Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Energy Efficiency
Published in: Energy Efficiency 4/2016

01-08-2016 | Original Article

Evidence of an indirect rebound effect with reversible heat pumps: having air conditioning but not using it?

Authors: Maxime Raynaud, Dominique Osso, Bernard Bourges, Bruno Duplessis, Jérôme Adnot

Published in: Energy Efficiency | Issue 4/2016

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Regional energy efficiency programmes are of particular interest as they tackle local constraints which are not always targeted by national energy policy. Within this framework, an energy efficiency programme for existing dwellings has been implemented in a southern European region, providing financial incentives for a combination of energy efficiency actions (heat pump combined with insulation and/or solar water heater). Ex-post evaluation results of this pilot programme are reported in this study. More than 200 households were surveyed regarding their individual energy consumption as well as house and household characteristics. Likewise, the survey highlights household behaviours concerning both space heating and air conditioning, before and after refurbishment. A 3-year billing analysis is used to calculate the energy savings attributed to the operation. Evaluations are carried out taking into account critical parameters like climate differences between years or direct (enhanced space heating comfort) and indirect (use of air conditioning) rebound effects via a statistical model. Moreover, an uncertainty assessment of energy savings was realized on the basis of three scenarios (low, median and high). This study is particularly focused on the use of air conditioning by households, data rarely found in the literature, whereas the consumption linked to air conditioning should increase in the residential sector especially in southern regions. These results help in answering questions about the installation of heat pumps in existing single-family houses with respect to energy savings as well as direct and indirect rebound effects.
previous article What did we recently learn about the evaluation of energy efficiency policies and programmes? Insights from IEPPEC 2014 in Berlin
next article Guided group purchases of energy renovation services and works in deprived urban neighbourhoods

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now
Appendix
Available only for authorised users
Footnotes
1
For example, in the city of Aix en Provence (Bouches du Rhône), from 1981 to 2010 (Météo Climat 2011), the average temperatures in July and August were respectively 22.9 and 22.5 °C. The average daily minima and maxima temperatures were 15.1 and 30.6 °C in July and 14.9 and 30.1 °C in August.
 
2
We should note that the authors do not discuss the third level of the rebound effect called “wide economy” that is beyond the scope of this paper (See Guerra and Sancho 2010).
 
3
In our case, air conditioning is considered as a new energy service provided by the reversible heat pump.
 
4
Minimum efficiency: COP 7/20 ≥3.3 (recommended COP 7/20 ≥3.6) and EER 35/27 >2.8.
 
5
Minimum efficiency with radiators: COP 7/35 ≥3.3 (recommended COP 7/35 ≥3.5).
 
6
The surface area heated had to be at least 60 % of the net floor area or a minimum of 80 m2.
 
7
Minimum level of thermal resistance added: R ≥ 5 m2.K/W
 
8
With the aim of obtaining one complete year of energy bills for before (2009) and after (2011) the refurbishment.
 
9
On 851 households who had been phoned, amongst 916 participants matching with our selection criteria. No incentive was given; thus, only volunteers answered the survey (answer rate of about 25 %).
 
10
19 % of the sample is initially with fossil fuel as main heating source and the remaining 6 % used mainly wood before.
 
11
Gas, 0.9 kWhLCV/kWhHCV (higher calorific value); domestic oil, 10 kWhLCV/l; LPG, 12,720 kWhLCV/tonne; wood logs, 1710 kWhLCV/stere; wood pellets, 4700 kWhLCV/tonne.
 
12
Base 18 °C.
 
13
Département 06, 1372 °C.day; Département 13, 1627 °C.day; Département 83, 1309 °C.day (COSTIC 2014).
 
14
The standard uncertainty of a quantity is defined as the estimated standard deviation associated to an estimation of its value (JCGM/WG1 2008).
 
15
“Because there was no specific knowledge about the possible values of X i within its estimated bounds a − to a +, one could only assume that it was equally probable for X i to take any value within those bounds, with zero probability of being outside them. Such step function discontinuities in a probability distribution are often unphysical. In many cases, it is more realistic to expect that values near the bounds are less likely than those near the midpoint. It is then reasonable to replace the symmetric rectangular distribution with a symmetric trapezoidal distribution having equal sloping sides.” (JCGM/WG1 2008).
 
