Stock modelling and cost-effectiveness analysis of energy-efficient household electronic appliances in Switzerland

Abstract

Worldwide, household electronic appliances represent a very dynamic market segment, accounting for a significant share of household energy demand. In Switzerland, household electronic appliances consumed 5.3 PJ (1.5 TWh) or 8.2% of the residential sector’s electricity demand. According to historical trends, improved energy efficiency has been counteracting increased size, enhanced functionality and growing numbers of consumer electronics. A stock model is developed to describe the evolution of the appliances in use and the corresponding energy use. Apart from analysing past trends, we develop scenarios for the future based on simplified assumptions for energy efficiency improvement and penetration rates. We find that the competing aforementioned trends may keep the total energy demand of this product category at today’s level until 2035. Our energy efficiency cost curves show that the current energy saving potential is close to 1 PJ or 18% but that the related measures are not cost-effective when taking today’s perspective of a consumer who is faced with the choice among energy-efficient products currently offered on the market. Based on our findings for today’s commercially available portfolio of products, it therefore currently does not seem reasonable to recommend proactive, consumer-oriented policies for household electronic appliances (such as rebates). Instead, the findings indicate that producer-oriented policy measures should be pursued, ensuring continuous R&D and implementation of energy efficiency technologies including standby loss minimization related to connected appliances and wireless charging.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21

Notes

  1. 1.

    Prognos’ study “Energy perspectives for Switzerland until 2050” (original title in German: Die Energieperspektiven für die Schweiz bis 2050 (Cooper 2004)), commissioned by the Swiss Federal Office for Energy (SFOE) and published in 2013, served as basis for the Swiss “Energy Strategy 2050”. It is a very detailed study depicting the energy transition in Switzerland until 2050. However, the modelling approach and data inputs are not published in detail.

  2. 2.

    For advanced approach, we assume that the appliances that are replaced during early replacement have reached half of their lifetime.

References

  1. Amann J., Sachs H., &' Kwatra S. (2013). Miscellaneous energy loads in buildings. Washington, DC: ACEEE.

  2. Azevedo, I. L., Morgan, M. G., Palmer, K., & Lave, L. B. (2013). Reducing U.S. residential energy use and CO2 emissions: How much, how soon, and at what cost? Environmental Science & Technology, 47(6), 2502–2511.

  3. Battig, R., & Ziegler, M. (2009). Swiss greenhouse gas abatement cost curve. http://www.mckinsey.com/~/media/mckinsey/dotcom/client_service/sustainability/costcurvepdfs/ghg_cost_curve_report_final.ashx.

  4. Blok, K., & Nieuwlaar, E. (2016). Introduction to energy analysis (2nd ed.). London: Routledge.

  5. Chiffres des ventes dans l’électronique grand public en Suisse. [Online]. 2016. http://www.swico.ch/fr/prestations/etudes-de-marche/.

  6. Cho, H., Freyre, A., Bürer, M., & Patel, M. K. (2019). Comparative analysis of customer-funded energy efficiency programs in the United States and Switzerland–Cost-effectiveness and discussion of operational practices. Energy Policy, 135. https://doi.org/10.1016/j.enpol.2019.111010.

  7. “Code of conduct on energy efficiency of digital TV service systems - Version 9,” 2013. https://e3p.jrc.ec.europa.eu/sites/default/files/documents/publications/code_of_conduct_digital_tv_service_systems_v9_final.pdf

  8. Coleman, M., Brown, N., Wright, A., & Firth, S. K. (2012). Information, communication and entertainment appliance use—Insights from a UK household study. Energy and Buildings, 54, 61–72.

    Article  Google Scholar 

  9. “ Commission Delegated Regulation (EU) No 1062/2010 of 28.9.2010 supplementing Directive 2010/30/EU of the European Parliament and of the Council with regard to energy labelling of televisions,” 2010.

  10. “Connected devices alliance technical report on progress with international initiatives on networked devices,” IEA, 2015. https://www.iea-4e.org/document/377/cda-technical-report-on-progress-withinternational-initiatives-on-networked-devices

  11. Cooper, T. (2004). Inadequate life? Evidence of consumer attitudes to product obsolescence. Journal of Consumer Policy, 27(4), 421–449.

    Article  Google Scholar 

  12. “Criteria paper for simple set-top boxes,” 2009. https://storage.topten.eu/source/files/D5_Criteria%20paper_Simple_Settop_boxes_.pdf

  13. Dasgupta, R. (2014). Characterization theorems for Weibull distribution with applications. Journal of Environmental Statistics, 6(4), 1–25.

