A general technology adoption model of solar photovoltaic under feed-in tariff policy incorporating learning and network effects.

There is now a plethora of renewable energy policy instruments to support the adoption of renewable energy technology and the generation of renewable electricity. Different ways to characterize such policies have included whether these policies are Price driven or Quota (Quantity) driven, generation based or capacity driven, etc. All such incentive-based policies (vs. Command and control policies) attempt to correct market failure of under supply of renewable energy. This paper uses a technology adoption approach to study the feed-in tariff policy for the photovoltaic (PV) technology. We developed a general economic model to study the adoption incentive for smaller system under a feed-in tariff regime. The model incorporates both the learning effect of system cost and a negative network externality effect inherent in the feed-in tariff policy. The latter is due to that nonadopters would need to contribute to payment for adopters' electricity generation. Using numerical methods, we demonstrated that the feed-in tariff model has the potential to exhibit bandwagon or accelerated adoption effects. Cost learning is key to contributing to this but network effects would serve to dampen it. Our model seems to able to explain the rapid growth pattern in PV systems installation capacity and generation in Germany during the growth period of 1999-2003. We explore some policy implications of the model and suggest future research directions. [ABSTRACT FROM AUTHOR]