Prof. Webster's research and teaching centers on the design, planning, and management of coupled energy and environmental systems with a particular focus on electric power systems. His research focus is on the development and application of methods for sequential decision under uncertainty, with a particular emphasis on applications to electric power systems planning and operations, energy systems design for flexibility and resilience, and environmental regulatory design. Long-term planning for infrastructure, such as the electric power system, is a complex sequence of decisions that must be made under uncertainty, with important interdependencies on other physical and economic systems. The characteristics of this problem class have required new algorithms and methodological innovations at the interface of engineering, economics, and operations research to enable tractable and computationally feasible solutions. The complexity of these coupled systems have required interdisciplinary collaborative approaches that integrate models and methods from traditionally distinct fields to understand the critical feedbacks. The application of these approaches to energy and environmental decision problems have also led to contributions to the climate change, regional air quality, power system planning and operations, and the energy-water nexus domains.
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
- 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.