Abstract:
This thesis presents an investment planning model that integrates learning curveinformation on renewable power generation technologies into a dynamic programming formulation featuring real options analysis. The model recursively evaluates a set ofinvestment alternatives on a year-by-year basis, thereby taking into account that theflexibility to delay an irreversible investment expenditure can profoundly affect thediffusion prospects of renewable power generation technologies. Price volatility is introduced through stochastic processes for the average electricity price and for input fuelprices. Demand for peak-load capacity is assumed to be increasingly price-elastic, as theelectricity market deregulation proceeds, and linearly dependent on the extent of marketopening. The empirical analysis is based on data for the Turkish electricity supply industry.Apart from general implications for policy-making, it provides some interesting insights about the impact of uncertainty on the diffusion of various emerging renewable energytechnologies.
