Mehrdad Pirnia, PEng

Dr. Mehrdad Pirnia received his Ph.D. degree from University of Waterloo in 2014 in Electrical and Computer Engineering (Power Systems Optimization). He also obtained his MASc degree in Management Sciences (Optimization Specialty). His undergraduate degree is in Industrial Engineering. The main focus of his research is on applying AI, optimization and stochastic techniques to enhance the operation and planning of energy systems.
Currently, he is a faculty member at the University of Waterloo, Department of Management Sciences. Before joining UWaterloo, he worked full-time in California ISO and ALSTOM Grid. He also did an internship at Federal Energy Regulatory Commission (FERC) during his PhD program.

• Electricity markets
• Operations research
• Data analytics
• Machine learning in energy applications
• Energy analytics
• Power system operations and planning

• 2014, Doctorate, Power System Engineering, University of Waterloo, Canada
• 2010, Master of Applied Science, Management Sciences, University of Waterloo, Canada

• MSE 100 - Management Engineering Concepts
  • Taught in 2024
• MSE 271 - Advanced Calculus and Numerical Methods
  • Taught in 2024

* Only courses taught in the past 5 years are displayed.

• Vera E.G., Canizares C., and Pirnia M., Geographic-information-based stochastic optimization model for multi-microgrid planning, Applied Energy, Volume 127, Canada, 2023.
• Vera E.G., Canizares C.A., Pirnia M., Guedes T.P., and Trujillo J.D.M., Two-Stage Stochastic Optimization Model for Multi-Microgrid Planning, IEEE Transactions on Smart Grid, Volume 14, 1723-1735, Canada, 2023.
• Pirnia M., Elsarague M., Beylunioglu F.C., Ahmed M., and Nathwani J., Impact of COVID-19 on Ontario's electricity market: Load, generation, emissions, Electricity Journal, Volume 35, Canada, 2022.
• Fuller J.D., and Pirnia M., Nonconvex multicommodity near equilibrium models: Energy markets perspective, Operations Research Perspectives, Volume 9, Canada, 2022.
• Lotfi A., and Pirnia M., Constraint-guided Deep Neural Network for solving Optimal Power Flow, Electric Power Systems Research, Volume 127, Canada, 2022.
• Vera E.G., Canizares C., and Pirnia M., Renewable Energy Integration in Canadian Remote Community Microgrids: The Feasibility of Hydrogen and Gas Generation, IEEE Electrification Magazine, Volume 8, 36-45, Canada, 2020.
• Shavandi H., Pirnia M., and Fuller J.D., Extended opportunity cost model to find near equilibrium electricity prices under non-convexities, Applied Energy, Volume 127, 251-264, Iran, 2019.
• Lipka P.A., Campaigne C., Pirnia M., O'Neill R.P., and Oren S.S., Constructing transmission line current constraints for the IEEE and polish systems, Energy Systems, Volume 8, 199-216, United States, 2017.
• Pirnia M., Canizares C.A., Bhattacharya K., and Vaccaro A., A novel affine arithmetic method to solve optimal power flow problems with uncertainties, IEEE Transactions on Power Systems, Volume 29, 2775-2783, Canada, 2014.
• Pirnia M., Canizares C., Bhattacharya K., and Vaccaro A., An affine arithmetic approach for microgrid dispatch with variable generation and load, Proceedings - 2014 Power Systems Computation Conference, PSCC 2014, Canada, 2014.

• Researchers awarded $4 million in federal funding