already 

depending  on  a  smart  meter  installation,  while  some  can  occur  in  the  presence  of 

traditional  meter  technologies.  For  example,  when  there  is  a  seasonal  change,  a 

communication  piece  is  sent  to  the  consumer  in  order  to  adapt  their  household  for  the 

specificities  of  the  arriving  season,  often  with  advice  on  technologies  to  implement  or 

simple behavioural changes to be incorporated in the daily life.  Other type of moments 

can be when a high bill is expected to come, on a peak day, on a possible rate change or 

in the case of extreme weather or outage. 

The  introduction  of  new  means  to  control  in  an  automatic  and  remote  way  the  spaces 

used  by  final  energy  consumers,  going  towards  a  concept  of  a  connected  home,  where 

control  systems  communicate  with  appliances  and  energy  providers,  can  ultimately 

present  an  opportunity  to  improve  energy  efficiency  both  in  the  Demand  as  in  the 

Energy Supply side. It is here that Direct Feedback comes into play. 

Direct feedback can also be divided into sub-categories: 

(i)  Direct  Feedback  using  In-Home  Displays  (IHD) where a device is installed in 

the home environment allowing the energy user an access of real-time information 

on  the  energy  use,  allowing  energy  users  to  learn  about  the  consumptions  of 

different  appliances  by  turning  on  and  off  the  home  devices,  receiving  immediate 

appliance-specific feedback. The In-House energy Displays are installed by clamping 

the  device  into  the  main  electricity  panel  (for  electric  energy)  allowing  at  least 

information  at  a  household  level,  while  some  can  even  give  a  disaggregation  at  a 

space  level  (kitchen,  living  room,  bedroom).  Lately,  with  the  roll-out  of  smart 

meters, clamping the IHD into the electricity panel has been substituted by a direct 

connection to the smart meter, usually via a wireless system. 

These devices can give information on the energy use in terms of cost and can be 

also associated to a web environment providing extra information allowing for alarm 

setting and goal tracking, if the user wishes. This type of feedback systems cannot, 

however,  be  operated  in  terms  of  demand  response  and  dynamic  pricing  signals, 

since are one-way communication devices. 

(ii) Direct  feedback  with  “Connected  Devices”  and  Automation  is  the  most 

complete and engaging type of feedback before a fully automated system. To reach 

an  accurate  and  effective  feedback  system,  the  user  needs  to  have  their  home 

connected to a central device or web application, being able to control remotely at 

9 

 
 
 
an  appliance  level  the  functionalities  of  the  home,  while  having  the  ability  even  to 

receiving  pricing  signals  and  utility  load  control.  These  types  of  systems  include 

several  features  and  components,  usually  required  to  be  installed  by  the  user, 

ranging  from  in-home  energy  displays,  smart  thermostats,  smart  plugs  and  smart 

lighting  and  appliances.  This  type  of  can  provide  an  appliance  and  end-use 

disaggregated  feedback.  This  type  of  feedback  gives  estimated  appliance  specific 

feedback,  historical  and  social  comparisons.  The  method  being  used  for  this 

disaggregation  named  NILM  (Non-Intrusive  Load  Monitoring)  and  requires  some 

supervision  from  the  energy  consumer,  at  a  first  stage  at  least,  to  set  up  a 

correspondence  between  the  load  signals  and  the  algorithm  to  interpret  such 

signals. 

Although,  like  mentioned  before,  some  companies  are  dedicating  their  action 

towards  Indirect  Feedback,  these  too  can  beneficiate  from  a  connection  to  the 

smart  meter,  thus  providing  more  accurate  and  reliable  information.  There  are, 

however,  companies  that  are  focusing  on  promoting  energy  efficiency  through 

direct    feedback,  using  similar  tools  as  the  ones  described  previously  in  order  to 

give valuable insight to final consumers.  

Figure 3 – Example of direct feedback interface with disaggregation by appliance 

10 

 
 
 
 
 
 
Companies  like  Plottwatt  or  Bidgely  (Figure  5)  provide  direct  feedback  to  costumers 

directly or through utilities in a B2B model, being able to give information up to the level 

of  domestic  appliances.  This  type  of  feedback  reaches  its  full potential  when  connected 

with  a  smart  meter,  while  being  part  of  a  smart  grid,  giving  the  ultimate  possibility  of 

Demand Response, thus potentiating the efficiency of the networks’ efficiency. 

Overall  the  main  differences  between  Indirect  and  Direct  Feedback  can  be  divided  into 

three issues: 

  Frequency: Indirect Feedback has a lower frequency (monthly bills at best in the 

case of standard billing) 

  Medium:  Direct  feedback  uses  IoT  devices  for  communication  between  the  user 

and the utility, while indirect feedback is yet mainly through paper mailing. 

  Communication:  Indirect  Feedback  is  one-way  communication,  while  Direct 

Feedback can be two-way communication between the user and utility. 

1.2. Feedback in the context of the Energy Efficiency Directive 

There  are  provisions  in  the  Energy  Efficiency  Directive  specifically  aimed  at  ensuring 

energy  consumption  feedback.  The  first  is  metering  (Article  9)  and  the  requirement  to  

provide to  final costumers individual meters  for electricity, natural  gas, district heating, 

district  cooling  and  domestic  hot  water  reflecting  the  actual  energy  consumption, 

providing information on actual time of use.  This complements provisions on roll-out of 

smart meters in the Electricy and Gas Market Directives. 

The  second  step  for  energy  feedback  in  the  EED  is  the  use  of  information  from  such 

meters for billing and billing information (Article 10).  

In  terms  of  periodicity  of  the  billing,  according  to  EED  Annex  VII,  bills  on  the  basis  of 

actual  consumption  must  as  the  general  rule  be  provided  at  least  once  a  year.  Where 

smart meters are not available, where technically possible and economically justified: by 

31  December  2014,  billing  information  based  on  actual  consumption  is  to  be  made 

available  at  least  quarterly,  on  request  or  where  the  consumers  have  opted  to  receive 

electronic billing or else twice yearly.  

In the case where meters are not available, the obligation on billing information can be 

fulfilled by a system of self-reading. In such cases, billing and billing information can be 

based on estimated consumption or a flat rate only if the final customer did not provide 

the reading.  

11 

 
 
 
The  critical  point  for  the  mandatory  character  of  accurate  billing  information  based  on 

actual  consumption  is  the  availability  of  individual  metering  equipment  as  stated  in 

Article 9 of the EED.  

Smart  meters  are  expected  to  lead  to  a  reduction  in  energy  consumption  by  changing 

consumer  behaviour  through  information  on  energy  consumption,  and  better  energy 

accounting  overall.  The  European  Commission  has  stated  the  view  that  where  smart 

metering is available to final customers, billing information based on actual consumption 

should be provided on a monthly basis1. 

1

 Cf. 

para 

37 

of  SWD(2013) 

448 

final, 

http://eur-lex.europa.eu/legal-

content/EN/TXT/?uri=CELEX%3A52013SC0448  

12 

 
 
 
 
 
 
                                           
2. Member State NEEAP Analysis 

In the articles 9 to 11 of the Energy Efficiency Directive relating to Metering and Billing, 

the EED aim that final consumers obtain accurate and up to date information relating to 

their energy consumption for all types of energy sources. In the case of Member States 

without the smart meter infrastructure already deployed, there is an obligation for these 

Member  States  to  ensure  that,  by  the  31st  of  December  2014,  billing  information  is 

accurate, based on actual consumption and provided with a minimum frequency as set in 

Annex  VII  of  the  EED.  Also,  in  the  case  of  Member  States  already  implementing  smart 

metering  systems,  the  EED  also  clarifies  some  obligations  for  establishing  minimum 

functionalities  and  obligations  for  market  participants  in  terms  of  billing  information 

based on actual consumption. 

There are five main issues relating to the afore mentioned EED articles that concern the 

objective  of  this  study  and  can  positively  influence  the  increase  of  energy  savings 

through  an  improvement  of  the  information  provided  to  costumers  in  energy  bills  and 

the potentialities arising from the deployment of smart meters infrastructures. These five 

issues  are  the  roll-out  of  smart  meters,  the  measurements  of  individual  energy 

consumptions,  the  information  provided  on  energy  bills,  the  periodicity  of  the  bills  and 

the periodicity of the readings. 

In  terms  of  the  roll-out  of  Smart  Meters,  Brussels  capital  and  Wallonia  and  CZ  are  not 

considering  the  installation  of  a  smart  meter  infrastructure  because  of  not  being  cost-

effective, while AT, BE Flanders, CY, DK, EE, FI, FR, IT, LV, LT, LU, MT, NL, PT, SK, SL, 

ES, SE, UK   are already deploying their smart meter infrastructure.  

To  be  noted  that  FI  and  IT  have  already  the  great  majority  of  energy  consumers 

connected to a remote read meter.  

Pilots  for  the  installation  of  smart  meters  have  been  concluded  on  EL  and  RO  and 

ongoing  in  HU  and  PL.  IE  has  concluded  its  pilot  studies  and  is  starting  a  wide  smart 

meter installation in 2016. 

No information regarding the roll-out of Smart Meters has been described in the NEEAPs 

of BG and DE, while HR was in an evaluation process at the time of the NEEAP writing.  

In the great majority of the Member States the responsible party to implement the roll-

out of Smart Meters are the DSO operating in such markets. 

13 

 
 
 
 
 
 
 
Regarding  the  Individual  consumer  measurements,  the  majority  of  the  Member  States 

have declared to have in place individual measurements for the final energy consumers, 

mainly in electric energy. 

Also for the extended information to be present in energy bills, the majority of Member 

States have in place measures to provide energy consumers with information regarding 

historic  information,  explanation  of  tariffs  and  price  details,  with  many  of  the  Member 

States  using  electronic  based  information  systems  to  provide  further  information  for 

their  customers.  Electronic  reporting  feedback  has  been  mentioned  in  the  BE  Wallonia, 

DK, EE, FI, EL, LU, SE, UK,   

No  measures  regarding  Articles  9-11  of  the  EED  were  presented  by  Germany.  It  was 

only stated that no conclusions on the smart meter service market can be made due to 

analytical difficulties. 

The  periodicity  of  readings  and  billing  are  the  issues  not  thoroughly  outlined  in  the 

NEEAPs.  The  Member  States  with  already  a  Smart  Meter  infrastructure  well  developed 

are able to provide regular monthly or bi-monthly billing thanks to the almost immediate 

readings  allowed  by  the  functionalities  of  the  meters.  Other  Member  States  with  the 

Smart  Meter  process  underway  have  implemented  measures  to  provide  at  least  one 

reading per year, with a periodicity of billing varying from yearly to four times a year. 

14 

 
 
 
 
 
 
 
 
 
Table 2 summarizes the status of the five issues reported in the Member States NEEAPs. 

15 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
Table 2: Status of main issues related to feedback reported in the MSs' NEEAPS. 

