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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2022
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2206.12214 |
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| _version_ | 1866909175946149888 |
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| author | Nadal, Ignasi Ventura Chevalier, Samuel |
| author_facet | Nadal, Ignasi Ventura Chevalier, Samuel |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2206_12214 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Optimization-Based Exploration of the Feasible Power Flow Space for Rapid Data Collection Nadal, Ignasi Ventura Chevalier, Samuel Systems and Control 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. |
| title | Optimization-Based Exploration of the Feasible Power Flow Space for Rapid Data Collection |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2206.12214 |