16
For the case where all of the input estimates x i are non-correlated, “the combined standard uncertainty u c (y) is thus simply a linear sum of terms representing the variation of the output estimate y generated by the standard uncertainty of each input estimate x i , i.e., u(x i )” (JCGM/WG1 2008). For the case where some input estimates x i are correlated, a covariance term is added.
 
17
Within the context of this study, we can assume firstly that the probability distribution characterizing ES i follows a normal distribution because of the central limit theorem (JCGM/WG1 2008) and secondly that u c (ES i ) is a reasonably reliable estimate of the standard deviation of the normal law.
 
18
Six cases having installed an air-to-air heat pump and realized two other energy efficiency actions, two cases having installed a water-to-water heat pump and one case having installed an air conditioning system out of the operation.
 
19
90 % of the sample did not have or did not use air conditioning before retrofitting.
 
20
Cumulated duration: 1 week or less.
 
21
Due to too low separately representativeness (respectively less than 17 % and less than 14 % of the sample), this category regroups two cumulated duration categories: 2 to 3 weeks (regularly) and 1 month and more (very often).
 
22
Each of these two categories represents 50 % of the sample.
 
23
P value = 0.95 so the null hypothesis of the Jarque-Bera’s test cannot be rejected (P value >0.05): “The sample follows a normal distribution.”.
 
24
See the section “Survey and sample”, for remembering that the surveyed dwellings are mainly single-family houses initially equipped with direct electric heating.
 
25
Coefficient of determination (R 2) takes into account the number of explanatory variables used by the model.
 
26
Root mean square error (RMSE) is an unbiased estimate of the standard deviation of model error.
 
27
According to the French Energy Performance Certificate calculation (based on a standardized and simplified energy modelling of the buildings) (Arrêté 17 octobre 2012), default coefficient of performance for AAHP = 2.2 and for AWHP = 2.6.
 
28
A model with a variable “declared use of air conditioning after retrofitting” defined by only the three categories of declared time of use during summer (no use, low use and important use) obtains similar results that the presented model: adjusted R 2 = 0.38, RMSE = 36.3 kWh/m2, category “low use” non-significant and category “important use” significant (value = 39.5 kWh/m2, confidence interval at level 95 % = [21.9; 57.1], P value <0.0001).
 
29
From 1981 to 2010 (Météo Climat 2011), the average temperature in July (the hottest in Denmark) was 18.2 °C for Copenhagen (Denmark) whereas for Aix en Provence (Bouches du Rhône), it was 22.9 °C. On the same month, the average daily minima and maxima temperatures were respectively 14.2 and 22.0 °C for Copenhagen and 15.1 and 30.6 °C for Aix en Provence.
 
