A dynamic behavioral model of the long-term development of solar photovoltaic generation driven by feed-in tariffs
Type
Journal Article
Year
2022
Publisher
Energy
Description
Authors: Taulant Kërçi, Georgios Tzounas, Federico Milano
Abstract: This work aims to assess the impact of renewable energy incentives, particularly that of the feed-in tariff (FiT), on the long-term development of (opens in a new window)solar photovoltaics (PVs). With this aim, the paper introduces a dynamic model based on nonlinear (opens in a new window)delay differential(opens in a new window)algebraic equations to simulate the evolution of the (opens in a new window)PV capacity and its commitment in the power grid. The model assumes the FiT budget, the (opens in a new window)PV cost and willingness of the public to install PVs as the main drivers for solar PV installations. In particular, the learning-by-doing concept to model the PV cost and consequently the PV deployment is proposed for the first time in this paper. The accuracy of the model is validated against (opens in a new window)historical data of two of the biggest PV markets in the world driven by FiT, namely, Italy during 2008–2014, and (opens in a new window)Germany during 2000–2014. A sensitivity analysis based on the Italian PV market is carried out to identify the impact of the parameters of the proposed model. Results indicate that the proposed model is a valuable tool that can help policymakers in the decision-making process, such as the definition of the FiT price and the duration of the incentives.