Advertisement

Imagine 2025: Prosumer and Consumer Requirements for Distributed Energy Resource Systems Business Models

  • Susen DöbeltEmail author
  • Maria Kreußlein
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 965)

Abstract

The user-centered design and the acceptance of smart grid technologies is one key factor for their success. To identify user requirements, barriers and underlying variables of acceptance for future business models (DSO controlled, Voltage-Tariff, Peer-to-Peer) a partly-standardized interview study with N = 21 pro- and consumers was conducted. The results of quantitative and qualitative data demonstrate that the acceptance of each future energy business model is relatively high. The overall usefulness was rated higher for future business models than the current business model. Prosumers had a more positive attitude towards the Peer-to-Peer model, whereas consumers preferred models in which the effort is low (DSO controlled) or an incentive is offered (Voltage-Tariff). The DSO controlled model is not attractive for prosumers, who criticize the increased dependency and external control. From the results it can be concluded that tariffs should be adapted to the user type.

Keywords

Acceptance Consumer and prosumer requirements Distributed energy resource Energy tariffs Energy business models 

Notes

Acknowledgments

The current research is part of the “NEMoGrid” project and has received funding in the framework of the joint programming initiative ERA-Net SES focus initiative Smart Grids Plus, with support from the EU’s Horizon 2020 research and innovation programme under grant agreement No. 646039. The content and views expressed in this study are those of the authors and do not necessarily reflect the views or opinion of the ERA-Net SG+ initiative. Any reference given does not necessarily imply the endorsement by ERA-Net SG+. We appreciate the support of our student scientists, who supported data collection and analysis.

References

  1. 1.
    Bhatti, H.J.: The future of sustainable society—the state of the art of renewable energy and distribution systems. Thesis Industrial Management and Innovation, Halmstad University (2018)Google Scholar
  2. 2.
    Döbelt, S., Jung, M., Busch, M., Tscheligi, M.: Consumers’ privacy concerns and implications for a privacy preserving Smart Grid architecture—results of an Austrian study. Energy Res. Soc. Sci. 9, 137–145 (2015)CrossRefGoogle Scholar
  3. 3.
    Severance, C.A.: A practical, affordable (and least business risk) plan to achieve “80% clean electricity” by 2035. Electr. J. 24(6), 8–26 (2011)Google Scholar
  4. 4.
    Yildiz, Ö.: Financing renewable energy infrastructures via financial citizen participation—the case of Germany. Renew. Energy 68, 677–685 (2014)CrossRefGoogle Scholar
  5. 5.
    Richter, M.: Business model innovation for sustainable energy: German utilities and renewable energy. Energy Policy 62, 1226–1237 (2013)CrossRefGoogle Scholar
  6. 6.
    Viardot, E.: The role of cooperatives in overcoming the barriers to adoption of renewable energy. Energy Policy 63, 756–764 (2013)CrossRefGoogle Scholar
  7. 7.
    Wolsink, M.: The research agenda on social acceptance of distributed generation in smart grids: renewable as common pool resources. Renew. Sustain. Energy Rev. 16(1), 822–835 (2012)CrossRefGoogle Scholar
  8. 8.
    Kubli, M., Loock, M., Wüstenhagen, R.: The flexible prosumer: measuring the willingness to co-create distributed flexibility. Energy Policy 114, 540–548 (2018)CrossRefGoogle Scholar
  9. 9.
    Akorede, M.F., Hizam, H., Pouresmaeil, E.: Distributed energy resources and benefits to the environment. Renew. Sustain. Energy Rev. 14(2), 724–734 (2010)CrossRefGoogle Scholar
  10. 10.
    Von Wirth, T., Gislason, L., Seidl, R.: Distributed energy systems on a neighborhood scale: Reviewing drivers of and barriers to social acceptance. Renew. Sustain. Energy Rev. 82, 2618–2628 (2018)Google Scholar
  11. 11.
    Davis, F.D.: Perceived usefulness, perceived ease of use, and user acceptance. MIS Quart 13, 319–340 (1989)Google Scholar
  12. 12.
    Schwartz, S.H.: Normative influences on altruism. In: Leonard, B. (ed.). Advances in Experimental Social Psychology, 10, pp. 221—279, Academic Press (1977)Google Scholar
  13. 13.
    Schwartz, S.H., Howard, J.A.: A normative decision-making model of altruism. In: Rushton, J.P., Sorrentine, R.M. (eds.) Altruism and Helping Behaviour: Social, Personality, and Developmental Perspectives, pp. 189–211. Lawrence Erlbaum, Hillsdale, NJ (1981)Google Scholar
  14. 14.
    Schwartz, S.H., Howard, J.A.: Internalized values as moderators of altruism. In: Staub, E., Karylowski, B.-T., Reykowski, J. (eds.) Development and Maintenance of Prosocial Behavior: International Perspectives on Positive Morality, pp. 229–255. Plenum Press, New York (1984)CrossRefGoogle Scholar
  15. 15.
    Toft, M.B., Schuitema, G., Thøgersen, J.: Responsible technology acceptance: model development and application to consumer acceptance of Smart Grid technology. Appl. Energy 134, 392–400 (2014)Google Scholar
  16. 16.
    Energy, D.: Demand Response—The eFlex Project. Virum, Denmark (2012)Google Scholar
  17. 17.
    Bolderdijk, J.W., Steg L., Geller, E.S., Lehman, P.K., Postmes T.: Comparing the effectiveness of monetary versus moral motives in environmental campaigning. Nat. Clim. Chang. 3(4), 413–416 (2013)CrossRefGoogle Scholar
  18. 18.
    Landis, J.R., Koch, G.G.: The measurement of observer agreement for categorical data. Biometrics, pp. 159–174 (1977)Google Scholar
  19. 19.
    Döbelt, S., Kreußlein, M.: Results regarding consumer/prosumer requirements. Public project delivearable NEMoGrid (2018). http://nemogrid.eu/wp-content/uploads/D2.3-Results-regarding-consumer-prosumer-requirements_TUC.pdf
  20. 20.
    Easytranscript (version 2.50.7) [Transcription Software]. E-Werkzeug. https://www.e-werkzeug.eu/index.php/de/produkte/easytranscript

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Professorship of Cognitive and Engineering PsychologyChemnitz University of TechnologyChemnitzGermany

Personalised recommendations