Optimization-Based Exploration of the Feasible Power Flow Space for Rapid Data Collection
Systems and Control
2024-04-23 v2 Systems and Control
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.
Cite
@article{arxiv.2206.12214,
title = {Optimization-Based Exploration of the Feasible Power Flow Space for Rapid Data Collection},
author = {Ignasi Ventura Nadal and Samuel Chevalier},
journal= {arXiv preprint arXiv:2206.12214},
year = {2024}
}