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A Model of Subsidies and Feed-In Tariffs for the Deployment of Photovoltaic Energy in the Residential Sector in Tunisia

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  • Mahmoud Tnani
  • Hafedh Ben Abdennebi

Abstract

Through an analytical model, we investigate the effectiveness and efficiency of current government incentives in accelerating deployment of photovoltaic systems since 2010 in the Tunisian residential sector. Investor behavior takes into account the diffusion phenomenon, the learning phenomenon, and the net present value. We show that the currently adopted incentives do not provide a framework conducive to investment for both households and the PV industrial sector. Specifically, it was found that the effectiveness and efficiency of the incentive policy cannot be achieved while maintaining feed-in tariffs (FITs) equals to retail tariffs. Moreover, the sensitivity analysis results obtained from the model show that the net social benefits can be maximized when the capacities are installed during the early years, accompanied by incentive mechanisms through prices and subsidies. Our analysis also reveals that for Tunisia, which is a net importer of PV, the optimal net social benefit depends essentially on the social costs of subsidies and FITs, which are directly impacted by government policies. In contrast, the externalities, the benefits of consumers, the savings in natural gas, and the carbon credits are only slightly affected by government policies, since the objective in terms of installed capacity is reached at a time horizon.

Suggested Citation

  • Mahmoud Tnani & Hafedh Ben Abdennebi, 2015. "A Model of Subsidies and Feed-In Tariffs for the Deployment of Photovoltaic Energy in the Residential Sector in Tunisia," International Journal of Management Sciences, Research Academy of Social Sciences, vol. 6(5), pages 235-259.
  • Handle: RePEc:rss:jnljms:v6i5p2
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    1. Geroski, P. A., 2000. "Models of technology diffusion," Research Policy, Elsevier, vol. 29(4-5), pages 603-625, April.
    2. McDonald, Alan & Schrattenholzer, Leo, 2001. "Learning rates for energy technologies," Energy Policy, Elsevier, vol. 29(4), pages 255-261, March.
    3. Rao, K. Usha & Kishore, V.V.N., 2010. "A review of technology diffusion models with special reference to renewable energy technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(3), pages 1070-1078, April.
    4. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    5. Fouquet, Doerte & Johansson, Thomas B., 2008. "European renewable energy policy at crossroads--Focus on electricity support mechanisms," Energy Policy, Elsevier, vol. 36(11), pages 4079-4092, November.
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