Building a photovoltaic marketing model based on feed-in tariffs and system installed cost

The purpose of this research is to establish an analytic model that combines energy policy and the photovoltaic (PV) industry from the governmental perspective. We suggest that government decision-makers set a policy goal for the cumulated installed total quantity of grid-connected PV systems for a certain planning horizon. The objective of their mathematical programming is to minimize the system total average cost of feed-in tariffs (FITs) policy support and the learning investment per kilowatt (kW) PV system installed. In order to attain this goal, they must determine the appropriate FIT unit price and constant change rate that will stimulate residents of developing countries to install the PV systems rapidly. We also expect to achieve a learning effect through the accumulating experience in grid-connected PV systems that will reduce the system installed cost per kW each year. Our analysis reveals that the unit PV installed cost decreases with time and that the cost reduction is quite rapid when the change rate is large. To a certain extent, levering the magnitude of the change rate could affect the growth of the PV product life cycle. If governments in developing countries need to install a large quantity of PV systems at an early stage to reverse global warming or overcome the effects of climate change, then they must choose a higher change rate with a relatively larger initial FIT unit price to a FIT scheme.