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Optimal Feed‐In Tariff Policies: The Impact of Market Structure and Technology Characteristics

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  • Shadi Goodarzi
  • Sam Aflaki
  • Andrea Masini

Abstract

This study models a multi‐player environment consisting of a grid operator responsible for meeting electricity demands, a photovoltaic (PV) manufacturer, customers who might install (solar) PV systems, and a regulator who must set an optimal feed‐in tariff (FIT). The grid operator must meet exogenous electricity demand and also buy back all electricity (produced by PV systems) at the FIT set by the regulator. Customers decide whether or not to invest in a PV system. Adoption rates affect the manufacturer and operator by (respectively) establishing the demand for PV systems and determining how much PV electricity is fed into the grid. The PV manufacturer’s decision variable is the sales price per PV unit. The decisions of all players in the model are intertwined in a way that clearly affects their respective welfare. We demonstrate in particular how technology and market characteristics—including PV manufacturing cost and market competition—change the optimal decisions of players and thereby influence the effectiveness of FITs, the number of PV adopters, and the cost to provide the social benefit of on‐demand electricity. Our findings confirm the importance of considering technology manufacturers when devising schemes to incentivize the adoption of PV systems.

Suggested Citation

  • Shadi Goodarzi & Sam Aflaki & Andrea Masini, 2019. "Optimal Feed‐In Tariff Policies: The Impact of Market Structure and Technology Characteristics," Production and Operations Management, Production and Operations Management Society, vol. 28(5), pages 1108-1128, May.
  • Handle: RePEc:bla:popmgt:v:28:y:2019:i:5:p:1108-1128
    DOI: 10.1111/poms.12971
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    Cited by:

    1. Konstantina Valogianni & Wolfgang Ketter & John Collins & Dmitry Zhdanov, 2020. "Sustainable Electric Vehicle Charging using Adaptive Pricing," Production and Operations Management, Production and Operations Management Society, vol. 29(6), pages 1550-1572, June.
    2. Li, Yanan & Lin, Jun & Qian, Yanjun & Li, Dehong, 2023. "Feed-in tariff policy for biomass power generation: Incorporating the feedstock acquisition process," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1113-1132.
    3. Zakeri, Behnam & Cross, Samuel & Dodds, Paul.E. & Gissey, Giorgio Castagneto, 2021. "Policy options for enhancing economic profitability of residential solar photovoltaic with battery energy storage," Applied Energy, Elsevier, vol. 290(C).
    4. Matinfard, Sahar & Yaghoubi, Saeed & Kharaji Manouchehrabadi, Maedeh, 2024. "A coordinated approach for a three-echelon solar-wind energy supply with government intervention," Utilities Policy, Elsevier, vol. 86(C).
    5. Goodarzi, Shadi & Masini, Andrea & Aflaki, Sam & Fahimnia, Behnam, 2021. "Right information at the right time: Reevaluating the attitude–behavior gap in environmental technology adoption," International Journal of Production Economics, Elsevier, vol. 242(C).

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