From Laboratory to Production: Learning Models of Efficiency and Manufacturing Cost of Industrial Crystalline Silicon and Thin-Film Photovoltaic Technologies

Efficiency and manufacturing cost are two key elements for the photovoltaic (PV) industry. In this paper, we look at the time-dependent evolution of efficiency and manufacturing cost for PV devices. For efficiency improvements, the empirical model developed by Goetzberger et al. is applied to describe the time-dependent improvements for a concrete technology in laboratory cell's research and development, and the learning factor c is extracted. The application of the Goetzberger's model is extended to industrial PV modules. It is forecasted that cadmium telluride (CdTe) and copper gallium indium diselenide (CIGS) will have the average module efficiency in 2020 of 17.9% and 16.4%, respectively. Over 21.8% commercial module efficiency is projected with n-type Si interdigitated back contact technology, while average module efficiencies of 17.4%, 18.4%, and 19.4% are projected for conventional p-type multi-, mono-, and mono-passivated emitter and rear cell (PERC), respectively. For the manufacturing cost, we parameterized the learning curve model of manufacturing cost for industrial crystalline silicon (c-Si), CdTe, and CIGS technologies. As projected by the learning curve, the manufacturing cost of c-Si and thin-film modules may reach 0.2 $/Wp or below, when the cumulative production reach 1 TW. The learning rate for Si (24.2%) is greater than CdTe (19.1%) and CIGS (8.1%).