Applications of Lifted Nonlinear Cuts to Convex Relaxations of the AC Power Flow Equations

Fuente: arXiv
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Autori principali: Bugosen, Sergio I., Parker, Robert B., Coffrin, Carleton
Natura: Preprint
Pubblicazione: 2024
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author Bugosen, Sergio I.
Parker, Robert B.
Coffrin, Carleton
author_facet Bugosen, Sergio I.
Parker, Robert B.
Coffrin, Carleton
contents We demonstrate that valid inequalities, or lifted nonlinear cuts (LNC), can be projected to tighten the Second Order Cone (SOC), Convex DistFlow (CDF), and Network Flow (NF) relaxations of the AC Optimal Power Flow (AC-OPF) problem. We conduct experiments on 36 cases from the PGLib-OPF library for two objective functions, (1) power generation maximization and (2) generation cost minimization. Significant optimality gap improvements are shown for the maximization problem, where the LNC strengthen the SOC and CDF relaxations in 100% of the test cases, with average and maximum differences in the optimality gaps of 23.1% and 93.5% respectively. The NF relaxation is strengthened in 79.2% of test cases, with average and maximum differences in the optimality gaps of 3.45% and 21.2% respectively. We also study the trade-off between relaxation quality and solve time, demonstrating that the strengthened CDF relaxation outperforms the strengthened SOC formulation in terms of runtime and number of iterations needed, while the strengthened NF formulation is the most scalable with the lowest relaxation quality provided by these LNC.
format Preprint
id arxiv_https___arxiv_org_abs_2404_17541
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Applications of Lifted Nonlinear Cuts to Convex Relaxations of the AC Power Flow Equations
Bugosen, Sergio I.
Parker, Robert B.
Coffrin, Carleton
Optimization and Control
Systems and Control
We demonstrate that valid inequalities, or lifted nonlinear cuts (LNC), can be projected to tighten the Second Order Cone (SOC), Convex DistFlow (CDF), and Network Flow (NF) relaxations of the AC Optimal Power Flow (AC-OPF) problem. We conduct experiments on 36 cases from the PGLib-OPF library for two objective functions, (1) power generation maximization and (2) generation cost minimization. Significant optimality gap improvements are shown for the maximization problem, where the LNC strengthen the SOC and CDF relaxations in 100% of the test cases, with average and maximum differences in the optimality gaps of 23.1% and 93.5% respectively. The NF relaxation is strengthened in 79.2% of test cases, with average and maximum differences in the optimality gaps of 3.45% and 21.2% respectively. We also study the trade-off between relaxation quality and solve time, demonstrating that the strengthened CDF relaxation outperforms the strengthened SOC formulation in terms of runtime and number of iterations needed, while the strengthened NF formulation is the most scalable with the lowest relaxation quality provided by these LNC.
title Applications of Lifted Nonlinear Cuts to Convex Relaxations of the AC Power Flow Equations
topic Optimization and Control
Systems and Control
url https://arxiv.org/abs/2404.17541