Member 
State 

Austria 

Belgium 
Brussels 
Capital 

Belgium 
Flanders 

Belgium 
Wallonia 

Roll out of 
Smart 
Meters 

Individual 
Consumer 
Measurements 

Bill Information 

Periodicity 
of Billing 

Readings 

From 
2012; 
large scale 
deplyomen
t: 
10% by 
2015, 70 
% by 
2017, 95% 
by 2019 for 
all 
electricity 
consumers  
Not until 
2018 

Pilots 
ongoing 
(41000 
meters). 
No final 
decision on 
the roll out 
of smart 
meters 
Not cost 
effective 

Implemented 

Complete 
information 

Smart 
Meter: 1x/ 
month 
Normal 
Meter: 1x/ 
year  

Smart Meter: 
4x/hour for 
electricity 
1x/day for 
gas, plus 
reading 
1x/day 
Normal 
Meter: 
1x/year 

Implemented 

Complete 
information 

Not clear 

At least once 
a year 

Implemented 

Historical information 
and further detailed 
information upon 
request 

Not clear 

At least once 
a year 

Implemented for 
new and refurbished 
buildings 

E-bills with historic 
information, energy 
consumption, advice 

Not clear 

At least once 
a year 

Bulgaria 

No 
information 

Implemented 

Implemented 

Croatia 

Cyprus 

Czech 
Republic 

At an 
evaluation 
stage at 
the time of 
NEEAP 
300k smart 
meters 
with 
structural 
funds aid 
No wide-
scale roll-
out 
foreseen  

Additional 
information on 
energy bills to be 
implemented in 
2014. Type of 
information complete 

From 2014 to 2016 
will introduce clear 
and comprehensive 
energy bills 

No 
periodicity 
indicated. 

No 
information 

No 
periodicity 
indicated 

No 
information 

Implemented 

No information 

No 
information 

No 
information 

Implemented for 
Electricity.  
Heat and Hot water 
meters to be 
installed individually 
in radiators. 

Bills provide 
economic information 
itemizing individual 
parts of the payment 

Monthly 

Quarterly or 
Annual 
Settlements 

16 

 
 
 
Member 
State 

Denmark 

Estonia 

Finland 

France 

Germany 

Greece 

Hungary 

Ireland 

Roll out of 
Smart 
Meters 

Individual 
Consumer 
Measurements 

Bill Information 

Periodicity 
of Billing 

Readings 

Ongoing 
from 2011. 
Up to 2020 
all meters 
will be 
remotely 
read 

Implemented for 
new and refurbished 
buildings. By 2016 
all consumptions 
are to be 
individualized. 

Implemented 

All consumers 
receive information 
on energy 
consumption, 
comparison with 
previous year and 
similar consumers. 
Information 
accessible through 
web app for 
electricity 
consumers.  

Information can be 
accessed through 
web environment 

Quarterly 

Yearly 

Not clear 

Smart meter: 
At least daily 

Starting 
from 2014. 
All meters 
to be smart 
by 2020 
Big 
majority of 
electricity 
and heat 
consumers 
already 
with 
remotely 
read 
meters. 
100 % by 
2020 
expected 
Wide-scale 
roll-out 
ongoing. 
Should be 
completed 
by 2020 

No 
information 
in NEEAP. 
Selective 
roll-out of 
Smart 
Meters by 
2020. 
Pilot 
project 
finished. 
Expected 
80% of 
smart 
meters by 
2020. 
Pilot 
ongoing. 
No wide-
scale roll-
out 
information 
Pilot 
finished. 
Wide smart 
meter 
installation 
to begin in 

Implemented for 
electricity and new 
and refurbished 
projects 

Electronic reports 
and normal bills with 
information and 
advice on savings 

Not clear 

Hourly for 
Smart meters 

Implemented 

All consumers 
receive information 
on energy 
consumption, 
comparison with 
previous  

At least once 
a year 

Once a year. 
Consumers 
can supply 
information 
on their 
consumption  

No information 

No information 

No 
information 

No 
information 

Implemented for 
electricity 

Electronic bills 
available. 
Some natural gas 
consumers can 
access to extended 
information on their 
consumptions. 

At least 
every four 
months for 
electricity 
and gas 

At least every 
four months 
for electricity 
and gas 

Implemented 

Consumption and 
billing data are freely 
available for 
consumers 

No 
information 

Billing made 
according to 
real 
consumption 

Not clear 

Complete 
information with 
consumption 
comparison and 
advice 

Regular 
scheduled 
bills 

Quarterly 

17 

 
 
 
Member 
State 

Roll out of 
Smart 
Meters 

Individual 
Consumer 
Measurements 

Bill Information 

Periodicity 
of Billing 

Readings 

Italy 

2016 for a 
100% 
coverage 
by 2020. 

Already in 
place for 
electricity. 
60% of gas 
smart 
meters 
expected 
by 2018. 

Implemented for 
free market 

Latvia 

Selective 
roll-out 
ongoing 

Implemented for 
new and refurbished 
buildings  

Not clear 

Not clear 

Lithuania 

Luxembourg 

Malta 

No 
indication 
of smart 
meter 
strategy. 
57% of 
Electricity 
already 
with 
remote 
reading  
From 2015 
for all new 
costumers 
and 
costumers 
having 
meters 
replaced. 
95% 
expected 
by 2020 
Implement
ed 

Current Electricity 
and Gas bill already 
comply with EED 
requirements. 
Authority website 
provides further 
information on the 
bills and a 
comparison between 
different energy 
suppliers. 
Smart meter project 
provides complete 
bill information on 
energy 
consumptions. 
Information on 
actual consumption  

Bi-monthly 

4x/hour 

Not clear 

Not clear 

Quarterly 

At least 
yearly 

Information on 
current prices, 
energy consumption, 
comparison with 
same period. 
Possibility to receive 
e-bill.  

At least 
2x/year or 
quarterly if 
requested 

At least 
yearly until 
all consumers 
have smart 
meters 

Implemented 

Complete 
information 

Bi-monthly 

2x/year 
before 
entering of 
Smart Meters 

Not clear for 
non-smart 
meters 

Netherlands 

Ongoing 

Implemented 

Ok for electricity, 
amendments needed 
for heating and 
cooling 

Bi-monthly 
for smart 
meters 

Poland 

Portugal 

Romania 

Starting 
from 2012 
with pilots. 
Roll-out 
ongoing. 
100% 
expected 
by 2020. 
Pilots 
implement
ed. 80 % 
by 2020, 
starting in 
2015 

Not clear 

Not clear 

Not clear 

Not clear 

Implemented 

Information present 
in bills 

Not clear 

Not clear 

Implemented 

NEEAP mentions 
Articles 9-11 are 
already transposed. 
Not clear at what 
extent 

Not clear 

At least 
yearly 

18 

 
 
 
 
Roll out of 
Smart 
Meters 

Individual 
Consumer 
Measurements 

Bill Information 

Periodicity 
of Billing 

Readings 

No information 

No information 

No 
information 

No 
information 

Not clear 

e-portal with 
complete information 
on energy offers 

Not clear 

From 2017 onwards  No information 

No 
information 

At least 
yearly. 
Possible for 
costumer to 
communicate 
monthly 
readings 
No 
information 

Member 
State 

Slovakia 

Slovenia 

Spain 

Sweden 

Ongoing. 
Mandatory 
for 
households 
with 
consumptio
n over 
4MWh 
(22% of 
households
) 
Ongoing 
(29% in 
2013) 

Ongoing. 
To be 
finished by 
2018 
Roll-out 
ongoing. 
100% by 
2020 

UK 

Ongoing 

Implemented 

Information on bills, 
completed by online 
information 

Clear bills with 
information on 
consumptions. Most 
e-bills.  

Quarterly 

Not clear 

Quarterly 

At least 
yearly 

19 

 
 
 
 
 
 
 
 
 
3. Analysis of Meta-data studies on Feedback  

In  order  to  quantify  the  effect  of  feedback  on  energy  consumption,  a  large  number  of 

studies  have  been  carried  out  in  the  past  40  years.  In  this  report  we  refer  to  the 

experiences already summarised in recent literature  review papers, and in particular to 

those of E. Zvingilaite and M. Togeby (Zvingilaite, 2015), and B. Karlin, J. F. Zinger, and 

R.  Ford  (Karlin,  2015).  These  reviews  analysed  past  empirical  studies  on  consumption 

feedback  through  qualitative  methods  of  literature  review,  in  which  a  set  of  empirical 

experiences on a specific topic are collected, classified, and summarised. Doing this task, 

these authors applied some inclusion criteria to ensure that the studies included in their 

analysis pass at least a minimum standard of quality (e.g. by excluding studies that did 

not have a control group as well as those with clear confounding variables). 

In this way we collected a final dataset of 118 feedback applications, which cover:  

  3 consumption types (electricity only, electricity and heating, heating only); 

  16 different Countries (mainly in North America and North Europe); 

  2 feedback types (direct and indirect); 

  6 media types (bill, card, In-House-Display (IHD), mail, PC or web, mixed mode); 

  A large range of sample sizes (from about 10 to almost 100 000 households); 

  Different duration periods (from 2 weeks to 3 years). 

Table  3  shows  the  percentage  energy  savings  achieved  by  all  these  studies,  in 

comparison with the main factors characterising the experiences. 

20 

 
 
 
Table 3: Summary of relevant feedback studies. 

