BioAlan H. Sanstad is a Staff Scientist in the Energy Technologies Area at the Lawrence Berkeley National Laboratory. Dr. Sanstad received the A.B. degree in Applied Mathematics, and the M.S. and Ph.D. degrees in Operations Research, from the University of California at Berkeley. Dr. Sanstad’s research and publications have included work on the economics and policy analysis of end-use energy efficiency, technological change in energy-economic simulation modeling, and integrated assessment of global climate change. His recent work has focused on developing new approaches to long-run quantitative modeling and decision-making pertaining to energy system transitions, large-scale greenhouse gas abatement, and other issues in the energy, environmental, and technology policy arenas. Dr. Sanstad has worked with the U. S. Environmental Protection Agency, the California Energy Commission, the U. S. Department of Energy, and non-governmental organizations in developing and implementing research strategies, policies, and projects on energy, greenhouse gas mitigation, and related topics. He is an affiliate researcher of the Energy & Resources Group at U. C. Berkeley and of the NSF-sponsored Center for Robust Decision-Making on Climate and Energy Policy at the University of Chicago.
Case Studies of the Economic Impacts of Power Interruptions and Damage to Electricity System Infrastructure from Extreme Events
Frontiers in the Economics of Widespread, Long-Duration Power Interruptions: Proceedings from an Expert Workshop
Estimating the cost of saving electricity through U.S. utility customer-funded energy efficiency programs
Regional Economic Modeling of Electricity Supply Disruptions: A Review and Recommendations for Research
Modeling an aggressive energy-efficiency scenario in long-range load forecasting for electric power transmission planning
Incorporating energy efficiency into electric power transmission planning: A western United States case study
Substitution and price elasticity estimates using inter-country pooled data in a translog cost model