@misc{c6c27ff42e8a4fc59a70ad5a8bf71c63,
title = "Scalable PETSc Implementation of the Three-Phase Unbalanced AC Power Flow Solver",
abstract = "A revolutionary transition of energy infrastructure, spanning across supply and demand sectors, is happening all around the world. Integration of renewable energy sources into our ever-complex power distribution networks is central to the infrastructure planning of the future. One step towards achieving this goal is to solve unbalanced transmission and distribution systems. Traditional approaches and software tools are not suitable because they assume a completely balanced 3-phase system, hence a single-phase equivalent can be solved. Renewable energy such as wind and solar power are intermittent and can pose a challenge when integrating into an already unbalanced power grid. Furthermore, these power grids can be quite large at scale consisting of potentially thousands of buses, which can be computationally demanding. This poster presents preliminary work on designing a robust and scalable 3-phase unbalanced AC power flow solver. The proposed power flow solver will eventually be built on top of the PETSc library and utilizes state-of-the-art parallel data structures like the DMNetwork as well as iterative solvers and preconditioners.",
keywords = "balancing, demand, energy infrastructure, power distribution networks, power grid, solar, supply, wind",
author = "Justin Chang and Gordon Stephen and Dheepak Krishnamurthy and Daniel Thom and Wesley Jones",
year = "2019",
language = "American English",
series = "Presented at the SIAM Conference on Computational Science and Engineering, 25 February - 1 March 2019, Spokane, Washington",
type = "Other",
}
