Management of Energy Technology for Sustainability: How to Fund Energy Technology Research and Development

Operations management methods have been applied profitably to a wide range of technology portfolio management problems, but have been slow to be adopted by governments and policy makers. We develop a framework that allows us to apply such techniques to a large and important public policy problem: energy technology R&D portfolio management under climate change. We apply a multi‐model approach, implementing probabilistic data derived from expert elicitations into a novel stochastic programming version of a dynamic integrated assessment model. We note that while the unifying framework we present can be applied to a range of models and data sets, the specific results depend on the data and assumptions used and therefore may not be generalizable. Nevertheless, the results are suggestive, and we find that the optimal technology portfolio for the set of projects considered is fairly robust to different specifications of climate uncertainty, to different policy environments, and to assumptions about the opportunity cost of investing. We also conclude that policy makers would do better to over‐invest in R&D rather than under‐invest. Finally, we show that R&D can play different roles in different types of policy environments, sometimes leading primarily to cost reduction, other times leading to better environmental outcomes.     

Lower Cost Arrivals for Airlines: Optimal Policies for Managing Runway Operations under Optimized Profile Descent

Optimized profile descent (OPD) is an operating procedure being used by airlines to improve fuel and environmental efficiency during arrival operations at airports. In this study, we develop a stochastic dynamic programming framework to manage the sequencing and separation of flights during OPD operations. We find that simple calculation based measures can be used as optimal decision rules, and that the expected annual savings can be around $29 million if such implementations are adapted by major airports in the United States. Of these savings, $24 million are direct savings for airlines due to reduced fuel usage, corresponding to a potential savings of 10%–15% in fuel consumption over current practice. We also find that most of these savings will be due to the optimal spacing of OPD flights, as opposed to the optimal sequencing policies which contribute only 14% to the total savings. Hence, optimal spacing of OPD flights is much more important than optimal sequencing of these flights. We also conclude that there is not much difference between the environmental costs of fuel‐optimal and sustainably‐optimal spacing policies. Hence, an airline‐centric approach in improving OPD operations is likely to be not in conflict with objectives that might be prioritized by other stakeholders.