Towards Efficient Alternating Current Optimal Power Flow Analysis on Graphical Processing Units

Kasia Swirydowicz; Nicholson Koukpaizan; Shrirang Abhyankar; Slaven Peles

doi:10.1109/ICAT57854.2023.10171317

Towards Efficient Alternating Current Optimal Power Flow Analysis on Graphical Processing Units

Kasia Swirydowicz, Nicholson Koukpaizan, Shrirang Abhyankar, Slaven Peles

Advanced Computing for Life Sciences and

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

We present a solution of sparse alternating current optimal power flow (ACOPF) analysis on graphical processing unit (GPU). In particular, we discuss the performance bottlenecks and detail our efforts to accelerate the linear solver, a core component of ACOPF that dominates the computational time. ACOPF analyses of two large-scale systems, synthetic Northeast (25,000 buses) and Eastern (70,000 buses) U.S. grids [1], on GPU show promising speed-up compared to analyses on central processing unit (CPU) using a state-of-the-art solver. To our knowledge, this is the first result demonstrating a significant acceleration of sparse ACOPF on GPUs.

Original language	English
Title of host publication	2023 29th International Conference on Information, Communication and Automation Technologies, ICAT 2023 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350399837
DOIs	https://doi.org/10.1109/ICAT57854.2023.10171317
State	Published - 2023
Event	29th International Conference on Information, Communication and Automation Technologies, ICAT 2023 - Sarajevo, Bosnia and Herzegovina Duration: Jun 11 2023 → Jun 14 2023

Publication series

Name	2023 29th International Conference on Information, Communication and Automation Technologies, ICAT 2023 - Proceedings

Conference

Conference	29th International Conference on Information, Communication and Automation Technologies, ICAT 2023
Country/Territory	Bosnia and Herzegovina
City	Sarajevo
Period	06/11/23 → 06/14/23

Funding

This research was supported by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of the U.S. Department of Energy Office of Science and the National Nuclear Security Administration. This research used resources of the Oak Ridge Leadership Computing Facility, which is supported by the U.S. Department of Energy Office of Science under Contract No. DE-AC05-00OR22725.

Keywords

ACOPF
GPU
economic dispatch
heterogeneous computing
opti-mization
sparse solvers

Access to Document

10.1109/ICAT57854.2023.10171317

Cite this

Swirydowicz, K., Koukpaizan, N., Abhyankar, S., & Peles, S. (2023). Towards Efficient Alternating Current Optimal Power Flow Analysis on Graphical Processing Units. In 2023 29th International Conference on Information, Communication and Automation Technologies, ICAT 2023 - Proceedings (2023 29th International Conference on Information, Communication and Automation Technologies, ICAT 2023 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICAT57854.2023.10171317

Swirydowicz, Kasia ; Koukpaizan, Nicholson ; Abhyankar, Shrirang et al. / Towards Efficient Alternating Current Optimal Power Flow Analysis on Graphical Processing Units. 2023 29th International Conference on Information, Communication and Automation Technologies, ICAT 2023 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 29th International Conference on Information, Communication and Automation Technologies, ICAT 2023 - Proceedings).

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abstract = "We present a solution of sparse alternating current optimal power flow (ACOPF) analysis on graphical processing unit (GPU). In particular, we discuss the performance bottlenecks and detail our efforts to accelerate the linear solver, a core component of ACOPF that dominates the computational time. ACOPF analyses of two large-scale systems, synthetic Northeast (25,000 buses) and Eastern (70,000 buses) U.S. grids [1], on GPU show promising speed-up compared to analyses on central processing unit (CPU) using a state-of-the-art solver. To our knowledge, this is the first result demonstrating a significant acceleration of sparse ACOPF on GPUs.",

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author = "Kasia Swirydowicz and Nicholson Koukpaizan and Shrirang Abhyankar and Slaven Peles",

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year = "2023",

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language = "English",

series = "2023 29th International Conference on Information, Communication and Automation Technologies, ICAT 2023 - Proceedings",

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Swirydowicz, K, Koukpaizan, N, Abhyankar, S & Peles, S 2023, Towards Efficient Alternating Current Optimal Power Flow Analysis on Graphical Processing Units. in 2023 29th International Conference on Information, Communication and Automation Technologies, ICAT 2023 - Proceedings. 2023 29th International Conference on Information, Communication and Automation Technologies, ICAT 2023 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 29th International Conference on Information, Communication and Automation Technologies, ICAT 2023, Sarajevo, Bosnia and Herzegovina, 06/11/23. https://doi.org/10.1109/ICAT57854.2023.10171317

Towards Efficient Alternating Current Optimal Power Flow Analysis on Graphical Processing Units. / Swirydowicz, Kasia; Koukpaizan, Nicholson; Abhyankar, Shrirang et al.
2023 29th International Conference on Information, Communication and Automation Technologies, ICAT 2023 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 29th International Conference on Information, Communication and Automation Technologies, ICAT 2023 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Abhyankar, Shrirang

AU - Peles, Slaven

PY - 2023

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N2 - We present a solution of sparse alternating current optimal power flow (ACOPF) analysis on graphical processing unit (GPU). In particular, we discuss the performance bottlenecks and detail our efforts to accelerate the linear solver, a core component of ACOPF that dominates the computational time. ACOPF analyses of two large-scale systems, synthetic Northeast (25,000 buses) and Eastern (70,000 buses) U.S. grids [1], on GPU show promising speed-up compared to analyses on central processing unit (CPU) using a state-of-the-art solver. To our knowledge, this is the first result demonstrating a significant acceleration of sparse ACOPF on GPUs.

AB - We present a solution of sparse alternating current optimal power flow (ACOPF) analysis on graphical processing unit (GPU). In particular, we discuss the performance bottlenecks and detail our efforts to accelerate the linear solver, a core component of ACOPF that dominates the computational time. ACOPF analyses of two large-scale systems, synthetic Northeast (25,000 buses) and Eastern (70,000 buses) U.S. grids [1], on GPU show promising speed-up compared to analyses on central processing unit (CPU) using a state-of-the-art solver. To our knowledge, this is the first result demonstrating a significant acceleration of sparse ACOPF on GPUs.

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KW - GPU

KW - economic dispatch

KW - heterogeneous computing

KW - opti-mization

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Swirydowicz K, Koukpaizan N, Abhyankar S, