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Modeling the Diffusion of Residential Photovoltaic Systems in Italy: An Agent-based Simulation

  • Palmer, Johannes

    ()

    (RWTH Aachen University)

  • Sorda, Giovanni

    ()

    (E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN))

  • Madlener, Reinhard

    ()

    (E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN))

We propose an agent-based model to simulate the diffusion of small PV systems among single- or two-family homes in Italy over the 2006-2026 period. To this end,we explicitly model the geographical distribution of the agents in order to account for regional differences across the country. The adoption decision is assumed to be influenced predominantly by (1) the payback period of the investment, (2) its environmental benefit, (3) the household’s income, and (4) the influence of communication with other agents. For the estimation of the payback period, the model considers investment costs, local irradiation levels, governmental support, earnings from using self-produced electricity vs. buying electricity from the grid, as well as various administrative fees and maintenance costs. The environmental benefit is estimated by a proxy for the CO2 emissions saved. The level of the household income is associated with the specific economic conditions of the region where the agent is located, as well as the agent’s socio-economic group (age group, level of education, household type). Finally, the influence of communication is measured by the number of links with other households that have already adopted a PV system. In each simulation step, the program dynamically updates the social system and the communication network, while the evolution of the PV system’s investment costs depend on a one-factor experience curve model that is based on the exogeneous development of the global installed PV capacity. Our results show that Italy’s domestic PV installations are already beyond an initial stage of rapid growth and, though likely to spread further, they will do so at a significantly slower rate of diffusion.

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Paper provided by E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN) in its series FCN Working Papers with number 9/2013.

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Length: 42 pages
Date of creation: May 2013
Date of revision:
Handle: RePEc:ris:fcnwpa:2013_009
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  1. Meade, Nigel & Islam, Towhidul, 2006. "Modelling and forecasting the diffusion of innovation - A 25-year review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 519-545.
  2. Yuan, Xueliang & Zuo, Jian & Ma, Chunyuan, 2011. "Social acceptance of solar energy technologies in China--End users' perspective," Energy Policy, Elsevier, vol. 39(3), pages 1031-1036, March.
  3. Zhai, Pei & Williams, Eric D., 2012. "Analyzing consumer acceptance of photovoltaics (PV) using fuzzy logic model," Renewable Energy, Elsevier, vol. 41(C), pages 350-357.
  4. Crescenzio Gallo & Michelangelo De Bonis, 2011. "Forecasting Photovoltaic Deployment with Neural Networks," Quaderni DSEMS 02-2011, Dipartimento di Scienze Economiche, Matematiche e Statistiche, Universita' di Foggia.
  5. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
  6. Dawid, Herbert, 2006. "Agent-based Models of Innovation and Technological Change," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 25, pages 1235-1272 Elsevier.
  7. Yang, Chi-Jen, 2010. "Reconsidering solar grid parity," Energy Policy, Elsevier, vol. 38(7), pages 3270-3273, July.
  8. Sorda, G. & Sunak, Y. & Madlener, R., 2013. "An agent-based spatial simulation to evaluate the promotion of electricity from agricultural biogas plants in Germany," Ecological Economics, Elsevier, vol. 89(C), pages 43-60.
  9. Faiers, Adam & Neame, Charles & Cook, Matt, 2007. "The adoption of domestic solar-power systems: Do consumers assess product attributes in a stepwise process?," Energy Policy, Elsevier, vol. 35(6), pages 3418-3423, June.
  10. Faber, Albert & Valente, Marco & Janssen, Peter, 2010. "Exploring domestic micro-cogeneration in the Netherlands: An agent-based demand model for technology diffusion," Energy Policy, Elsevier, vol. 38(6), pages 2763-2775, June.
  11. Malte Schwoon, 2006. "Simulating the adoption of fuel cell vehicles," Journal of Evolutionary Economics, Springer, vol. 16(4), pages 435-472, October.
  12. Malte Schwoon, 2005. "Simulating the Adoption of Fuel Cell Vehicles," Working Papers FNU-59, Research unit Sustainability and Global Change, Hamburg University, revised Feb 2006.
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