Optimization-Based Exploration of the Feasible Power Flow Space for Rapid Data Collection

Ignasi Ventura Nadal; Samuel Chevalier

doi:10.1109/SmartGridComm52983.2022.9960969

Optimization-Based Exploration of the Feasible Power Flow Space for Rapid Data Collection

Ignasi Ventura Nadal
, Samuel Chevalier

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Abstract

This paper provides a systematic investigation into the various nonlinear objective functions which can be used to explore the feasible space associated with the optimal power flow problem. A total of 40 nonlinear objective functions are tested, and their results are compared to the data generated by a novel exhaustive rejection sampling routine. The Hausdorff distance, which is a min-max set dissimilarity metric, is then used to assess how well each nonlinear objective function performed (i.e., how well the tested objective functions were able to explore the non-convex power flow space). Exhaustive test results were collected from five PGLib test-cases and systematically analyzed.

Original language	English
Title of host publication	Proceedings of 2022 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)
Number of pages	6
Publisher	IEEE
Publication date	2022
Pages	347-352
ISBN (Electronic)	978-1-6654-3254-2
DOIs	https://doi.org/10.1109/SmartGridComm52983.2022.9960969
Publication status	Published - 2022
Event	2022 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids - Singapore, Singapore Duration: 25 Oct 2022 → 28 Oct 2022

Conference

Conference	2022 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids
Country/Territory	Singapore
City	Singapore
Period	25/10/2022 → 28/10/2022

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10.1109/SmartGridComm52983.2022.9960969

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title = "Optimization-Based Exploration of the Feasible Power Flow Space for Rapid Data Collection",

abstract = "This paper provides a systematic investigation into the various nonlinear objective functions which can be used to explore the feasible space associated with the optimal power flow problem. A total of 40 nonlinear objective functions are tested, and their results are compared to the data generated by a novel exhaustive rejection sampling routine. The Hausdorff distance, which is a min-max set dissimilarity metric, is then used to assess how well each nonlinear objective function performed (i.e., how well the tested objective functions were able to explore the non-convex power flow space). Exhaustive test results were collected from five PGLib test-cases and systematically analyzed.",

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note = "2022 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm ; Conference date: 25-10-2022 Through 28-10-2022",

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Nadal, IV & Chevalier, S 2022, Optimization-Based Exploration of the Feasible Power Flow Space for Rapid Data Collection. in Proceedings of 2022 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm). IEEE, pp. 347-352, 2022 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, Singapore, Singapore, 25/10/2022. https://doi.org/10.1109/SmartGridComm52983.2022.9960969

Optimization-Based Exploration of the Feasible Power Flow Space for Rapid Data Collection. / Nadal, Ignasi Ventura; Chevalier, Samuel.
Proceedings of 2022 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm). IEEE, 2022. p. 347-352.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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Optimization-Based Exploration of the Feasible Power Flow Space for Rapid Data Collection

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