    Google Scholar 

  14. Ellis, M., Jollands, N., Harrington, L., & Meier, A. (2007). Do energy efficient appliances cost more? In ECEEE 2007 summer study. Washington, DC: Residential Energy Consumption Survey.

  15. “Energy Saving Trust (EST). The rise of the machines. A review of energy using products in the home from the 1970s to today,” 2006.

  16. Energy Saving Trust (EST) (2007). The ampere strikes back – How consumer electronics are taking over the world. Report by EST. London: Energy Saving Trust.

  17. EU ENERGY STAR imaging equipment specifications v2.0. [Online] (2014). https://www.euenergystar.org/downloads/specifications/Imaging%20Equipment%20v2.0%20%20CELEX_32014D0202_EN_TXT.pdf

  18. EU ENERGY STAR computers specifications v6.1. [Online]. (2015a). https://www.eu-energystar.org/downloads/specifications/Computers%20v6.1%20-%20CELEX_32015D1402_EN_TXT.pdf

  19. EU ENERGY STAR displays specifications v7.0. [Online]. (2016). https://www.eu-energystar.org/downloads/specifications/Displays%20v6.0%20-%20CELEX_32014D0202_EN_TXT.pdf

  20. EU ENERGY STAR Database ® for Computers, qualified under Computers specification 6.1 2018a.

  21. EU ENERGY STAR Database ® for Displays, qualified under Displays specification 7.0 2018b.

  22. EU ENERGY STAR Database ® for Imaging equipment, qualified under Imaging equipment specification 2.0 2018c.

  23. Fares, R., Sofos, M., Langevin, J., Hosbach, R., Meier, A., Butzbaugh, J. B., et al. (2018). Improving characterization of miscellaneous energy loads in energy demand models. In ACEEE Summer Study on Energy Efficiency in Buildings, Pacific Grove, CA. Washington, DC: American Council for an Energy Efficient Economy.

  24. Fawcett, T., Lane, K., & Boardman, B. (2000). Lower carbon futures for European households. Tech. Rep. Oxford: University of Oxford, Environmental Change Institute.

  25. Gerber, D., Meier, A., Hosbach, R., & Liou, R. (2018). Zero standby solutions with optical energy harvesting from a laser pointer. Electronics, 7(11).

  26. Gerke, B. F., McNeil, M. A., & Tu, T. (2017). The International database of efficient appliances (IDEA): A new tool to support appliance energy-efficiency deployment. Applied Energy, 205, 453–464.

    Article  Google Scholar 

  27. Guan, L., Berrill, T., & Brown, R. J. (2011). Measurement of standby power for selected electrical appliances in Australia. Energy and Buildings, 485–490.

  28. Haan, P., Kissling, I., & Wolfensberger, M. (2012). Effizienz und Elektrifizierung Haushalte, Schlussbericht zuhanden VSE – Verband Schweizerischer Elektrizitätsunternehmen. Zollikon: Ernst Basler + Partner AG.

  29. Harrington, L., Norman, B., “Beyond network standby - Policy framework,” IEA, 2014.https://standby.iea-4e.org/files/otherfiles/0000/0104/Network_Standby_Report_Final.pdf

  30. Heidari, M., Majcen, D., van der Lans, N., Floret, I., & Patel, M. K. (2017). Analysis of the energy efficiency potential of household lighting in Switzerland using a stock model. Energy and Buildings, 158, 536–548.

    Article  Google Scholar 

  31. http://topten.ch/ 2019b.

  32. “IEA: More data, less energy - Making network standby more efficient in Bbllions of connected devices ,” 2014. https://webstore.iea.org/login?ReturnUrl=%2fdownload%2fdirect%2f426

  33. IEA – International Energy Agency. (2009). Gadgets and gigawatts. Policies for energy efficient electronics. Paris, France: International Energy Agency.

    Google Scholar 

  34. “IEA Benchmarking of the standby power performance of domestic appliances,” 2012. https://www.iea-4e.org/document/314/international-benchmarking-report-onstandby-power

  35. “IEA mapping report - Notebook computers - Switzerland - IEA 4E,” 2012. https://mappingandbenchmarking.iea-4e.org/shared_files/468/download

  36. “IEA mapping report - Set-top boxes - EU ,” 2014. https://mappingandbenchmarking.iea-4e.org/shared_files/550/download

  37. “IEA mapping report - televisions - Switzerland - IEA 4E,” 2010. https://www.iea-4e.org/document/268/mapping-report-televisions-switzerland

  38. IEA World Energy Balances 2018(2016) Switzerland Energy Strategy 2050. [Online]. https://www.uvek.admin.ch/uvek/en/home/energie/energy-strategy-2050.html

  39. “IEA World Energy Balances 2018,” Paris, 2018a.

