Energy Technology R&D Portfolio Management: Modeling Uncertain Returns and Market Diffusion

Abstract

The allocation of research and development (R&D) funds across a portfolio of programs must simultaneously consider uncertainty from research outcomes and from market acceptance of the resulting technologies. We introduce a stochastic R&D portfolio management framework for addressing both sources of uncertainty and present numerical results for energy technology R&D strategy under uncertainties in climate policy and natural gas prices. Numerical experiments indicate that R&D may be more valuable in second-best planning environments where decision-makers use expected-value approaches, and recourse investments occur after R&D has reduced costs. We also find that deterministic R&D valuation approaches likely overestimate the expected value of R&D success but undervalue the optionality and hedging potential of technologies relative to sequential decision-making approaches under uncertainty. The results also highlight the role of R&D in second-best policy environments.