Study 

Consumption 
Type 

Country 

Feedback 
type 

Media 

Frequency 

Sample 
size 

Duration 
[months] 

% Savings 

Allcott (2010) 

Allcott (2009) a 

Allcott (2009) b 

Allen & Janda (2006) 

Arvola et al. (1994)a 

Arvola et al. (1994)b 

Ayres et al. (2013) 

Battalio et al. (1979); Winett 
et al. (1978) 

Becker & Seligman (1978); 
Seligman et al. (1978) Study 
3 
Becker (1978); Seligman et 
al. (1978) Study 2 

Benders et al. (2006) 

Bittle et al. (1979) 

Bittle et al. (1979–1980) 

Brandon and Lewis (1999) 

Electricity 

Electricity 

Electricity 

Electricity 

Electricity and 
Heating 

Electricity and 
Heating 

Electricity and 
Heating 

USA 

USA 

USA 

USA 

FI 

Indirect 

Indirect 

Indirect 

Direct 

Indirect 

FI 

Indirect 

USA 

Indirect 

Bill 

Mixed 

Mixed 

IHD 

Bill 

Bill 

Bill 

Monthly 

Monthly 

2-6 months 

Continuous 

Monthly 

78492 

23530 

15687 

60 

180 

Monthly 

173 

Monthly 

84000 

Electricity 

USA 

Indirect 

Card 

1-4 times/week 

70 

Electricity 

USA 

Indirect 

Card 

1-4 times/week 

20 

Electricity 

USA 

Indirect 

Card 

1-4 times/week 

80 

Electricity 

Electricity 

Electricity 

Electricity and 
Heating 

NL 

USA 

USA 

UK 

IE 

IE 

IE 

Indirect 

PC or Web 

Indirect 

Indirect 

Card 

Card 

- 

Daily 

Daily 

Indirect 

PC or Web 

Monthly 

Indirect 

Indirect 

Mail 

Bill 

2-6 months 

Monthly 

137 

30 

353 

28 

656 

672 

Direct 

IHD 

Continuous 

636 

Carroll et al. (2013), A 

Electricity 

Carroll et al. (2013), B 

Carroll et al. (2013), C 

Electricity and 
Heating 

Electricity and 
Heating 

DECC (2015) 

Electricity 

UK 

Direct 

IHD 

Continuous 

5145 

21 

9 

12 

12 

2 

30 

30 

9 

0.5 

0.5 

0.5 

5 

2 

0.5 

9 

12 

12 

12 

12 

2.4% 

2.0% 

1.5% 

- 

3.0% 

5.0% 

1.2% 

0.9% 

15.7% 

13.0% 

9.0% 

- 

- 

4.3% 

0.4% 

3.0% 

2.0% 

2.3% 

 
 
Consumption 
Type 

Country 

Feedback 
type 

Media 

Frequency 

Sample 
size 

Duration 
[months] 

% Savings 

Study 

DECC (2015) 

DENA (2014) 

Heating 

Heating 

Dobson  and  Griffin  (1992)  in 
Darby (2006) 

Electricity and 
Heating 

D'Oca et al. (2014) 

E.ON/AECOM  2011  a'  (fuel 
poor) 
E.ON/AECOM  2011  a'  (fuel 
poor) 
E.ON/AECOM  2011  a''  (high 
use) 
E.ON/AECOM  2011  a''  (high 
use) 
E.ON/AECOM  2011  a'''  (not 
fuel poor) 
E.ON/AECOM 2011 b' 

E.ON/AECOM 2011 b'' 

E.ON/AECOM  2011  b'  (fuel 
poor) 
E.ON/AECOM  2011  b''  (high 
use) 
E.ON/AECOM 2011 c' 

E.ON/AECOM 2011 c'' 

E.ON/AECOM  2011  c'  (fuel 
poor) 
E.ON/AECOM  2011  c''  (high 
use) 
E.ON/AECOM 2011 d' 

E.ON/AECOM 2011 d'' 

E.ON/AECOM  2011  d'  (fuel 
poor) 
E.ON/AECOM  2011  d''  (high 
use) 
E.ON/AECOM  2011  d'''  (not 
fuel poor) 

Electricity 

Electricity 

Heating 

Electricity 

Heating 

Heating 

Heating 

Heating 

Electricity 

Electricity 

Heating 

Heating 

Electricity 

Electricity 

Heating 

Heating 

Electricity 

Electricity 

Heating 

Continuous 

Monthly 

5145 

145 

Continuous 

< 100 

Continuous 

Monthly 

Monthly 

Monthly 

Monthly 

Monthly 

Monthly 

Monthly 

Monthly 

Monthly 

Monthly 

Monthly 

Monthly 

Monthly 

Mixed 

Mixed 

Mixed 

Mixed 

Mixed 

31 

2639 

2639 

2639 

2639 

2639 

2639 

2639 

1436 

1436 

1436 

1436 

1456 

1456 

1436 

1436 

2524 

2524 

1436 

12 

12 

2 

12 

24 

24 

24 

24 

24 

24 

24 

24 

24 

24 

24 

24 

24 

24 

24 

24 

24 

24 

1.5% 

9.0% 

13.0% 

18.0% 

-2.0% 

4.4% 

2.0% 

2.3% 

3.6% 

6.7% 

2.5% 

-2.0% 

3.0% 

7.2% 

2.4% 

-1.0% 

2.0% 

4.6% 

2.2% 

2.0% 

4.0% 

4.9% 

UK 

DE 

CA 

IT 

UK 

UK 

UK 

UK 

UK 

UK 

UK 

UK 

UK 

UK 

UK 

UK 

UK 

UK 

UK 

UK 

UK 

UK 

Direct 

Indirect 

Direct 

Direct 

Indirect 

Indirect 

Indirect 

Indirect 

Indirect 

Indirect 

Indirect 

Indirect 

Indirect 

Indirect 

Indirect 

Indirect 

Indirect 

Direct 

Direct 

Direct 

IHD 

Mail 

IHD 

IHD 

Bill 

Bill 

Bill 

Bill 

Bill 

Bill 

Bill 

Bill 

Bill 

Bill 

Bill 

Bill 

Bill 

Mixed 

Mixed 

Mixed 

Direct 

Mixed 

Direct 

Mixed 

22 

 
 
 
Study 

E.ON/AECOM 2011 e 

EDF/AECOM 2011 a 

EDF/AECOM 2011 b 

EDF/AECOM 2011 c 

Consumption 
Type 

Electricity and 
Heating 

Electricity 

Electricity 

Electricity 

Garay and Lind-holm (1995) 

Heating 

Garay  and  Lindholm  (1995) 
in Darby (2006) 

Electricity and 
Heating 

Gleerup et al. (2010) 

Haakana (1997) 

Haakana (1997) 

Harrigan and Gregory(1994) 

Hayes & Cone (1981) 

Henryson  et  al.  (2000)  in 
Fischer (2008) 

HER (2012) b 

HER (2012) b 

Houwelingen (1989) a 

Houwelingen (1989) b 

Houwelingen (1989) c 

Electricity 

Electricity 

Heating 

Heating 

Electricity 

Electricity 

Electricity 

Heating 

Heating 

Heating 

Heating 

Hutton et al. (1986) Study 1 

Electricity 

Hutton et al. (1986) Study 2 

Electricity 

Hutton et al. (1986) Study 3 

Electricity 

Hydro One (2006) 

Hydro One (2006) b 

Electricity 

Electricity and 
Heating 

Hydro  One  (2006)  c  (electric 
hot water heating) 

Electricity and 
Heating 

UK 

UK 

UK 

UK 

SE 

SE 

DK 

FI 

FI 

USA 

USA 

DK-SE 

USA 

USA 

NL 

NL 

NL 

USA-CA 

USA-CA 

USA-CA 

CA 

CA 

CA 

Country 

Feedback 
type 

Media 

Frequency 

Sample 
size 

Duration 
[months] 

% Savings 

Direct 

Mixed 

Mixed 

2524 

24 

20 

20 

20 

15 

15 

12 

20 

20 

14 

5 

12 

12 

12 

12 

12 

5 

5 

5 

30 

30 

30 

3.0% 

2.0% 

5.0% 

7.0% 

n.a. 

n.a. 

2.5% 

13.5% 

6.0% 

0.0% 

7.0% 

7.0% 

1.0% 

0.7% 

8.0% 

3.0% 

1.0% 

4.1% 

5.0% 

6.8% 

7.0% 

1.2% 

16.7% 

3500 

n.a. 

Indirect 

Direct 

Direct 

Indirect 

Indirect 

Indirect 

Indirect 

Indirect 

Direct 

Indirect 

Indirect 

Indirect 

Indirect 

Direct 

Indirect 

Direct 

Direct 

Direct 

Direct 

Direct 

Direct 

Mail 

IHD 

IHD 

Mail 

Mail 

Mixed 

Mail 

Mail 

IHD 

Card 

Mail 

Mixed 

Mixed 

IHD 

Mail 

IHD 

IHD 

IHD 

IHD 

IHD 

IHD 

Monthly 

Continuous 

Continuous 

Monthly 

Monthly 

Mixed 

Monthly 

Monthly 

Continuous 

Monthly 

Monthly 

2-6 months 

2-6 months 

Daily 

Monthly 

Continuous 

Continuous 

Continuous 

Continuous 

Continuous 

Continuous 

386 

370 

200 

600 

600 

194 

79 

< 100 

71 

40 

50000 

50000 

50 

50 

50 

371 

377 

336 

500 

500 

Direct 

IHD 

Continuous 

500 

23 

 
 
 
Study 

Consumption 
Type 

Country 

Feedback 
type 

Media 

Frequency 

Sample 
size 

Duration 
[months] 

% Savings 

ISTA (2011) 

Kasulis et al. (1981) 

Katzev et al. (1980–1981) 

Kofod (2013), CUB 

Kurz et al. (2005) 

Heating 

Electricity 

Electricity 

Electricity 

Electricity and 
Heating 

DE 

USA 

USA 

USA 

AU 

Indirect 

PC or Web 

Indirect 

Indirect 

Indirect 

Indirect 

Bill 

Card 

Mail 

Card 

Monthly 

Monthly 

Mixed 

- 

1-4 times/week 

n/a 

390 

22 

2457 

423 

6 

5 

0.5 

n.a. 

5 

14.0% 

- 

15.0% 

4.4% 

0.0% 

Electricity 

DE 

Indirect 

Mail 

1-4 times/week 

19 

n.a. 

3.0% 

Mack  and  Hallmann  (2004) 
Fischer (2008) 

Mansouri  &  Newborough 
(1999) 
Matsukawa (2004) 

McClelland  &  Cook  (1979–
1980) 
Midden et al. (1983) 

Mosler  and  Gutscher  (2004) 
Fischer (2008) 

Mountain (2007) Study 1 

Mountain (2007) Study 2 

Mountain 
Economic 
Consulting  and  Associates 
(2006) 
Nexus 
(2006) 

Software 

Energy 

Nielsen (1992) a 

Nielsen (1992) b 

Nielsen (1992) c 

Nilsson et al. (2014) a 

Nilsson et al. (2014) b 

Electricity 

Electricity 

Electricity 

Electricity 

Electricity 

Electricity 

Electricity 

Electricity 

Electricity and 
Heating 

Electricity 

Electricity 

Electricity 

Electricity 

Electricity 

Pallak  &  Cummings  (1976); 
Pallak et al. (1980) 

Electricity and 
Heating 

UK 

JP 

USA 

NL 

CH 

CA 

CA 

CA 

Direct 

Direct 

Direct 

Indirect 

Direct 

Direct 

Direct 

Direct 

IHD 

IHD 

IHD 

Card 

n/a 

IHD 

IHD 

IHD 

Continuous 

Continuous 

Continuous 

1-4 times/week 

Daily 

Continuous 

Continuous 

Continuous 

USA 

Indirect 

Mixed 

Mixed 

Monthly 

Monthly 

Monthly 

Continuous 

Continuous 

1-4 times/week 

109 

DK 

DK 

DK 

SE 

SE 

USA 

Indirect 

Indirect 

Indirect 

Direct 

Direct 

Direct 

Mixed 

Mail 

Mixed 

IHD 

IHD 

IHD 

24 

31 

319 

101 

95 

48 

118 

110 

552 

249 

500 

500 

500 

20 

13 

2 

5 

9 

2 

1 

15 

15 

15 

5 

36 

36 

36 

1 

1 

2 

20.0% 

1.8% 

12.0% 

13.2% 

6.0% 

18.1% 

2.7% 

6.5% 

19.0% 

10.0% 

8.0% 

7.0% 

0.0% 

0.0% 

16.0% 

 
 
