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Nonlinear Optimization for Optimal Power Flow Problems
Elizabeth Wong
UCSD
Abstract:
In this talk, we present an algorithm created for Challenge 2 of the Grid Optimization Competition from ARPA-E (Advanced Research Projects Agency–Energy). The competition considered a security constrained optimal power flow (SCOPF) problem whose solution determines optimal dispatch and control settings for power generation and grid control equipment and maximizes the market surplus associated with the operation of the grid, subject to pre- and post-contingency constraints. We will discuss the practical issues associated with the challenge and describe the approach and heuristics established to enhance performance of the algorithm submitted to the competition. Results from the competition will also be presented. This is joint work with Frank E. Curtis (Lehigh University), Daniel Molzahn (Georgia Tech), Andreas Wächter and Ermin Wei (Northwestern University).
Tuesday, November 16, 2021
11:00AM Zoom ID 970 1854 2148
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Randolph E. Bank
Philip E. Gill
Michael Holst
Administrative Contact:
[ Click to Send Email ]
Elizabeth Wong
UCSD
Abstract:
In this talk, we present an algorithm created for Challenge 2 of the Grid Optimization Competition from ARPA-E (Advanced Research Projects Agency–Energy). The competition considered a security constrained optimal power flow (SCOPF) problem whose solution determines optimal dispatch and control settings for power generation and grid control equipment and maximizes the market surplus associated with the operation of the grid, subject to pre- and post-contingency constraints. We will discuss the practical issues associated with the challenge and describe the approach and heuristics established to enhance performance of the algorithm submitted to the competition. Results from the competition will also be presented. This is joint work with Frank E. Curtis (Lehigh University), Daniel Molzahn (Georgia Tech), Andreas Wächter and Ermin Wei (Northwestern University).
Tuesday, November 16, 2021
11:00AM Zoom ID 970 1854 2148