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The role of educational trainings in the diffusion of smart metering platforms: An agent-based modeling approach

Author

Listed:
  • Tomasz Weron
  • Anna Kowalska-Pyzalska
  • Rafal Weron

Abstract

Using an agent-based modeling approach we examine the impact of educational programs and trainings on the diffusion of smart metering platforms (SMPs). We also investigate how social responses, like conformity or independence, mass-media advertising as well as opinion stability impact the transition from predecisional and preactional behavioral stages (opinion formation) to actional and postactional stages (decision-making) of individual electricity consumers. We find that mass-media advertising (i.e., a global external field) and educational trainings (i.e., a local external field) lead to similar, though not identical adoption rates. Secondly, that spatially concentrated 'group' trainings are never worse than randomly scattered ones, and for a certain range of parameters are significantly better. Finally, that by manipulating the time required by an agent to make a decision, e.g., through promotions, we can speed up or slow down the diffusion of SMPs.

Suggested Citation

  • Tomasz Weron & Anna Kowalska-Pyzalska & Rafal Weron, 2017. "The role of educational trainings in the diffusion of smart metering platforms: An agent-based modeling approach," HSC Research Reports HSC/17/04, Hugo Steinhaus Center, Wroclaw University of Technology.
  • Handle: RePEc:wuu:wpaper:hsc1704
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    References listed on IDEAS

    as
    1. Gadenne, David & Sharma, Bishnu & Kerr, Don & Smith, Tim, 2011. "The influence of consumers' environmental beliefs and attitudes on energy saving behaviours," Energy Policy, Elsevier, vol. 39(12), pages 7684-7694.
    2. repec:wsi:ijmpcx:v:11:y:2000:i:06:n:s012918310000105x is not listed on IDEAS
    3. Sobkowicz, Pawel, 2016. "Agent based model of effects of task allocation strategies in flat organizations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 17-30.
    4. Gangale, Flavia & Mengolini, Anna & Onyeji, Ijeoma, 2013. "Consumer engagement: An insight from smart grid projects in Europe," Energy Policy, Elsevier, vol. 60(C), pages 621-628.
    5. Byrka, Katarzyna & Jȩdrzejewski, Arkadiusz & Sznajd-Weron, Katarzyna & Weron, Rafał, 2016. "Difficulty is critical: The importance of social factors in modeling diffusion of green products and practices," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 723-735.
    6. Martins, André C.R. & Pereira, Carlos de B. & Vicente, Renato, 2009. "An opinion dynamics model for the diffusion of innovations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(15), pages 3225-3232.
    7. Claudy, Marius C. & Michelsen, Claus & O'Driscoll, Aidan & Mullen, Michael R., 2010. "Consumer awareness in the adoption of microgeneration technologies: An empirical investigation in the Republic of Ireland," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(7), pages 2154-2160, September.
    8. Galam, Serge, 2004. "Contrarian deterministic effects on opinion dynamics: “the hung elections scenario”," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 333(C), pages 453-460.
    9. Good, Nicholas & Ellis, Keith A. & Mancarella, Pierluigi, 2017. "Review and classification of barriers and enablers of demand response in the smart grid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 57-72.
    10. Lopes, M.A.R. & Antunes, C.H. & Martins, N., 2012. "Energy behaviours as promoters of energy efficiency: A 21st century review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(6), pages 4095-4104.
    11. Zhang, T. & Nuttall, W.J., 2008. "Evaluating Government’s Policies on Promoting Smart Metering in Retail Electricity Markets via Agent Based Simulation," Cambridge Working Papers in Economics 0842, Faculty of Economics, University of Cambridge.
    12. Kowalska-Pyzalska, Anna & Maciejowska, Katarzyna & Suszczyński, Karol & Sznajd-Weron, Katarzyna & Weron, Rafał, 2014. "Turning green: Agent-based modeling of the adoption of dynamic electricity tariffs," Energy Policy, Elsevier, vol. 72(C), pages 164-174.
    13. Galam, Serge & Jacobs, Frans, 2007. "The role of inflexible minorities in the breaking of democratic opinion dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 381(C), pages 366-376.
    14. Papachristos, George, 2017. "Diversity in technology competition: The link between platforms and sociotechnical transitions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 291-306.
    15. Anna Kowalska-Pyzalska, 2015. "Social acceptance of green energy and dynamic electricity tariffs - a short review," HSC Research Reports HSC/15/07, Hugo Steinhaus Center, Wroclaw University of Technology.
    16. Diaz-Rainey, Ivan & Tzavara, Dionisia, 2012. "Financing the decarbonized energy system through green electricity tariffs: A diffusion model of an induced consumer environmental market," Technological Forecasting and Social Change, Elsevier, vol. 79(9), pages 1693-1704.
    17. repec:eee:rensus:v:82:y:2018:i:p3:p:3570-3581 is not listed on IDEAS
    18. repec:wsi:acsxxx:v:17:y:2014:i:01:n:s0219525914500040 is not listed on IDEAS
    19. Krishnamurti, Tamar & Schwartz, Daniel & Davis, Alexander & Fischhoff, Baruch & de Bruin, Wändi Bruine & Lave, Lester & Wang, Jack, 2012. "Preparing for smart grid technologies: A behavioral decision research approach to understanding consumer expectations about smart meters," Energy Policy, Elsevier, vol. 41(C), pages 790-797.
    20. Katarzyna Sznajd-Weron, 2005. "Sznajd model and its applications," HSC Research Reports HSC/05/04, Hugo Steinhaus Center, Wroclaw University of Technology.
    21. Piotr Przybyła & Katarzyna Sznajd-Weron & Rafał Weron, 2014. "Diffusion Of Innovation Within An Agent-Based Model: Spinsons, Independence And Advertising," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 17(01), pages 1-22.
    22. Alexandra-Gwyn Paetz & Elisabeth Dütschke & Wolf Fichtner, 2012. "Smart Homes as a Means to Sustainable Energy Consumption: A Study of Consumer Perceptions," Journal of Consumer Policy, Springer, vol. 35(1), pages 23-41, March.
    23. Paul R. Nail & Katarzyna Sznajd-Weron, 2016. "The diamond model of social response within an agent-based approach," HSC Research Reports HSC/16/02, Hugo Steinhaus Center, Wroclaw University of Technology.
    24. Ringler, Philipp & Keles, Dogan & Fichtner, Wolf, 2016. "Agent-based modelling and simulation of smart electricity grids and markets – A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 205-215.
    25. Katarzyna Sznajd-Weron & Janusz Szwabinski & Rafal Weron & Tomasz Weron, 2013. "Rewiring the network. What helps an innovation to diffuse?," HSC Research Reports HSC/13/09, Hugo Steinhaus Center, Wroclaw University of Technology.
    26. Anna Kowalska-Pyzalska & Karolina Cwik & Arkadiusz Jedrzejewski & Katarzyna Sznajd-Weron, 2016. "Linking consumer opinions with reservation prices in an agent-based model of innovation diffusion," HSC Research Reports HSC/16/03, Hugo Steinhaus Center, Wroclaw University of Technology.
    27. Rixen, Martin & Weigand, Jürgen, 2014. "Agent-based simulation of policy induced diffusion of smart meters," Technological Forecasting and Social Change, Elsevier, vol. 85(C), pages 153-167.
    28. Jȩdrzejewski, Arkadiusz & Sznajd-Weron, Katarzyna & Szwabiński, Janusz, 2016. "Mapping the q-voter model: From a single chain to complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 446(C), pages 110-119.
    29. Gerpott, Torsten J. & Paukert, Mathias, 2013. "Determinants of willingness to pay for smart meters: An empirical analysis of household customers in Germany," Energy Policy, Elsevier, vol. 61(C), pages 483-495.
    30. Anna Kowalska-Pyzalska, 2016. "What makes consumers adopt to innovative energy services in the energy market?," HSC Research Reports HSC/16/09, Hugo Steinhaus Center, Wroclaw University of Technology.
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    More about this item

    Keywords

    Smart meter; Smart metering platform (SMP); Behavioral strategy; Demand response; Diffusion of innovations; Agent-based model;

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation
    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth

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