 
Study 

Consumption 
Type 

Country 

Feedback 
type 

Media 

Frequency 

Sample 
size 

Duration 
[months] 

% Savings 

Parker et al. (2008) 

Robinson (2007) 

Schleich et al. (2011) a 

Schleich et al. (2011) b 

Electricity 

Electricity 

Electricity 

Electricity 

Scottish Power/AECOM 2011 

Electricity 

Scottish Power/AECOM 2011 

Heating 

SEAS NVE (2014) 

Seaver & Patterson (1976) 

Seligman  et  al.  (1978)  Study 
1 
Seligman  et  al.  (1978)  Study 
2 
Seligman  et  al.  (1978)  Study 
3 
Sexton  et  al.  (1987);  Sexton 
et  al.  (1989);  Sexton  & 
Sexton (1987) 
Sipe & Castor (2009) Study 1 

Sipe & Castor (2009) Study 2 

SSE/AECOM 2011 a 

SSE/AECOM 2011 b 

SSE/AECOM 2011 c 

SSE/AECOM 2011 c 

Blue 

Summit 
(2009) 
TREFOR a in Kofod (2013) 

Consulting 

Electricity 

Heating 

Electricity 

Electricity 

Electricity 

Electricity 

Electricity and 
Heating 

Electricity and 
Heating 

Electricity 

Electricity 

Electricity 

Heating 

Electricity 

Electricity 

TREFOR b in Kofod (2013) 

Electricity and 
Heating 

Ueno  et  al.  (2005);  Ueno  et 
al. (2006) 

Electricity and 
Heating 

USA 

USA 

DE-AT 

AT 

UK 

UK 

DK 

USA 

USA 

USA 

USA 

USA 

Direct 

Direct 

Indirect 

Indirect 

Direct 

Direct 

n.a. 

Indirect 

Indirect 

Direct 

Direct 

Direct 

IHD 

Mixed 

Mixed 

Mixed 

Mixed 

Mixed 

PC or Web 

Card 

Card 

Card 

IHD 

IHD 

Continuous 

1-4 times/week 

Monthly 

Monthly 

Mixed 

Mixed 

- 

Mixed 

Daily 

Continuous 

Continuous 

17 

141 

1070 

750 

1603 

1603 

276 

75 

< 50 

< 50 

< 50 

Continuous 

269 

USA 

Direct 

IHD 

Continuous 

305 

USA 

Direct 

IHD 

Continuous 

588 

UK 

UK 

UK 

UK 

Direct 

Indirect 

Direct 

Direct 

USA 

Indirect 

IHD 

Bill 

IHD 

IHD 

Bill 

Continuous 

2-6 months 

Continuous 

Continuous 

2500 

1902 

524 

204 

Monthly 

85000 

DK 

DK 

JP 

Indirect 

PC or Web 

Indirect 

PC or Web 

- 

- 

90000 

10000 

Direct 

PC or Web 

Continuous 

19 

15 

5 

12 

12 

10 

9 

12 

5 

1 

0.5 

0.5 

9 

9 

9 

36 

36 

24 

24 

9 

12 

12 

9 

7.0% 

- 

3.7% 

4.5% 

0.0% 

0.0% 

0.0% 

- 

10.5% 

13.0% 

15.7% 

- 

- 

- 

1.0% 

1.0% 

2.0% 

3.0% 

2.3% 

3.5% 

4.7% 

12.0% 

25 

 
 
 
Study 

Consumption 
Type 

Country 

Feedback 
type 

Media 

Frequency 

Sample 
size 

Duration 
[months] 

% Savings 

van Elburg, H. (2008) b 

van Elburg, H. (2008) c 

van Elburg, H. a 

van Elburg, H. c 

van Houwelingen & Van Raaij 
(1989) 
Wilhite & Ling (1995) 

Wilhite et al. (1993) 

Wilhite et al. (1999) 

Winett et al. (1979) a 

Winett et al. (1979) b 

Electricity 

Electricity 

Heating 

Heating 

Heating 

Electricity 

Electricity and 
Heating 

Electricity and 
Heating 

Electricity and 
Heating 

Electricity and 
Heating 

IT 

NL 

LV 

NL 

NL 

NO 

NO 

NO 

Direct 

IHD 

Continuous 

Indirect 

PC or Web 

- 

Indirect 

Bill 

Monthly 

Indirect 

PC or Web 

Direct 

Mixed 

- 

Mixed 

Indirect 

Indirect 

Bill 

Bill 

Monthly 

2-6 months 

1000 

60000 

22 

60000 

235 

1284 

600 

Indirect 

Mail 

2-6 months 

2000 

USA 

Indirect 

Mail 

Daily 

USA 

Indirect 

Mail 

Daily 

12 

24 

12 

24 

9 

15 

36 

24 

1 

1 

2 

0.5 

10.0% 

3.0% 

0.0% 

3.0% 

12.3% 

10.0% 

10.0% 

4.0% 

13.0% 

7.0% 

- 

- 

12 

16 

49 

35 

Winett et al. (1982) Study 1 

Electricity 

Winett et al. (1982) Study 2 

Electricity 

USA 

USA 

Indirect 

Indirect 

Card 

Card 

Daily 

1-4 times/week 

26 

 
 
 
 
3.1 Feedback Studies Breakdown  

In  order  to  contextualise  better  the  results  shown  in  section  4  ("Achieved  Saving 

through Feedback"), we presents below the results of a breakdown analysis for the 118 

studies listed above. Summarising, the following information can be deduced: 

  The  majority  (57%)  of  researches  have  been  carried  out  in  North  Europe 

(mostly  in  UK  and  Scandinavia)  and  more  than  one  third  (37%)  in  North 

America (USA and Canada); other world areas are poorly represented or not at 

all covered (Figure 4a). 

  Large  part  of  studies  (58%)  focused  on  the  electricity  consumptions,  but  also 

the  effectiveness  of  feedback  on  heating  consumptions  has  been  well 

documented (Figure 4b). 

  Probably  due  to  increased  political  focus  on  energy  efficiency  and  rollout  of 

smart  energy  metes  and  online  services  by  energy  utilities,  the  number  of 

studies has increased during the last decade: the 41% of considered researches 

have been carried out after 2010 (Figure 4c). 

  Half  of  studies  were  done  on  samples  between  100  and  1000  households  and 

28% on less than 100 families (Figure 4d). 

  The 82% of experiences have had duration greater than 3 months (Figure 4e). 

  The  majority  (59%)  of  studies  focused  on  indirect  means,  including  feedbacks 

which have been processed in some way before the user receives it (Figure 4f). 

  The  recognised  studies  are  representative  of  a  large  range  of  feedback 

frequencies,  but  the  most  represented  categories  are  those  of  1-4  times/week 

and continuous feedback (generally did with an In-House-Display), respectively 

at 35% and 32% (Figure 4g). 

  Large part of direct feedbacks was done using an In-House-Display (IHD), while 

several  different  media  (but  mostly  by  bill  and  mail)  were  used  to  provide 

indirect feedbacks (Figure 4h). 

27 

 
 
 
(a) 

(b) 

(c) 

(d) 

28 

 
 
 
 
 
 
 
(e) 

(f) 

(g) 

(h) 

Figure 4: Breakdown of studies taken into account. 

29 

 
 
 
 
 
 
 
 
 
4. Achieved Savings through Feedback 

Both theory and past empirical research suggest that feedback may have a key role in 

engaging  users  in  residential  energy  conservation  by  making  consumers  aware  of  the 

energy  impacts  of  the  household  behaviours.  However,  analysing  and  comparing  the 

past  literature,  it  is  important  to  remark  again  that  the  considered  studies  have  been 

differently  designed,  focusing  on  different  energy  consumption  types  and  applying 

different  methodologies.  As  such,  the  effect  of  a  feedback  strategy  relevantly  varies 

based on both how and to whom it is provided. 

For  this  reasons  it  is  not  trivial  to  derive  absolute  evidences  by  analysing  and 

comparing  the  energy  savings  observed.  However  some  general  indications  can  be 

obtained,  by  classifying  and  categorising  the  results  by  the  main  contextual  and 

methodological  characteristics.  In  the  following  chapters  the  results  of  this  kind  of 

analysis are presented and discussed. 

30 

 
 
 
 
 
 
 
 
4.1  Savings  per  consumption  type  and  geographical  area  of  the 

studies  

Firstly  it  is  interesting  to  observe  that  the  main  energy  savings  (around  20%)  were 

recorded  on  the  electrical  consumptions,  independently  of  the  location  (if  we  consider 

as statistically insignificant the two studies labelled as "Extra"). 

Where  the  feedback  was  applied  also  on  the  heating  consumptions,  the  differences 

between North EU and North America are more pronounced: while in USA a maximum 

of 19% was obtained, in North Europe (i.e. in Norway) it was only 10%.  

25%

20%

15%

10%

5%

0%

-5%

North EU South EU North
America

Extra North EU North
America

Extra North EU North
America

Electricity

Electricity and Heating

Heating

Figure 5: Maximum, minimum and average savings per consumption type and 
geographical area. White average bullets refer to dataset composed by few studies (i.e. 
≤3). 

31 

 
 
 
 
 
 
 
4.2 Savings per consumption and feedback type 

By  grouping  the  achieved  results  per  consumption  and  feedback  type  (Figure  below), 

we  can  observe  how  generally  a  higher  (average)  saving  is  associated  to  the  direct 

feedback  respect  the  indirect  one.  This  is  true  when  the  feedback  is  applied  on  the 

electricity  consumption  (7%  versus  5%)  and  on  the  electricity  and  heating  ones  (9% 

versus 7%), but when we analyse the feedback on (only) heating this rule fails. In this 

case  both  maximum  (14%  versus  12%)  and  average  (5%  versus  4%)  savings  are 

higher for indirect feedbacks. 

25%

20%

15%

10%

5%

0%

-5%

Direct

Indirect

Direct

Indirect

Direct

Indirect

Electricity

Electricity and Heating

Heating

Figure 6: Maximum, minimum and average savings per consumption and feedback 
type. 

32 

 
 
 
 
 
 
 
 
4.3 Savings per consumption type and the period of the study 

Looking at Figure 7 it is quite evident how the average savings depend on the year of 

the studies. As the common sense would suggest, the feedback effectiveness is related 

(inversely)  to  the  grade  of  awareness  of  building  occupants:  in  other  words,  the 

feedback  is  more  effective  in  presence  of  a  less  conscious  behaviour  of  the  users. 