30
44 % = 0.75 * 24 % + 0.84 * 31 %
 
31
Cumulated duration in summer: 2 weeks to 1 month and more.
 
Literature
Arrêté 17 octobre. (2012). Arrêté du 17 octobre 2012 modifiant la méthode de calcul 3CL-DPE introduite par l'arrêté du 9 novembre 2006 portant approbation de diverses méthodes de calcul pour le diagnostic de performance énergétique en France métropolitaine. Journal officiel de la République française, 0262.
Aste, N., Buzzetti, M., Caputo, P., & Manfren, M. (2014). Local energy efficiency programs: a monitoring methodology for heating systems. Sustainable Cities and Society, 13, 69–77.CrossRef
Berkhout, P. H. G., Muskens, J. C., & Velthuijsen, J. W. (2000). Defining the rebound effect. Energy Policy, 28, 425–432.CrossRef
Blackhurst, M., Azevedo, I. L., Matthews, H. S., & Hendrickson, C. T. (2011). Designing building energy efficiency programs for greenhouse gas reductions. Energy Policy, 39, 5269–5279.CrossRef
Boßmann, T., Eichhammer, W., & Elsland, R. (2012). Concrete paths of the European Union to the 2°C scenario: achieving the climate protection targets of the EU by 2050 through structural change, energy savings and energy efficiency technologies. Project Number: 405/2010, FKZ: UM 10 41 913. Fraunhofer Institute for Systems and Innovation Research ISI.
Broc, J.-S. (2006). L'evaluation ex-post des opérations locales de maitrise de la demande en énergie. Etat de l'art, méthodes bottom-up, exemples appliqués et approche du développement d'une culture pratique de l'évaluation. PhD Thesis. MINES ParisTech.
CEREN. (2009). Consommation moyenne d'énergie régionale par usage. Exploitation particulière de l'Enquête Logement 2006. Etude 8107.
CEREN. (2013). Secteur Résidentiel – Bilan avancé des consommations d’énergie de 2012. Etude 2103.
Chakravarty, D., Dasgupta, S., & Roy, J. (2013). Rebound effect: how much to worry? Current Opinion in Environmental Sustainability, 5, 216–228.CrossRef
Chitnis, M., Sorrell, S., Druckman, A., Firth, S. K., & Jackson, T. (2014). Who rebounds most? Estimating direct and indirect rebound effects for different UK socioeconomic groups. Ecological Economics, 106, 12–32.CrossRef
Day, A. R. (1999). An investigation into the estimation and weather normalisation of energy consumption in buildings using degree-days. PhD Thesis. South Bank University.
Ehrhardt-Martinez, K., & John, A. (2010). Rebound, technology and people: mitigating the rebound effect with energy-resource management and people-centered initiatives. 2010 ACEEE Summer Study on Energy Efficiency in Buildings, 7–76. Pacific Grove, United States.
Galvin, R. (2014). Making the ‘rebound effect’ more useful for performance evaluation of thermal retrofits of existing homes: defining the ‘energy savings deficit’ and the ‘energy performance gap’. Energy and Buildings, 69, 515–524.CrossRef
Gram-Hanssen, K., Christensen, T. H., & Petersen, P. E. (2012). Air-to-air heat pumps in real-life use: are potential savings achieved or are they transformed into increased comfort? Energy and Buildings, 53, 64–73.CrossRef
Greening, L., Greene, D. L., & Difiglio, C. (2000). Energy efficiency and consumption—the rebound effect—a survey. Energy Policy, 28, 389–401.CrossRef
Guerra, A.-I., & Sancho, F. (2010). Rethinking economy-wide rebound measures: an unbiased proposal. Energy Policy, 38, 6684–6694.CrossRef
Haas, R., & Biermayr, R. (2000). The rebound effect for space heating: empirical evidence from Austria. Energy Policy, 28, 403–410.CrossRef
Hengstenberg, J. (2014). Evaluating savings from boiler replacement. Berlin: International Energy Program Evaluation Conference- IEPPEC.
Hong, S. H., Oreszczyn, T., Ridley, I., & The Warm Front Study Group. (2006). The impact of energy efficient refurbishment on the space heating fuel consumption in English dwellings. Energy and Buildings, 38, 1171–1181.CrossRef
Laurent, M.-H., Allibe, B., Oreszczyn, T., Hamilton, I., Tigchelaar, C., & Galvin, R. (2013). Back to reality: how domestic energy efficiency policies in four European countries can be improved by using empirical data instead of normative calculation. France: ECEEE Summer Study. Presqu'île de Gien.
Nauleau, M.L. (2014). Free-riding on tax credits for home insulation in France: an econometric assessment using panel data. Berlin: International Energy Program Evaluation Conference - IEPPEC.
Raynaud, M., Osso, D., Adnot, J., Bourges, B., & Duplessis, B. (2012). An energy efficiency program analysis to understand the gaps between ex-ante and ex-post evaluations. Rome: International Energy Program Evaluation Conference - IEPEC.
