A Review of Real Options Analysis Methods for R&D Valuation in Renewable Energy Research

We propose a new real options analysis method for evaluating R&D investments using a novel Poisson process to simulate the discrete progress typical of R&D breakthroughs. We take explicit account of the technical risk of an R&D project, while the market risk and the effect of learning-by-doing in operational technologies are also explicitly modelled. We present a compound real option structure, where a European real option is used to model the fixed length term typical of early phase research, which is exercisable into an American real option to model later phase R&D. In this later phase, a successful outcome will be acted on immediately to operationalise the technology. We propose a Monte Carlo simulation approach, which models R&D progress in a stylised logistic function or 'S-bend' form, capturing the typically slow rate of R&D progress at the start of the early phase, through to more rapid improvement as the R&D advances, which then slows again as the limitations of the R&D are approached. We demonstrate that this method is applicable for evaluating the R&D investment potential in CO2 recycling technology, where an energy commodity (such as methane) is produced, using appropriate modelling for the price of the energy commodity. The method may be applied widely to R&D technology projects