Assuming  that  awareness  is  increasing  over  time,  this  could  explain  that  for  all 

consumption  types  the  average  savings  before  1990  are  greater  than  those  recorded 

after  2010.  Also  the  fact  that  appliances  and  buildings  in  general  tend  to  be  more 

efficient can be an explanation for this decrease. 

25%

20%

15%

10%

5%

0%

-5%

Before
1990

Between
1990 and
2010

Electricity

After
2010

Before
1990

Between
1990 and
2010

After
2010

Before
1990

Electricity and Heating

After
2010

Between
1990 and
2010

Heating

Figure 7: Maximum, minimum and average savings per consumption type and the 
period of the study. White average bullets refer to dataset composed by few studies 
(i.e. ≤3). 

33 

 
 
 
 
 
 
 
 
4.4 Savings per feedback type and medium 

About  media,  this  analysis  reveals  that  the  maximum  saving  is  achieved  with  a 

continuous  (direct)  feedback  provided  by  an  In-House-Display  (IHD)  and  that  the 

indirect feedbacks provided with card (e.g. door hanger or other card/sign provided to 

the  household  by  the  researchers)  are  more  effective  than  those  provided  by  other 

means (excluding mixed modes). The strategies using bills are certainly more replicable 

and can be extended to higher sample (see Figure 9) due to their lower specific costs, 

while their effect also seems to be smaller (4% in average and 10% maximum). 

25%

20%

15%

10%

5%

0%

-5%

IHD

Mixed

Bill

Mail

PC or Web

Card

Mixed

Direct

Indirect

Figure 8: Maximum, minimum and average savings per feedback and medium type. 

34 

 
 
 
 
 
 
50,000

40,000

30,000

20,000

10,000

0

IHD

Mixed

Bill

Mail

PC or Web

Card

Mixed

Direct

Indirect

Figure 9: Average dimension of samples per feedback and medium type. 

Looking  forward,  one  could  consider  that  the  quantity  of  time  spent  interacting  with 

computers  and  smart  devices  has  considerably  increased  in  the  past  years.  So  in  the 

future,  computerised  and  interactive  feedback  will  have  more  opportunities  to  engage 

users  for  longer  or  more  frequent  periods  of  time.  This  suggests  that  digitised  media 

may  augment  feedback  effectiveness.  A  more  specific  discussion  is  needed  on  what 

type of technological medium can/should be chosen over another, since the interactivity 

may change a lot depending on the type of medium, the customer segment and many 

other variables such as the detailed design and usability of any, software, hardware or 

written material involved. For instance, if you have an IHD needing an active prompting 

action as your only mean to get feedback versus a push notification from a smartphone 

that  warns  you  during  different  energy  consumption  moments  and  may  guide  on  how 

to proceed in order to potentiate energy savings. 

35 

 
 
 
 
 
 
 
 
4.5 Savings per feedback type and frequency of interaction 

Theory  suggests  that  frequent  feedback  is  more  effective  than  infrequent  feedback 

(because it helps link actions with consequences) and this is generally verified looking 

at  the  Figure  below.  The  average  savings  obtained  with  indirect  feedbacks  are 

proportional with frequency and the absolute maximum saving has been observed with 

a  continuous  feedback  provided  by  IHD.  In  accordance  with  previous  studies, 

immediate feedback (the occupant is able to refer to the feedback directly after taking 

action)  is  particularly  effective  during  a  learning  phase,  when  the  user's  attention  is 

focused on specific action goals. 

25%

20%

15%

10%

5%

0%

-5%

y
l
i

a
D

s
u
o
u
n
i
t
n
o
C

k
e
e
w
/
s
e
m

i
t
4
-
1

d
e
x
i
M

y
l
i

a
D

y
l
h
t
n
o
M

s
h
t
n
o
m
3
-
2

d
e
x
i
M

k
e
e
w
/
s
e
m

i
t
4
-
1

Direct

Indirect

Figure 10: Maximum, minimum and average savings per feedback type and frequency 
of interaction. White average bullets refer to dataset composed by few studies (i.e. 
≤3). 

36 

 
 
 
 
 
 
 
 
 
 
 
4.6 Savings per feedback type and duration of the study 

Another variable influencing the effectiveness of a feedback is the duration over which 

feedback  is  provided.  Over  time,  occupants’  attention  may  shift  as  they  move  from 

initial  task  learning  to  the  satisfation  of  a  usual  goal.  Thus,  the  duration  over  which 

feedback is provided may impact how the  feedback message is interpreted and  where 

the users’ attention is subsequently directed. 

Data  shown  in  Figure  11  suggests  that  the  average  energy  savings  decrease  with 

increasing duration, both for direct and indirect feedback. 

The  fact  that  for  short-term  studies  are  achieving  larger  energy  savings  may  be 

explained to a natural consumer engagement from the interest  gained in the beginning 

of the studies, which may fade away further down the time.  

25%

20%

15%

10%

5%

0%

-5%

Less than 3
months

Between 3
and 12
months

Direct

More than 12
months

Less than 3
months

More than 12
months

Between 3
and 12
months

Indirect

Figure 11: Maximum, minimum and average savings per feedback type and duration of 
the study. 

37 

 
 
 
 
 
 
 
5. Conclusions and Discussion 

By evaluating the EU Member States NEEAPs some considerations may be: 

 

the roll-out of Smart Meters may allow for accurate and up to date energy data, 

but there is still a long way to go before it becomes a reality in all EU Member 

States.  Real  time  and  direct  feedback  is  necessary  to  harness  the  full  energy 

savings potential of such smart meters; 

 

requirements on individual consumers measurements  exist in practically all EU-

28; 

  minimum requirements for billing exist in the majority of Member States; 

 

the  frequency  of  readings  and  billing  still  needs  to  be  looked  into  with  further 

attention  by  the  responsible  entities.  Readings  once  a  year  can  be  considered 

too little and lacking ambition considering the potential savings. 

In  general,  the  literature  finds  that  feedback  can  reduce  the  households'  energy 

consumption up to realistic 5 to 10% and that it works best when it is:  

 

tailored to the householder; 

  presented clearly and engagingly; 

  accompanied by advice for reducing energy consumptions;  

  delivered regularly and with high frequency;  

  made through enhanced billing versus standard billing; 

 

in the presence of In Home Devices, Web Based, interactive and digital;  

  capable of providing information by appliance (even if cases are still rare);  

  associated with a well-defined and challenging goal.  

However,  there  are  relevant  uncertainties  from  the  literature  and  significant  gaps  still 

remain  in  our  knowledge  of  the  effectiveness  and  cost  benefit  of  feedback.  In 

particular: 

 

 

the effect of feedback on consumers in different social and demographic groups;  

the effect of feedback on appliance purchasing decisions;  

  whether  feedback  continues  to  work  over  time  or  whether  it  needs  to  be 

renewed/reshaped 

to  keep  householders  engaged  and  maintain  any 

conservation effects.  

 

the  ability  for  feedback  to  facilitate  the  sharing  of  energy  information  between 

households, friends or neighbours is almost entirely unexplored;  

38 

 
 
 
 

the divergence of cost-benefit calculations for feedback with advanced metering 

infrastructure needs to be explored as does the conditions under which the costs 

of feedback outweigh the benefits.  

Although awareness of energy consumption has been increasing throughout the years, 

proactive  actions  towards  final  energy  consumers’  awareness  of  their  energy 

consumptions  and  actions  on  how  to  improve  their  energy  efficiency  present 

themselves as a potentially effective way to reduce energy consumption. 

It is important that the engagement of the final energy consumers is sustained in order 

to  minimize  the  novelty  aspect  of  a  new  way  of  energy  feedback  fading  away  after 

some  time.  Two-way  communication  from  the  energy  provider  and  final  energy 

consumers is recommended. Gamification tools like the comparison with similar energy 

consumers  or  the  sense  of  gratification  when  the  consumer’s  energy  performance 

improves and is communicated towards the final consumer may pose as a good solution 

for the continuous engagement of consumers.  

The  frequency  of  the  feedback  moments  is  another  crucial  point  in  terms  of  the 

continuous engagement of final energy consumers. While too many feedback moments 

may  become  somewhat  of  a  nuisance  for  the  final  energy  consumers,  a  balance 

between too many and too few feedback moments should be studied and considered. 

With  the  evidence,  from  the  evaluated  studies,  that  a  bigger  frequency  of  feedback 

leads  to  greater  energy  savings,  it  may  be  considered  that  the  consumption  readings 

(at least once a year) and the billing info (twice a year) required in the EED provisions 

may be increased for the sake of enhancing energy savings. The possibility for reducing 

the periodicity of feedback moments, not only in the periods respecting to the payment 

of the bill, but other dedicated moments throughout of the year,  could also be looked 

into,  since  it  has  been  shown  that  dedicated  feedback  leads  to  a  bigger  consumer 

engagement and consequently bigger energy savings. 

Although  the  full  smart  meter  roll-out  in  Europe  is  as  yet  a  reality  in  only  a  few  EU 

countries, the potentialities that such an infrastructure may arise, in terms of efficiency 

both for the demand as for the supply side, suggests that an even greater boost should 

be  given  to  the  implementation  of  smart  meters  European  wide.  The  results  of  the 

meta-studies analysis is a clear proof of this, with the direct feedback through In-House 

Displays presenting the bigger savings. 

39 

 
 
 
 
40 

 
 
 
 
 
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46 

 
 
 
 
 
 
 
 
 
 
 
ANNEX I 

Summaries of DG ENERGY/Joint Research Centre’s workshop presentations on 
“Provision of consumption information to final customers - EC support to the 
Implementation of EED Article 10 in relation to billing information” taken place on the 
21st of January 2016. 

47 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
I.1  Informative  billing  and  energy  consumption  –  Sarah  Darby,  University  of 
Oxford, UK 

Three reasons for improving feedback 

  Educational  –  without  feedback,  nobody  learns.  Everyone  needs  it,  from 

customers to policymakers, designers and regulators. 

  Economic – need well-informed energy users for effective markets. 

  Cognitive  /  awareness  –  a  lot  of  energy  flows  ‘invisibly’  in  pipes,  radiators, 

appliances etc. 

Informative billing is one form of energy feedback and belongs within quite a complex 
‘information  environment’,  within  and  beyond  the  home.  Customers  know  something 
about  what  their  home  is  like,  the  number  and  type  of  appliances  and  lights,  heating 
system  and  household  activities.  The  supplier  can  supplement  this  with  detailed 
information about their energy consumption and about weather conditions (i.e., offering 
adjustments to heating consumption if appropriate).  

Billing  feedback  (historic  or  comparative)  in  large-scale  trials  or  programmes  such  as 
OPower,  has  typically  led  to  durable  savings  of  2-3%  compared  with  control  groups 
with no such feedback.  

Online  feedback  typically  ineffective  (relies  on  customer  ‘opting  in’).  Very  little 
information  to  date  on  effectiveness  of  phone  apps.  Should  not  see  online/apps  as 
alternatives to billing feedback or to IHDs: they all act in different ways and in different 
contexts. Best seen as complementary. 