  40. IEA World Energy Balances 2018 (2018b) ODYSSEE database on energy efficiency data and indicators. [Online]. http://www.indicators.odyssee-mure.eu/energy-efficiency-database.html

  41. IEA World Energy Outlook 2017 (2009) DIRECTIVE 2009/125/EC OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL, establishing a framework for the setting of ecodesign requirements for energy-related products. [Online]. https://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2009:285:0010:0035:en:PDF

  42. “IEA World Energy Outlook 2017,” Paris, 2017a.

  43. IEA World Energy Outlook 2017 (2017b) REGULATION (EU) 2017/1369 OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL setting a framework for energy labelling and repealing Directive 2010/30/EU. [Online]. https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32017R1369&from=EN

  44. IEA World Energy Outlook 2017 (2018) Energy Labelling legislation, Regulation (EU) 2017/1369 setting a framework for energy labelling and repealing Directive. [Online]. https://ec.europa.eu/energy/sites/ener/files/documents/list_of_enegy_labelling_measures.pdf

  45. “IEA World Energy Outlook 2018,” Paris, 2018.

  46. “Impact assessment accompanying the communication from the European Commission: A policy framework for climate and energy in the period from 2020 to 2030,” Brussels, 2014. https://ec.europa.eu/smartregulation/impact/ia_carried_out/docs/ia_2014/swd_2014_0015_en.pdf

  47. “Information technology/office equipment market Switzerland total market and estimation,” Gfk, 2018. https://www.gfk.com/fileadmin/user_upload/country_one_pager/CH/

  48. Kelly, G. (2012). Sustainability at home: policy measures for energy-efficient appliances. Renewable and Sustainable Energy Reviews, 19 (9), 6851–6860.

  49. Kemmler, A., Piegsa, A., Wuthrich, P., & Keller M. (2016). Analyse des schweizerischen Energieverbrauchs 2000–2015 nach Verwendungszwecken. Bern: Bundesamt für Energie (BFE).

  50. Kirchner, A. (2012). Die Energieperspektiven für die Schweiz bis 2050. Basel: Prognos AG.

  51. Kleijn, R., Huele, R., & van der Voet, E. (2000). Dynamic substance flow analysis: the delaying mechanism of stocks, with the case of PVC in Sweden. Ecological Economics, 32(2), 241–254.

    Article  Google Scholar 

  52. Koomey, J. G., Atkinson, C., Meier, A., McMahon, J., & Boghosian, S. (1991). The potential for electricity efficiency improvements in the U.S. residential sector. Tech. Rep. Berkeley: Lawrence Berkeley National Laboratory.

  53. Liu, X., Tanaka, M., & Matsui, Y. (2006). Electrical and electronic waste management in China: progress and the barriers to overcome. Waste Management and Research, 24(1), 92–101.

    Article  Google Scholar 

  54. McKinsey. (2007). Reducing U.S. greenhouse gas emissions: How much at what cost? New York: McKinsey & Company and the Conference Board.

    Google Scholar 

  55. McNeil, M. A., & Bojda, N. (2012). Cost-effectiveness of high-efficiency appliances in the U.S. residential sector: A case study. Energy Policy, 45, 33–42.

    Article  Google Scholar 

  56. Meier, A. K. (2019). New standby power targets. Energy Efficiency, 12(1), 175–186.

    Article  Google Scholar 

  57. Meier, A., Rosenfeld, A. H., & Wright, J. (1982). Supply curves of conserved energy for California’s residential sector. Energy, 7(4), 347–358.

    Article  Google Scholar 

  58. "Measurement of the power consumption of set-top boxes,”, Energieshweiz, 2007. http://www.salt-chur.ch/files/Schlussbericht-Settop-Boxen-V14_EN2-total.pdf

  59. Mohd, A. (2010). Motor systems efficiency supply curves. Technical Report. Vienna: United Nations Industrial Development Organization (UNIDO).

  60. Mont, O., & Power, K. (2009). Understanding factors that shape consumption. Copenhagen: ETC/SCP Working Paper No 1/2013.

    Google Scholar 

  61. Muth, R. F. (1973). A Vintage Model of the Housing Stock. Papers in Regional Science, 30, 141–156.

    Article  Google Scholar 

  62. Nachtrieb, R. (2013). System dynamics model of residential and commercial lighting markets. In 31st international conference of the system dynamics society, Cambridge, Massachusetts.

