Mort Webster is a Professor of Energy Engineering, and his research program focuses on stochastic optimization for energy and environmental systems. Prof. Webster specializes in risk analysis, uncertainty analysis, and decision-making under uncertainty, particularly as applied to electric power systems. He has published numerous peer-reviewed articles in energy and environmental science, engineering, economics, and policy, and has served on several national and international panels, including the U.S. EPA Science Advisory Board. Current research projects include planning and operations of the electric power system under uncertainty, electricity market design to incentivize flexibility, and integrating power system models with environmental system models to represent water and air quality feedbacks. Prior to joining Penn State, Prof. Webster was Assistant and Associate Professor of Engineering Systems at the Massachusetts Institute of Technology (2006-2013) and Assistant Professor of public policy in the Department of Public Policy at the University of North Carolina at Chapel Hill (2001-2006). He received a Ph.D. (2000) in Engineering Systems and a M.S. (1996) in Technology and Policy from MIT, and a B.S.E. (1988) in Computer Science and Engineering from the University of Pennsylvania.
Electric Power Transmission Planning Under Uncertainty
This project is developing new algorithms for multi-stage transmission planning under uncertainty that can scale efficiently for large (RTO-scale) networks, large numbers of candidate lines, large numbers of scenarios, and two or more decision stages with recourse.
- Funding: National Science Foundation, U.S. Department of Energy
- Graduate Student: Jesse Bukenberger
- Collaborator: Uday Shanbhag
Coupled Multi-Sector Dynamics and Resilience
This project includes several efforts to develop a hierarchy of power system models of varying scale and complexity, and couple these models with models of other coupled systems, including water balance models, economic models, and agricultural models, to explore resilience of the coupled systems. These efforts are part of The Program for Coupled Human and Earth Systems (PCHES) is a project, funded by the U.S. Department of Energy, looking to create a state-of-the-art framework of computational tools that will help to assess the impacts of weather-related variability and change.
- Funding: U.S. Department of Energy, Office of Science
- Graduate Students: Vijay Kumar, Brayam Valqui
- Collaborators: Karen Fisher-Vanden
Value of Flexibility in Power Systems
The project is exploring the economic value of adding specific flexibility features to electric power generation in terms of 1) total cost to the system (i.e., to the consumer), and 2) the change in net revenues (profits) to the owner of the generation unit. In collaboration with engineers at General Electric's Power Services Division and Energy Consulting, we test the relative impacts of modifying natural gas combustion turbines to shorten startup times, increase ramp rates, lower the minimum output level, and increase the maximum output level. We use unit commitment models of actual systems with both deterministic and stochastic version.
- Funding: General Electric, Power Services
- Graduate Student: Sourabh Dalvi
- Webster, M.D., Zhao*, B., Bukenberger*, J., and Blumsack, S. (2021). The Transition to Low-Carbon Electric Power: Portfolios, Flexibility, and Option Value. Environmental Science & Technology (Accepted).
- Valqui*, B., Webster, M.D., Sun, S., and Hertel, T. (2021). Technology Adoption in Electricity Markets: Game-Theoretic Framework Approach for Coupling Market Models. The Energy Journal (Accepted).
- Webster, M., Fisher-Vanden, K., Lammers, R.B., Kumar*, V., and Perla, J. (2022). Integrated hydrological, power system and economic modeling of climate impacts on electricity demand and cost. Nature Energy 7 (February 2022): 163-169. DOI: 10.1038/s41560-021-00958-8.
- Zhao*, B., Bukenberger*, J., and Webster, M. (2021). Scenario Reduction Methods for Two-Stage Stochastic Generation Expansion under Multi-Scale Uncertainty. IEEE Transactions on Power Systems 37 (3): 2371-2383. DOI: 10.1109/TPWRS.2021.3121369.
- Varghese*, S., Dalvi*, S., Narula, N., and Webster, M. (2021). The Impacts of Distinct Flexibility Enhancements on the Value and Dynamics of Natural Gas Power Plant Operations. IEEE Transactions on Power Systems 36 (6): 5803-5813. DOI: 10.1109/TPWRS.2021.3084367.
- Sun, S., Valqui Ordonez*, B., Webster, M.D., Liu, J., Kucharik, C.J., and Hertel, T. (2020). Fine-Scale Analysis of the Energy−Land−Water Nexus: Nitrate Leaching Implications of Biomass Cofiring in the Midwestern United States. Environmental Science & Technology 54: 2122−2132. DOI: 10.1021/acs.est.9b07458.
- Bukenberger*, J.P., and Webster, M. (2019). Approximate Latent Factor Algorithm for Scenario Selection and Weighting in Transmission Expansion Planning. IEEE Transactions on Power Systems 35 (2) 1099-1108. DOI: 10.1109/TPWRS.2019.2942925.
- Morris, J., Srikrishnan, V., Webster, M., and Reilly, J. (2018). Hedging Strategies: Electricity Investment Decisions under Policy Uncertainty. Energy Journal 39 (1) 101-122. (View)
- Webster, M., Fisher-Vanden, K., Popp, D., and Santen, N. (2017). Should We Give Up After Solyndra? Optimal Technology R&D Portfolios under Uncertainty. Journal of the Association of Environmental and Resource Economics. 4 (S1) (September 2017, Part 2): S123-S151. (View)
- Santen, N.R., Webster, M.D., Popp, D. and Perez-Arriaga, I. (2017). Inter-temporal R&D and capital investment portfolios for the electricity industry’s low carbon future. The Energy Journal. 38 (1), 1-24. (View)
- McDonald-Buller, Elena, Kimura, Yosuke, Craig, Michael, McGaughey, Gary, Allen, David and Webster, Mort (2016). Dynamic Management of NOX and SO2 Emissions in the Texas and Mid-Atlantic Electric Power Systems and Implications for Air Quality (2016). Environ. Sci. Technol., 50 (3): 1611-1619. (View)
- Palmintier, B. and Webster, M. (2016). Impact of Operational Flexibility on Generation Planning. IEEE Transactions on Sustainable Energy. 7 (2) 672-684. (View)
- Díaz, C.A., Webster, M., Villar, J. and Campos, F.A. (2016). Market Power in ERCOT System: a Fundamental CSFE with Network Constraints. IEEE Transactions on Power Systems 31 (2): 861-871. (View)
- Parpas, P., Ustun, B., Webster, M., and Tran, Quang Kha (2015). Importance Sampling in Stochastic Programming: A Markov Chain Monte Carlo Approach. INFORMS Journal on Computing 27 (2) 358 – 377. (View)
- de Sisternes, F.J., Webster, M.D., and Perez-Arriaga, J.I. (2015). The Impact of Bidding Rules on Electricity Markets with Intermittent Renewables. IEEE Transactions on Power Systems 30 (3) 1603 - 1613. (View)
- Eide, J., de Sisternes, F., Herzog, H. and Webster, M. (2014). CO2 emissions standards and investment in carbon capture. Energy Economics 45 (2014) 53–65. (View)
- Palmintier, B. and Webster, M. (2014). Heterogeneous Unit Clustering for Efficient Operational Flexibility Modeling. IEEE Transactions on Power Systems 29 (3): 1089-1098. (View)
- Parpas, P. and Webster, M. (2014). A stochastic multiscale model for electricity generation capacity expansion. European Journal of Operational Research 232 (2): 359-374. (View)
- Webster, M., Donohoo, P., and Palmintier, B. (2013). Water-CO2 Tradeoffs in Electricity Generation Planning. Nature Climate Change 3 (27 October 2013): 1029-1032. (View)
U.S. Department of Energy Early Career Award, January, 2010.