‘More is more’. Multiple feedback/information modes have more effect on demand than 
just one. Billing feedback typically more effective if combined with feedback from an in-
home  display  (IHD)  and/or  advice  and/or  an  educational  programme  and/or  time-of-
use price signals. As the report from the Irish smart meter trials noted, ‘Results come 
from  a  combination  of  technology,  price  signal  and  customer  engagement’. 
(Engagement included bimonthly energy reports and IHDs.) 

Early learning from GB smart meter rollout (where all householders are offered an IHD 
and installers are trained to explain them), shows that  

  Effective  residential  smart  metering  involves  installing  a  new  piece  of  equipment 
AND  enabling  users  to  understand  and  use  it.  Smart  metering  enables  demand 
reduction and demand response IF there is good feedback.  

  Useful  synergies  between  feedback  from  informative  bills,  IHDs,  energy  reports, 
energy advice (e.g. from housing association, local authority) and energy efficiency 
programmes.   

  After  2-3  years  of  installations,  there  were  measured  reductions  of  2.3%  in 
electricity  and  1.5%  in  gas  compared  with  traditionally-metered  customers.  Scope 
to improve as everyone involved learns from experience.  

  ~60% of the 2000 smart-metered customers interviewed were still using their IHDs 

between 6 months and >2 years after installation. 

  Householders  who  made  IHDs  part  of  the  household  and  used  them  to  check  on 
trends  and  exceptions  in  their  energy  consumption  over  time  (a  ‘monitoring 
approach’)  were  more  likely  to  be  experiencing  benefits,  including  savings,  than 
those who just used them to check real-time demand of appliances and who tended 
to  lose  interest  after  a  few  weeks.  Need  to  encourage  ‘monitoring  approach’  in 
support.  
installer 

advisory  material 

explanations, 

follow-up 

and 

48 

 
 
 
(https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/40
7568/8_Synthesis_FINAL_25feb15.pdf). 

I.2  The  question  of  energy  reduction:  The  problems  with  feedback  -  Kathryn 
Buchanan, University of Essex, UK 

Aim  of  presentation:  to  outline  some  of  the  problems  that  I  believe  are  associated 
with  giving  feedback  to  householders  about  their  energy  use  via  an  in-home  display 
(IHD).  While  focusing  on  the  negative  side  of  feedback,  this  does  not  mean  I  am  not 
“anti-feedback”. In fact, I recognise that it can have real and tangible benefits such as 
increased  awareness,  knowledge  of  energy-related  issues,  and  can  prompt  people  to 
engage  in  energy  saving  actions.  However,  through  pinpointing  the  problems 
associated  with  feedback  we  can  reframe  them  as  challenges,  so  that  we  can  start  to 
move  towards  identifying  solutions  to  maximize  the  effectiveness  of  feedback-related 
initiatives. 

Observation: Variation in estimates the exact amount of savings that can be achieved 
via feedback. Three reasons for this variation.  

1.  Differences between study in terms of key variables, namely, length of trial, 

target population, frequency, type and quality of feedback employed. 

2.  Differences in methodological rigour.  
3.  Feedback cannot reduce energy use by itself rather it depends on and requires 

human action and interaction (referred to as “the human factor”). 

Challenges associated with the “human factor”: 

  Lack of interest from some consumers’ pre and post-acquisition. Only those 

interested may engage with the IHD. Novelty of IHD may wear off over time.   

  Financial motivations – Small financial savings may undermine willingness to 

engage in energy saving actions or may appeal to those who are already using 
less than  But what level of monetary savings are required to motivate 
behaviour change? Also, can realising the cost of energy-practises legitimize 
them? 

  Comprehension –consumers sometimes do not understand their IHD; consumers 
that are more highly educated reported being more likely to use their IHD to 
save energy than those less well-educated; IHD do not explicitly link each 
energy-use activity in the home to cost, instead onus is on household to figure it 
out and they do not always get it right. 

  Evaluation – how do people decide whether their energy use is good or bad? 
Evaluation is key because it precedes action. Some IHD include features 
designed to guide evaluative process, but do these always act in the desired 
ways? Possibility for rebound effects where any energy savings are re-invested 
into further energy consumption. 
Individual Differences – can a one-size fits all approach really be justified? 
Danger of reeling in those who are already “energy-engaged” with more 
information provided via IHD, rather than drawing in the “non-energy-engaged” 
who may have more scope for reduction. 

 

  Action Potentials – energy saving actions are limited by people’s circumstances 

(e.g., if renting than may be the landlords prerogative to install insulation but 

49 

 
 
 
 
 
 
 
not really any governmental policy that incentivizes this) and perceptions of 
“essential” energy use.  

Recognise  that  the  success  of  feedback  depends  on  user-engagement  or  the  ‘human 
factor’. We should strive for ‘smarter design’ that keeps the “Human Factor” in mind. 

Beyond  IHD  design,  also  needed  are:  fun,  informative,  and  engaging  marketing 
campaigns,  customer  support  for  the  IHD  from  pre  to  post-acquisition  and  policy  that 
supports householders in energy efficiency. 

I.3  Observation,  Experimentation,  and  Notification:  Energy  feedback  as  a 
means  of  engaging  customers  and  reducing/shifting  consumption  -  Karen 
Ehrhardt-Martinez, Navigant, US 

Research indicates the  energy  feedback  can help households to pay  more attention to 
their  energy  consumption  and  to  take  actions  to  reduce  energy  demand.  Feedback 
triggers attention and action by making energy more visible and meaningful. Different 
types of feedback appear to elicit different levels of energy savings and different sets of 
actions  on  the  part  of  households.    Households  are  inspired  to  act  in  response  to  a 
variety  of  factors  and  economic  concerns  appear  to  be  less  important  than  most 
policymakers tend to believe.  Some evidence suggests that households may not have 
to pay attention to feedback consistently in order to benefit. 

Invisibility  of  Energy  and  Ability  to  Observe  Consumption.    Modern  energy 
systems provide households with convenient but largely invisible sources of energy for 
heating,  cooling,  lighting,  cooking  and  a  variety  of  other  end  uses.  However  the  shift 
from  wood,  coal,  and  candles  to  modern  energy  sources  has  created  a  rift  between 
people  and  the  energy  that  they  consume,  making  it  highly  difficult  for  people  to 
monitor or manage their energy consumption.  Instead electricity and natural gas flow 
invisibly into our homes and modern energy units (kwh or therms) hold little meaning 
for  most  people.    As  a  result,  most  people  don’t  know  how  much  energy  their 
household  consumes  and  when  they  do,  they  often  don’t  know  which  end  uses  are 
responsible for the majority of that consumption, whether their level of consumption is 
reasonable  or  unreasonable,  or  where  they  should  target  efforts  to  reduce 
consumption.  Feedback creates an opportunity to make energy more visible, enhance 
people’s knowledge and understanding of their energy consumption patterns and ways 
to save energy, and give meaning to modern energy measures of consumption. 

Triggering  of  Experimentation,  Actions  and  Savings.  A wide variety of  research 
studies  clearly  indicate  that  feedback  is  effective  at  generating  energy  savings,  and  a 
growing  number  of  studies  are  painting  a  clearer  picture  as  to  the  actions  that 
households are taking in order to generate those  savings. This research suggests that 
different  types  of  feedback  generate  different  types  of  actions  and  different  levels  of 
savings.  Indirect forms of feedback such as home energy reports and daily or weekly 
feedback  (often  provided  online  via  a  web  portal)  tend  to  generate  household  level 
savings between 3.5 and 8.5% while direct forms of feedback provided in real time or 
near  real  time  by  smart  meters  and  in-home  displays  or  mobile  devices,  tend  to 

50 

 
 
 
 
 
 
 
 
 
generate savings of 9 to 12%.  Some research suggests that indirect feedback may be 
better for generating changes in energy consumption from large end use demands such 
as space heating and cooling while direct feedback may be better at changing demand 
associated  with  smaller  end  uses  such  as  plug  loads  and  devices.    Expert  advice 
continues  to  play  a  critical  role  in  guiding  energy  savings  associated  with  indirect 
feedback  and  large  end  use  demands,  whereas  direct  sources  of  feedback  tend  to 
generate  savings  via  in-home  experimentation.  Evidence  from  a  recent  study  that 
looked  at  self-reported  behaviors  across  three  types  of  feedback  (enhanced  billing, 
online,  and  real-time  displays)  suggests  that  feedback  is  much  more  likely  to  induce 
behavior-based  approaches  rather  for  reducing  energy  consumption  (as  opposed  to 
investments  in  more  energy  efficient  equipment)  regardless  of  the  type  of  feedback 
provided.    Despite  the  predominant  focus  on  behavior,  households  with  enhanced 
billing were more likely to focus on turning things off and using alternative technologies 
(CFLs  versus  incandescent  bulbs  for  example).    Households  who  received  online 
feedback were more likely to focus on conservation behaviors (washing and drying full 
loads  of  laundry  or  air  drying  laundry,  for  example)  and  also  embraced  alternative 
technologies.    Households  who  received  real-time  feedback  tended  to  have  the  most 
varied  energy  saving  strategies  but  were  more  included  to  focus  on  conservation 
settings  (on  appliances),  enhanced  control  mechanisms  like  timers  and  smart  strips, 
and maintenance activities. 

Evolving  Use  of  Notifications  (and  other  means)  to  Inspire  Attention  and 
Action.    While  feedback  is  a  great  way  to  provide  households  with  useful  energy 
information  and  to  frame  that  information  in a  way  that  provides  meaning,  household 
energy  feedback  may  not  be  effective  and  getting  all  households  to  pay  attention  to 
their  consumption  patterns  and  levels  or  to  hold  the  attention  of  households  for  long.  
We need to move beyond the three underlying myths that 1) people will act rationally 
and do things that are in their best interests, 2) economics are always the best means 
of  motivating  action,  and  3)  people  need  to  continuously  pay  attention  to  feedback  in 
order  for  it  to  be  effective.    Social  science  research  provides  valuable  insights  that 
suggest that people often act in ways that are best described as predictably irrational, 
that the benefits  of economic incentives are  often short lived and  sometimes  counter-
productive, and that people aren’t always aware  of what will motivate them to action.  
Finally,  a  growing  field  of  research  has  begun  to  assess  whether  households  need  to 
consistently  monitor  feedback  in  order  for  it  to  be  effective.    Instead  of  the  need  for 
regular monitoring, these approaches are increasingly looking to models that leverage 
seasonal changes, life events and notifications associated with energy usage thresholds 
as  a  means  of  encouraging  attention  to  energy  issues  in  those  instances  when  such 
attention is most warranted.    

