Anderson, James and Zhou, Fengyu and Low, Steven H. (2020) Worst-Case Sensitivity of DC Optimal Power Flow Problems. In: 2020 American Control Conference (ACC). IEEE , Piscataway, NJ, pp. 3156-3163. ISBN 9781538682661. https://resolver.caltech.edu/CaltechAUTHORS:20200707-112527402
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Abstract
In this paper we consider the problem of analyzing the effect a change in the load vector can have on the optimal power generation in a DC power flow model. The methodology is based upon the recently introduced concept of the OPF operator. It is shown that for general network topologies computing the worst-case sensitivities is computationally intractable. However, we show that certain problems involving the OPF operator can be equivalently converted to a graphical discrete optimization problem. Using the discrete formulation, we provide a decomposition algorithm that reduces the computational cost of computing the worst-case sensitivity. A 27-bus numerical example is used to illustrate our results.
Item Type: | Book Section | ||||||||||||
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Additional Information: | © 2020 AACC. This work is funded by NSF grants CCF 1637598, ECCS 1619352, CNS 1545096, ARPA-E through grant DE-AR0000699 and the GRID DATA program, and DTRA through grant HDTRA 1-15-1-0003. | ||||||||||||
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DOI: | 10.23919/ACC45564.2020.9147770 | ||||||||||||
Record Number: | CaltechAUTHORS:20200707-112527402 | ||||||||||||
Persistent URL: | https://resolver.caltech.edu/CaltechAUTHORS:20200707-112527402 | ||||||||||||
Official Citation: | J. Anderson, F. Zhou and S. H. Low, "Worst-Case Sensitivity of DC Optimal Power Flow Problems," 2020 American Control Conference (ACC), Denver, CO, USA, 2020, pp. 3156-3163, doi: 10.23919/ACC45564.2020.9147770 | ||||||||||||
Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. | ||||||||||||
ID Code: | 104250 | ||||||||||||
Collection: | CaltechAUTHORS | ||||||||||||
Deposited By: | Tony Diaz | ||||||||||||
Deposited On: | 07 Jul 2020 18:42 | ||||||||||||
Last Modified: | 16 Nov 2021 18:29 |
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