  63. Negahban, A., & Yilmaz, L. (2014). Agent-based simulation applications in marketing research: An integrated review. Journal of Simulation, 8(2).

  64. Park, W. Y., & Phadke, A. A. (2017). Adoption of energy-efficient televisions for expanded off-grid electricity service. Development Engineering, 2, 107–113.

    Article  Google Scholar 

  65. Park, W. Y., Phadke, A., Shah, N., & Letschert, V. (2013). Efficiency improvement opportunities in TVs: Implications for market transformation programs. Energy Policy, 59, 361–372.

    Article  Google Scholar 

  66. Pielli, K., Angel, S., & Mansueti, L. (2008). Understanding cost-effectiveness of energy efficiency programs: best practices, technical methods, and emerging issues for policy-makers. Technical Report. Washington, DC: U.S. Environmental Protection Agency Office of Air and Radiation.

  67. Pothitou, M., Hanna, R. F., & Chalvatzis, K. (2016). Environmental knowledge, pro-environmental behaviour and energy savings in households: An empirical study. Applied Energy, 184, 1217–1229.

  68. Ramsey, F. P. (1928). A mathematical theory of saving. The Econometrics Journal, 38, 543–559.

    Google Scholar 

  69. REGULATIONS COMMISSION REGULATION (EU) No 801/2013 of 22 August 2013 (n.d.). [Online]. https://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2013:225:0001:0012:en:PDF

  70. Rubin, E., Kido, C., May-Ostendo, P., Mercier, C., & Dayem, K. (2019). Global forecast of energy use for wireless charging. Report prepared for 4E Electronic Devices and Network Annex.

  71. van Sark, W., Nemet, G., Kahouli-Brahmi, S., & Neij, L. (2010). General aspects and caveats of experience curve analysis. In Technological learning in the energy sector - lessons for policy, industry and science. Cheltenham: Edward Elgar Publishing Ltd.

  72. Schleich, J., Gassmann, X., Faure, C., & Meissner, T. (2016. [Online]). Making the implicit explicit: A look inside the implicit discount rate. Energy Policy, 97, 321–331. https://doi.org/10.1016/j.enpol.2016.07.044.

    Article  Google Scholar 

  73. SFSO Construction de logement. [Online]. SFSO, 2014. (2015b). Construction, logement. Available at: http://www.bfs.admin.ch/bfs/portal/fr/index/news/publikationen.html?publicationID=6994

  74. Steinbach, J., & Staniaszek, D. (2015). Discount rates in energy system analysis discussion paper. Berlin: BPIE.

  75. Stephenson, J., Barton, B., Carrington, G., & Gnoth, D. (2010). Energy cultures: A framework for understanding energy behaviours. Energy Policy, 38, 6120–6129.

    Article  Google Scholar 

  76. Stern, N. (2007). The economics of climate change: the stern review. Cambridge: Cambridge University Press.

  77. Sweeney, J., & Powley, B. (2008). Probabilistic cost of light models for solid state lighting in general illumination markets.

  78. Switzerland government bond 10Y (n.d.). [Online]. http://www.tradingeconomics.com/switzerland/government-bond-yield

  79. Thiébaud, E., Hilty, L. M., Schluep, M., & Faulsti. (2014). EU ENERGY STAR imaging equipment specifications v2.0. [Online]. https://www.eu-energystar.org/downloads/specifications/Imaging%20Equipment%20v2.0%20-%20CELEX_32014D0202_EN_TXT.pdf

  80. Thiébaud, E., Hilty, L. M., Schluep, M., & Faulsti. (2015a). EU ENERGY STAR computers specifications v6.1. [Online]. https://www.eu-energystar.org/downloads/specifications/Computers%20v6.1%20-%20CELEX_32015D1402_EN_TXT.pdf

  81. Thiébaud, E., Hilty, L. M., Schluep, M., & Faulsti. (2015b). SFSO Construction de logement. [Online]. SFSO, 2014. Construction, logement. Available at: http://www.bfs.admin.ch/bfs/portal/fr/index/news/publikationen.html?publicationID=6994

  82. Thiébaud, E., Hilty, L. M., Schluep, M., & Faulsti. (2016). EU ENERGY STAR displays specifications v7.0. [Online]. https://www.eu-energystar.org/downloads/specifications/Displays%20v6.0%20-%20CELEX_32014D0202_EN_TXT.pdf

  83. Thiébaud, E., Hilty, L. M., Schluep, M., & Faulsti. (2017a). Use, storage, and disposal of electronic equipment in Switzerland. Environmental Science & Technology, 51(8), 4494–4502.