Policy  Take  Aways.    Feedback  has  proven  to  be  an  effective  approach  for  reducing 
energy  consumption  because  it  makes  energy  more  visible  and  meaningful  to 
households.  Different types of feedback tend to generate different  types of action and 
different  levels  of  savings  and  these  factors  should  be  taken  into  consideration  when 
developing a strategy for providing feedback.  The effects of feedback can be enhanced 
through  a  variety  of  strategies  that  motivate  households  to  take  action.    While 
economic  incentives  may  play  a  role  in  motivating  action,  their  effects  can  be  short 
lived  and  may  even  be  counterproductive.    It  is  important  to  look  to  other  means  – 
such  as  social  norms,  opt  out  strategies,  and  public  commitments  –  for  motivating 
household  engagement  and  action.    Finally,  temporal  strategies  may  also  play  an 
important role in encouraging households to pay attention to their energy consumption 

51 

 
 
 
 
 
at  those  key  moments  that  matter  most,  thereby  avoiding  attention  fatigue.    Taken 
together,  these  approaches  can  help  maximize  the  energy  savings  from  household 
energy feedback. 

I.4.  Empowering  Customers  to  Save  Energy  by  informative  Billing:  The 
Empowering Project - Stoyan Danov, CIMNE, Spain 

The project develops and implements a range of services and software tools aiming at 
empowering the energy utilities’ customers and helping them to save energy on a basis 
of information they receive on their energy bills or through online tools.  

The services are developed in two iterations and then implemented over a population of 
more  than  344.000  consumers.  The  service  effectiveness  is  evaluated  in  terms  of 
energy  savings,  user  acceptance  and  satisfaction.  The 
technical  and 
organisational  factors  influencing  the  successful  implementation  at  the  utilities  are 
analysed.  

legal, 

The project achieves measurable savings within the action and provides an open source 
software infrastructure, guidelines and dissemination for widespread service application 
and durable impact after the action. 

Results of the project: 

  Powerful  open  source  solution  for  big  data  analytics  and  a  portfolio  of  billing 
information  services  adapted  to  the  European  market  and  data  protection 
legislation. 

 

Implementation and testing in 4 utility pilots in Austria, France, Italy and Spain 

  Considerable  interest  in  the  solution  due  to  the  flexibility  and  the  utility-tailored 
implementation  approach:  Two  additional  utilities  adopted  the  services  within  the 
execution  phase  of  the  project  and  more  than  20  utilities  expressing  interest  in 
adopting the Empowering solution in the next years. 

  Energy savings up to 15% achieved among the users in 3 of the 4 pilots during the 

first 6 months of  pilot operation 

Lessons learnt & Recommendations: 

Regulation for improved consumption information: 

  Clear and unified procedures for metering data exchange between DSO and energy 
retailer  are  necessary  to  assure  data  availability  soon  after  consumption  is 
produced. Retailers are more interested in offering services to their customers. 

  Considering certain billing information services as end-user energy saving actions of 

the energy suppliers will incentivise their widespread adoption 

Considerations for technical implementation at utilities: 

  Billing information  services  should  be  ideally integrated  with  the  billing  IT  systems 
at  the  utilities  and  should  use  verified  consumption  data  in  order  to  inspire 
confidence. 

52 

 
 
 
 
 
 
 
 
  Customers should have an easy access to the services through multiple channels.  

  Offering services to the whole customer population (opt-out) is more effective than 
searching  pro-active  registration  by  customers  (opt-in).  From  the  tested  solutions, 
the  combination  of  Energy  Report  and  Online  Self-assessment  Tools  proved  more 
effective than each of the solutions offered separately. 

Organisational aspects for implementation: 

  The  successful  implementation  at  the  utilities  requires  the  creation  of  cross-
department  team  involving  Marketing,  IT  and  Customer  Service  staff,  and 
continuous support by the general management. 

  Presentation  of  the  services  to  the  customers  should  be  done  once  they  are 
technically  operational  to  avoid  false  expectations.  Customer  engagement  is  a  key 
for success. 

I.5 Provision of historical consumption data to drive energy efficiency  - Giulia 
Gioffreda, Opower, UK 

Behavioural energy efficiency programmes are built on a single  powerful idea: that 
providing  people  with  better  information  about  their  energy  use  motivates  them  to 
use  less. It’s a premise pioneered by social science and proven by years of rigorous 
testing.  When  utility  customers  start  receiving  proactive,  personalized  insights  into 
reducing  their  energy  waste,  they  pay  attention  and  start  changing  their  behavior. 
That,  in  turn,  transforms  them  into  a  clean  energy  resource.  Engaged  utility 
customers  use  less  electricity  than  their  peers,  generate  fewer  carbon  emissions, 
and ease demand on the  grid. They also save money on their bills and think more 
highly of their energy providers. 

There  are  5  principles  that  we  always  follow  at  Opower  when  helping  utilities  to 
improve their communication with consumers: 

53 

 
 
 
 
 
 
 
 
    
1. Design for how people actually behave  

2. Assume people don’t care  

3. Always lead to action 

4. Aim for lasting relationships  

5. Build for everyone who receives a utility bill 

Those 5 principles are always combined with behavioural science techniques, such as 
the  use  of  neighbor  comparison;  social  norms;  loss  aversion  principle;  reciprocity 
principle;  setting  an  EE  goal;  use  a  format  of  communication  designed  for  limited 
attention span (etc.). 

Most of the times the problem isn’t the quantity of the content. It’s the quality. Many 
utilities are falling back on messaging that’s generic, redundant, and fails to provide 
much  value.  And  all  too  often,  their  BEE  programs  are  following  suit.  To  capture 
customers’  attention  and  achieve  long-term  energy  savings,  utilities  need  to  talk  to 
their customers as individuals, sharing highly personalized content that mirrors their 
own  experiences  and  preferences.  Timing  is  also  critical.  A  2012  study  from 
Accenture  found  that  customers  spend  just  9  minutes  a  year  engaging  with  their 
energy providers.  It’s imperative that utilities increase the moments to  engage their 
customers. Billing information should reach consumers at least monthly. 

Behavioural  energy  efficiency  should  always  be  scientifically  measured.  A  high  level 
of  measurement  rigor  is  achieved  through  careful  experimental  design,  and 
specifically  by  implementing  randomised  control  trials.  A  randomised  controlled  trial 
(RCT)  is  a  specific  type  of  scientific  experiment  and  is  the  gold  standard  for  clinical 
trials.  In  such  trials,  RCTs  are  often  used  to  test  the  efficacy  or  effectiveness  of 
various  types  of  medical  interventions  within  a  patient  population.  RCTs  may  also 
provide  an  opportunity  to  gather  useful  information  about  adverse  effects,  such  as 
drug  reactions.  RCTs  have  also  been  recognized  as  the  gold  standards  to  evaluate 
behavioural energy efficiency.2     

I.6 Consumer Organisation perspective - Gillian Cooper, Citizen Advice, UK 

Our  predecessor  body,  energywatch,  made  a  super-complaint  about  energy  billing  in 
2005. Energywatch believed that poor quality bills and billing processes created a barrier 
to:  

  enable consumers to make informed decisions about their level of usage, budget 

for their usage or understand the value of switching to another supplier;  

  effective  competition  in  the  energy  market,  with  customers  retained  by 

obfuscation of essential data; and   
the take up of energy efficiency measures   

 

Since the super-complaint, there have been a number of changes made to energy bills 

 

Information  requirements  changed  as  a  result  of  Ofgem’s  Energy  Probe  (2008-
2009)  and  Retail  Market  Review  (2010-2013)  as  well  as  the  transposition  of 
European Directives: all were intended to boost market participation 

2  Evaluation,  Measurement,  and  Verification  (EM&V)  of  Residential  Behavior  Based 
Energy  Efficiency  Programs:  Issues  and  Recommendations,  SEE  Action  Network,  May 
2012. 

54 

 
 
 
 
 
                                           
 

Individual  changes  -  tariff  name,  annual  consumption,  translation  of  kWh  to 
services - all well-intentioned, but 

  Taken together, these changes mean bills are longer and more complex 

Research  conducted  by  Citizens  Advice  in  2014-15  show  that  while  the  majority  of 
consumers are satisfied that they understand their energy bills, they  are more likely to 
have problems with:  

  Understanding the cost per unit  
  Understanding  how  much  energy  has  been  used  and/or  whether  there  an 

opportunity to save money by reducing energy use or switching supplier 

What Citizens Advice thinks needs to happen next with energy bills: 

  Rollout of smart meters will improve accuracy of historical billing information 
  BUT consumers will need help with behaviour change  
  Regulatory  requirements  are  an  opportunity  and  a  challenge  when  it  comes  to 

improving energy bills 

  Key information on bills must be provided in a comparable format 
  Bill  content  and  presentation  must  reflect  consumers’  preferences  and  greater 

differentiation is needed between bills and annual statements 

  Must  take  into  account  the  needs  of  different  groups  of  consumers,  as  research 
shows active consumers react to lack of trust in suppliers by scrutinising company 
communications & bills and by switching supplier and inactive consumers react by 
becoming more inactive 
Introduce improved protections for consumers from inaccurate bills to ensure the 
smart meter rollout delivers consumer benefits 

 

What Citizens Advice is doing:  

  Providing  advice,  help  and  practical  tools  to  inform  and  educate  energy 

consumers 

  Carrying out research looking at alternative ways to engage energy consumers 

I.7 The regulator perspective - Marielle Liikanen , CEER 

CEER  believes  that  the  current  provisions  from  the  Energy  efficiency  directive  are  not 
sufficiently  applied,  implemented,  and/or  upheld  to  guarantee  easily  accessible, 
sufficiently  frequent,  detailed  and  understandable  information  on  consumers’  energy 
intake.  Closer  coordination  between  sector  specific  regulators  and  consumer  authorities 
is  needed  to  achieve  the  goals  of  the  EED.  New  developments  e.g.  smart  metering  will 
also  lead  to  improvements  in  the  information  provided  to  consumers  and  how  it  is 
presented 

I.8 The consumer perspective - Zoe Mcleod, OnTheRecord, UK 

OnTheRecord is a new social enterprise. Our mission is to make businesses better so as 
to  save  customers  time  and  money.  We  have  a  particular  focus  on  improving 
accessibility to services, especially for customers with disabilities. 

Consumer benefits 

55 

 
 
 
 
 
 
 
 
 
It  is  important  that  any  regulation  on  billing  and  energy  information  is  focused  on  the 
desired consumer outcomes. From a consumer perspective the key benefits are: 

  Energy  reduction  and  shifting  –  to  help  customers  reduce  costs  and  carbon. 
Consumers  may  interpret  information  and  use  this  to  take  action  themselves, 
with the help of a third party, or via automation, particularly in the future.   

  Money  management  –  information  facilitates  greater  control  over  energy 
spending,  enables  consumers  to  check  if  bills  are  accurate  and  budget  more 
easily.  In  turn  this  helps  to  build  trust  in  companies.  Control  is  also  a  key 
component of affordability. 

