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Line Roald

Line Roald

Grainger Institute for Engineering Associate Professor

Prof. Roald and her group focusses on facilitating the transition to a more sustainable and resilient energy system, while ensuring that electricity can be provided in an economically efficient and secure manner. To tackle challenges faced by participants in the energy industry, from system operators to power producers and consumers, we are developing mathematical tools and software implementations to model and optimize system operation and energy markets, while taking into account the impact of uncertain events such as variations renewable energy production, component failures and large-scale outages.

Department

Electrical & Computer Engineering

Contact

2544, Engineering Hall
1415 Engineering Dr
Madison, WI

Professor Line Roald - Department of Electrical and Computer Engineering at UW-Madison

  • PhD 2016, ETH Zurich
  • MS 2012, ETH Zurich
  • BS 2009, ETH Zurich

  • Modelling, optimization and control of the electric grid and the infrastructures that depend on it.
  • Integration of renewable energy to reduce carbon emissions.
  • Grid resilience to climate change-driven extreme events, with a focus on wildfire risk mitigation.
  • Stochastic optimization, risk analysis and data-driven methods.

  • 2024 University of Wisconsin-Madison, Inclusion, Equity and Diversity in Engineering Award
  • 2024 University of Wisconsin-Madison, Vilas Faculty Early Career Investigator Award
  • 2023 IEEE Power Tech, Best Student Paper Award (with Noah Rhodes)
  • 2023 Electrical and Computer Engineering, University of Wisconsin-Madison, ECE Gerald Holdridge Excellence in Teaching Award
  • 2022 Energy Track, Hawaii International Conf. on System Sciences (HICSS), Best Paper Award
  • 2021 National Science Foundation, NSF CAREER Award
  • 2020 Electrical and Computer Engineering, University of Wisconsin-Madison, ECE Outstanding Graduate Mentoring Award
  • 2019 University of Wisconsin-Madison, Madison Teaching and Learning Excellence (MTLE) Fellow
  • 2017 ETH Zurich, ETH Medal for Outstanding Doctoral Theses (Nominated)
  • 2014 Power System Computation Conference (PSCC), Best Paper Selection

  • Overbye, T. J., Davis, K., Heydt, G. T., & Roald, L. (2025). Survey of High Impact Electric Power System Papers, 1975-2024.
  • Gorka, J., & Roald, L. (2024). Classification Models for Forecasting and Real-Time Identification of Solar Curtailment in the California Grid. In Proceedings of the 15th ACM International Conference on Future and Sustainable Energy Systems (pp. 158–169).
  • Marathe, M., & Roald, L. (2024). Energy Management for Prepaid Customers: A Linear Optimization Approach. In 2024 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) (pp. 492–498).
  • Rossmann, R., Anitescu, M., Bessac, J., Ferris, M., Krock, M., Luedtke, J., & Roald, L. (2024). A Framework for Balancing Power Grid Efficiency and Risk with Bi-objective Stochastic Integer Optimization. arXiv preprint arXiv:2405.18538.
  • Lesniak, A., Johnsen, A. G., Rhodes, N., & Roald, L. (2024). Advanced Scheduling of Electrolyzer Modules for Grid Flexibility. arXiv preprint arXiv:2412.19345.
  • Gorka, J., Hsu, T., Li, W., Maximov, Y., & Roald, L. (2024). Cascading Blackout Severity Prediction with Statistically-Augmented Graph Neural Networks. arXiv preprint arXiv:2403.15363.
  • Gorka, J., Rhodes, N., & Roald, L. (2024). ElectricityEmissions. jl: A Framework for the Comparison of Carbon Intensity Signals. arXiv preprint arXiv:2411.06560.
  • Sharma, S., O’Donnell, J., Su, W., Mueller, R., Roald, L., Rehman, K., & Bernstein, A. (2024). Engineering Microgrids Amid the Evolving Electrical Distribution System. Energies, 17(19), 4764.
  • Akter, S., Dube, O. P., Villagra, P., Mockrin, M., Taylor, S., Roald, L., Di Giuseppe, F., Wu, C., Fernandes, P. M., & Rouet-Leduc, J. (2024). Fire risk in a warming world. One Earth, 7(6), 927--931.
  • Haag, E., Rhodes, N., & Roald, L. (2024). Long solution times or low solution quality: On trade-offs in choosing a power flow formulation for the optimal power shutoff problem. Electric Power Systems Research, 234, 110713.

  • E C E 901 - Special Topics in Electrical and Computer Engineering (Spring 2025)
  • E C E 990 - Dissertator's Research (Spring 2025)
  • COMP SCI 524 - Introduction to Optimization (Fall 2024)
  • E C E 524 - Introduction to Optimization (Fall 2024)
  • E C E 790 - Master's Research (Fall 2024)
  • E C E 890 - Pre-Dissertator's Research (Fall 2024)
  • E C E 990 - Dissertator's Research (Fall 2024)
  • E C E 999 - Advanced Independent Study (Fall 2024)
  • I SY E 524 - Introduction to Optimization (Fall 2024)
  • E C E 890 - Pre-Dissertator's Research (Summer 2024)
  • E C E 990 - Dissertator's Research (Summer 2024)
  • E C E 489 - Honors in Research (Spring 2024)
  • E C E 723 - On-Line Control of Power Systems (Spring 2024)
  • E C E 890 - Pre-Dissertator's Research (Spring 2024)
  • E C E 990 - Dissertator's Research (Spring 2024)
  • E C E 399 - Independent Study (Fall 2023)
  • E C E 489 - Honors in Research (Fall 2023)
  • E C E 890 - Pre-Dissertator's Research (Fall 2023)
  • E C E 990 - Dissertator's Research (Fall 2023)
  • E C E 790 - Master's Research (Summer 2023)
  • E C E 890 - Pre-Dissertator's Research (Summer 2023)
  • E C E 990 - Dissertator's Research (Summer 2023)