    Article  Google Scholar 

  84. Urban, B., Roth, K., Singh, M., & Howes, D. (2017). Energy consumption of consumer electronics in U.S. homes in 2017. Fraunhofer: Center for Sustainable Energy Systems.

  85. Van der Voet, E., Kleijn, R., Huele, R., & Ishikawa, M. (2002). Predicting future emissions based on characteristics of stocks. Ecological Economics, 41(2), 223–234.

    Article  Google Scholar 

  86. “Verkäufe von Informations- und Kommunikationstechnologien und Unterhaltungselektronik in der Schweiz,” GfK Switzerland AG, Hergiswil, Technical report 2015. https://www.gfk.com/fileadmin/user_upload/country_one_pager/CH/documents/2015/

  87. “Verkaufszahlenbasierte Energieeffizienzanalyse von Elektrogeräten,” Energie Agentur Electrogeräte (EAE), Technical Report 2016.

  88. Viegand, J., Huang, B., Drysdale, L. M., & Kemna, R. (n.d.). Review study on standby regulation study on the review of the regulation (EC) No 1275/2008. Prepared for European Commission.

  89. Wang, F., Huisman, J., Stevels, A., & Balde, C. P. (2013. [Online]). Enhancing e-waste estimates: Improving data quality by multivariate input–output analysis. Waste Management, 33(11), 2397–2407. https://doi.org/10.1016/j.wasm.

    Article  Google Scholar 

  90. Weiss, R. (2015). Weissbuch 2015, Der ICT-Market report. Männedorf: Robert Weiss Consulting.

  91. Whitmarsh, L., Upham, P., Poortinga, W., & McLachlan, D. (2011). Public attitudes, understanding, and engagement in relation to low carbon energy: A selective review of academic and non academic literatures. Swindon: Report for Research Council UK (RCUK) Energy Programme.

    Google Scholar 

  92. Wierda, L., & Kemna, R. (2018). Ecodesign impact accounting status report 2018. [Online]. https://ec.europa.eu/energy/sites/ener/files/documents/eia_status_report_2017_-_v20171222.pdf.

  93. Worrell, E., Laitner, J. A., Ruth, M., & Finman, H. (2003). Productivity benefits of industrial energy efficiency measures. Energy, 28, 1081–1098.

    Article  Google Scholar 

  94. Yilmaz, S., Majcen, D., Heidari, M., Mahmoodi, J., Brosch, T., & Patel M. K. (2018). Analysis of the impact of energy efficiency labelling and potential changes on electricity demand reduction of white goods using a stock model: The case of Switzerland. Applied Energy, 239, 117–132.

  95. Zahner, M., Fröhlich, J., & Dürrenberger, G. (2017). Energieeffizienz und EMF-Immissionen von integrierten Induktionsladestationen. Commissioned by the Swiss Federal Office for Energy (SFOE).

  96. Zhang, L., Yuan, Z., & Bi, J. (2011). Predicting future quantities of obsolete household appliances in Nanjing by a stock-based model. Resources, Conservation and Recycling, 55(11), 1087–1094.

  97. Zhuang, J., Liang, Z., Lin, T., & De Guzman, F. (2007). Theory and practice in the choice of social discount rate for cost-benefit analysis: a survey. Economics Working Paper No. 94. Manila: Asian Development Bank.

  98. Zuberi, M. J. S., & Patel, M. K. (2016). Bottom-up analysis of energy efficiency improvement and CO2 emission reduction potentials in the Swiss cement industry. Journal of Cleaner Production, 142, 4294–4309.

  99. Zuberi, M. J. S., Tijdink, A., & Patel, M. K. (2017). Techno-economic analysis of energy efficiency improvement in electric motor driven systems in Swiss industry. Applied Energy, 205, 85–104.

    Article  Google Scholar 

Download references

Acknowledgements

This research project was financially supported by the Swiss Innovation Agency Innosuisse (former name: Swiss Commission for Technology and Innovation, CTI) and is part of the Swiss Competence Center for Research in Energy, Society and Transition (CREST). We are grateful for this support and also thank the anonymous reviewers of the journal “Energy Efficiency” for their critical comments which have allowed to substantially improve the paper compared to its original version.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Mahbod Heidari.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

ESM 1

(DOCX 661 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Heidari, M., Patel, M. Stock modelling and cost-effectiveness analysis of energy-efficient household electronic appliances in Switzerland. Energy Efficiency 13, 571–596 (2020). https://doi.org/10.1007/s12053-020-09843-x

Download citation

Keywords

  • Energy Efficiency
  • Cost-Effectiveness
  • Stock Model
  • Electronic Appliances