@misc{8ae1a4b17e474c958e6b210ec33ae8a0,
title = "Riemannian Optimization Applied to AC Optimal Power Flow",
abstract = "The nonlinear, nonconvex AC optimal power flow problem is of growing importance as the nature of the power grid evolves. This problem can be difficult to solve for interior point methods. However, the advent of optimization algorithms over smooth Riemannian manifolds presents an alternative approach. The nonlinear, nonconvex constraints in the AC power flow problem form an embedded submanifold of Euclidean space. In this paper, the authors explore the performance of Riemannian optimization algorithms for the ACOPF problem where the optimization is performed directly on the AC power flow manifold. This is done by using the Julia programming language and the Julia packages PowerModels.jl and Manopt.jl.",
keywords = "AC optimal power flow, manifold optimization, nonlinear optimization, Riemannian optimization",
author = "Jonathan Maack and Devon Sigler and Ariel Goodwin",
year = "2024",
language = "American English",
series = "Presented at the 2024 IEEE Power & Energy Society General Meeting, 21-25 July 2024, Seattle, Washington",
publisher = "National Renewable Energy Laboratory (NREL)",
address = "United States",
type = "Other",
}