  Improving  purchasing  decisions  –  with  the  right  information  in  the  right 
format,  customers  can  be  incentivized  to  make  purchasing  decisions  and  are 
better informed when they do. E.g. they can more easily identify the best energy 
deal for them, or calculate if an energy efficiency product will give them benefits 
and its payback time.  

Balancing prescription with more outcomes based approaches 

There  is  an  important  role  for  prescription  in  regulation  in  this  area  but  care  must  be 
taken as to how and when it is applied. Current rules have led to unintended outcomes 
for consumers e.g. longer more complex bills.  

It is recognized that information alone, while a prerequisite, is  rarely  enough to deliver 
behavior  change  and  outcomes  outlined  above.  The  evidence  base  in  terms  of  what 
‘works best’, particularly around feedback mechanisms, such as in home displays versus 
mobile phone apps etc. is still largely inconclusive, particularly in the case of gas. A one-
sized  fits  all  approach  to  providing  information  is  however  recognized  as  not  the  best 
approach  to  deliver  the  impact  needed.    Evidence  indicates  that  some  consumers  in 
more  vulnerable  situations  also  need  additional  support  or  tailored  approaches.  
For all these reasons it is important for much of the regulation in this space to allow for 
innovation.    Focusing  on  what  Member  States  must  deliver  by  way  of  consumer 
outcomes (that is ensuring access to information to enable switching, energy reduction, 
purchasing decisions) rather than how they must do (put predefined information on bills) 
allows  for  flexibility  to  respond  to  market  circumstances,  as  well  as  a  better  degree  of 
future proofing. However, in order for this to work there must be appropriate monitoring 
and reporting of the impacts/outcomes. 

Prescription  is  best  applied  where  there  is  evidence  that  the  current  market  and  wider 
structures  have  historically  failed  to,  and/or  are  therefore  unlikely  to  deliver  the 
necessary  consumer  outcomes  e.g.  there  is  evidence  base  of  problems,  or  there  are 
insufficient  commercial  incentives  for  the  market  players  to  take  action.    Also,  where  a 
standardized  approach  is  necessary  to  ensure  interoperability.  This  is  especially 
important in a smart world with the likely growth in bundling of services across energy, 
telecommunications,  transport  and  other  sectors.  We  therefore  make  the  following 
recommendations.   

Recommendations: 

1.  Establish  an  inclusivity  principle  –  a  significant  number  of  consumers  face 
barriers when accessing information due to their personal characteristics or their 
circumstances. E.g. if they don’t use or have internet access they will need hard 
copy information; customers with dexterity problems can find it hard to use touch 
screen  energy  displays;  those  who  are  blind  or  partially  sighted  need  tailored 
communications  etc.  Companies  should  take  all  reasonable  steps  to  ensure  that 
services are inclusively designed and that they meet the needs of all consumers. 
There are already: precedents for this in some Member States; a sound business 
case  for  inclusive  approaches;  and  good  practice  standards  to  facilitate 

56 

 
 
 
 
compliance. 

2.  Further  improve access to the granularity  of time of  use of consumption 
data  –  this  is  critical  for  customers  to  make  informed  switching  decisions  in 
particular. 

i)  Companies  should  make  energy  consumption  information  available  in 
sufficient  detail  that  allows  customers  or  their  representatives  to  identify  the 
best  offers  for  them.  This  doesn’t  currently  happen.  e.g.  in  GB  how  much 
energy  a  customer  needs  to  use  off-peak  to  benefit  from  a  time  of  use  deal 
varies  from  9%-55%  depending  on  the  tariff.  Customers  need  to  know  how 
much energy they consume each hour to calculate if they are better or worse 
off  on  different  deals.  They  don’t  have  the  information  to  do  this.  This  is 
particularly  important  to  establish  given  the  likely  growth  in  demand  side 
response and ‘smart tariffs’. 

ii)  There  should  be  a  fairness  principle  that  whatever  granularity  of  data 
companies  ‘take’  should  be  easily  available  to  consumers  for  free.  E.g.  if 
companies are accessing half hourly data, this should also be available to the 
free.  
customer 

for 

3.  Require  greater  standardization  of  data  to  allow  for  timely  data 
portability – e.g. in terms of terminology, format. This is to enable data sharing 
with third parties who can help deliver the outcomes outlined, or for the customer 
to  use  with  tools  such  as  automation.  Combining  data  sets  can  also  bring 
additional  value.  The  slowness  with  which  suppliers  have  participated  in  the  GB 
Midata project indicates that there are often insufficient commercial incentives for 
companies  to  give  appropriate  access  to  data.  Indeed  generally  companies  are 
reluctant to share this ‘black gold’. 

4.  Explore  requiring  access  to  new  kinds  of  smart  metering  data - e.g. the 
data  that  prosumers  need,  and  the  availability  of  data  about  quality  of  supply, 
such  as  about  outages,  and  voltage  quality.  This  could  help  customers  seek 
compensation  and  drive  improvements  in  service.  There  is  little  incentive  on 
companies to provide this, especially when they are liable if service is found to be 
substandard.  

5.  Introduce  new  regulation  on  billing  accuracy  –  billing  problems  are  the 
largest  source  of  consumer  complaints  in  GB.    Smart  metering  is  expected  to 
significantly  improve  billing  accuracy  but  it  will  not  resolve  all  problems.  
Customers  have  a  low  tolerance  for  estimated  bills,  particularly  with  smart 
meters,  and  accurate  bills  are  a  top  priority.    A  particular  problem  is  back-bills 
when customers are sent a catch-up bill for monies outstanding, due to a supplier 
error – these can run into the hundreds and thousands of pounds.  Back-bills can 
cause  considerable  detriment,  pushing  customers  into  debt  and  onto  more 
expensive  payment  methods.  Regulation  is  necessary  to  ensure  the  liability  for 
billing problems does not rest with the consumer and to improve billing accuracy. 
There  are  precedents  for  this  in  a  number  of  countries.  This  is  key  to  building 
consumer trust and engagement.  

I.9 The Utilities point of view - Sébastien Dolige, Eurelectric 

57 

 
 
 
 
 
 
 
 
 
In a competitive market, bill design should be left to retailers to diversify their brand and 
image, and meet their customers’ needs. This is one of main recommendations of the EC 
WG report on E-billing to the London Forum (2013) 

In most EU countries suppliers are in constant dialogue with consumers (e.g. consumer 
panels)  and  energy  companies  are  taking  steps  to  make  energy  bills  clearer  and  offers 
easier to compare, such as by reducing their number and simplifying their structure. See 
for instance a recent initiative by SSE: 

http://sse.com/newsandviews/allarticles/2016/02/new-sse-bill-design-aims-to-end-energy-bill-confusion/ 

As constantly advocated by EURELECTRIC, improved transparency in price and offers is 
also linked to better - which sometimes  mean less - regulation. In several EU member 
states, bills are heavily regulated and, whilst many consumers complain that there is too 
much  information  on  their  bills,  making  them  difficult  to  read,  suppliers  are  not  always 
allowed  to  simplify  them.  In  France  for  instance,  more  than  70%  of  the  bill  is  fully 
regulated. 

In  our  view  before  coming  up  with  more  regulation,  policy-makers  should  assess  the 
impact  of  current  national  legislative  provisions  and  requirements  regulating  the 
presentation  of  offers  and  bills.  We  think  there  would  be  merit  in  encouraging  more 
evidence and principle-based regulation rather than dictating how things should be done. 

Policy makers should also consider that many other options exist to provide information 
to consumers. New communication technologies - display devices or individual feedback 
services  on  the  internet  or  telephone  -  are  changing  the  way  suppliers  and  ESCOs 
communicate  with  their  customers  and  will  play  a  greater  role  in  monitoring  or 
optimising customers’ energy consumption. 

Smart  meters  with  appropriate  functionalities  and  the  availability  of  real-time  metering 
data  are  of  utmost  importance  to  provide  innovative  services  to  customers.  SM  are 
sometimes  taken  for  granted  but  they  are  not  there  yet  in  most  Member  States.  The 
Commission should therefore keep a watching brief on member states’ roll-out plans and 
smart meters functionalities.  

Finally  as  shown  by  EURELECTRIC’s  recently  published  infographics  ‘Making  sense  of 
your  electricity  bill’,  the  average  EU  household  electricity  bill  in  2014  was  made  up  of 
37%  of  energy  and  supply  costs,  26%  of  network  costs  and  36%  of  taxes  and  policy 
costs.  What  is  particularly  disconcerting is  that  as  from  2014  European  households  pay 
as much for electricity as for taxes and policy costs. As the power sector makes strides 
towards  sustainability  and  electricity  becomes  decarbonised,  its  role  as  Europe’s  fuel  of 
choice is jeopardised because  of the burden put by governments  on its final price.  It is 
all  the  more  urgent  that  European  policymakers  rethink  how  costs  are  levied  on 
everyone’s  bill  if  Europe  is  to  reach  decarbonisation  at  the  lowest  possible  cost  to  all 
consumers 

I.10 State of play on implementation of Article 10 in Finland, Leino Sirpa 

Smart Meter roll-out in Finland 

•  Electricity - Legal framework 

–  Almost 100 % coverage of smart metering 

•  District heating -  Commercial basis 

–  80 % of meters register hourly data,  
–  90 % are remotely read 

Metering Legal Framework - Requirements for metering (electricity): 

  remote reading daily 

58 

 
 
 
 
 
 
 
 shall register over 3 minute black-out time
 remote demand response feature (1 relay)
 data storage in DSO systems
 security of data (meters and systems)

•
•

Customers have access to their hourly measurements via online service by DSO
Standard  open  interface  at  the  meter  for  real  time  consumption  data  has  to  be
provided on customer request

Several benefits to the market actors and the whole energy system: 

•

Customer

– Customers  have  been  switched  from  billing  based  on  estimated  to  billing

•
•

based on actual consumption. Experiences:
Bills are easier to understand.
The  questions  have  before  been  about  not  understanding  the  bill,
now they are about how the customer could save energy.
Some  customers  have  started  to  use  energy  more  efficiently.  This
information  about
time 
is  also  because  of  real 
consumption to the customers

feedback 

•

– Wide variety services how to deliver hourly data to the customers via on-
line  systems  (web,  smart  phone,  tablet)  and  helping  customers  better
understand their energy consumption

•

Energy system benefits

–

–

Possibility to involve also small customers in to demand response and thus
the ability to integrate volatile renewables
Electricity  market  functions  close  to  real  time  –  from  big  production  to
small customers

•

Supplier benefits

–

Possibility  for  variety  of  new  pricing  methods  and  other  new  business
possibilities

– Billing based on actual consumption improves business planning and cash

management (increased predictability)

•

Third parties / ESCOs

– New innovative business possibilities

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doi:10.2790/565532 
ISBN: 978-92-79-59778-7