Raynaud, M. (2014). Evaluation ex-post de l’efficacité de solutions de rénovation énergétique en résidentiel. PhD Thesis. MINES ParisTech.
Rosenow, J., & Galvin, R. (2013). Evaluating the evaluations: evidence from energy efficiency programmes in Germany and the UK. Energy and Buildings, 62, 450–458.CrossRef
Saunders, H. (2013). Is what we think of as “rebound” really just income effects in disguise? Energy Policy, 57, 308–317.MathSciNetCrossRef
Scheer, J., Clancy, M., & Ní Hógáin, S. (2013). Quantification of energy savings from Ireland’s Home Energy Saving scheme: an ex post billing analysis. Energy Efficiency, 6, 35–48.CrossRef
Sorrell, S. (2007). The rebound effect: an assessment of evidence for economy-wide energy savings form improved energy efficiency. Technology and Policy Assessment function, UK Energy Research Centre. ISBN 1-903144-0-35.
Sorrell, S., & Dimitropoulos, J. (2008). The rebound effect: microeconomic definitions, limitations and extensions. Ecological Economics, 65, 636–649.CrossRef
Sorrell, S. (2009). The evidence for direct rebound effects. In Energy efficiency and sustainable consumption: the rebound effect. Horace Herring and Steve Sorrell (eds.). New York, NY: Palgrave Macmillan (St. Martin’s Press).
Sorrell, S., Dimitropoulos, J., & Sommerville, M. (2009). Empirical estimates of the direct rebound effect: a review. Energy Policy, 37, 1356–1371.CrossRef
Stern, F., & Vantzis, D. (2014). Protocols for evaluating energy efficiency—both sides of the Atlantic. Berlin: International Energy Program Evaluation Conference - IEPPEC.
Suerkemper, F., Thomas, S., Osso, D., & Baudry, P. (2012). Cost-effectiveness of energy efficiency programmes—evaluating the impacts of a regional programme in France. Energy Efficiency, 5, 121–135.CrossRef
Sunikka-Blank, M., & Galvin, R. (2012). Introducing the prebound effect: the gap between performance and actual energy consumption. Building Research and Information, 40, 260–273.CrossRef
TecMarket, et al. (2004). The California Evaluation Framework. Last Revision: January 2006. Project number: K2033910.
Thomas, B. A., & Azevedo, I. L. (2013). Estimating direct and indirect rebound effects for U.S. households with input–output analysis part 1: theoretical framework. Ecological Economics, 86, 199–210.CrossRef
Valentová, M., & Bertoldi, P. (2011). Evaluation of the green building programme. Energy and Buildings, 43, 1875–1883.CrossRef
Vine, E., Hall, N., Keating, K. M., Kushler, M., & Prahl, R. (2013). Emerging evaluation issues: persistence, behavior, rebound, and policy. Energy Efficiency, 6, 329–339.CrossRef
Violette, D. M., & Vantzis, D. (2014). Building confidence in meeting energy efficiency targets—addressing free riders and additionality. Berlin: International Energy Program Evaluation Conference - IEPPEC.
JCGM/WG1 (Working Group 1 of the Joint Committee for Guides in Metrology). (2008). Evaluation of measurement data—guide to the expression of uncertainty in measurement. Guide JCGM 100: 2008 (E).
Yu, B., Zhang, J., & Fujiwara, A. (2013). Evaluating the direct and indirect rebound effects in household energy consumption behavior: a case study of Beijing. Energy Policy, 57, 441–453.CrossRef
Metadata
Title
Evidence of an indirect rebound effect with reversible heat pumps: having air conditioning but not using it?
Authors
Maxime Raynaud
Dominique Osso
Bernard Bourges
Bruno Duplessis
Jérôme Adnot
Publication date
01-08-2016
Publisher
Springer Netherlands
Published in
Energy Efficiency / Issue 4/2016
Print ISSN: 1570-646X
Electronic ISSN: 1570-6478
DOI
https://doi.org/10.1007/s12053-015-9419-2

Other articles of this Issue 4/2016

Energy Efficiency 4/2016 Go to the issue

Original Article

The impact of applying different metrics in target definitions: lessons for policy design

Original Paper

The price effect of building energy ratings in the Dublin residential market

Original Article

Guided group purchases of energy renovation services and works in deprived urban neighbourhoods

Original Article

Behavioral energy feedback program evaluations: a survey of current knowledge and a call to action

Original Article

Evaluating a behavioral demand response trial in Japan: evidence from the summer of 2013

Original Article

Northwest ductless heat pump Pilot Project—a holistic approach to market transformation and evaluation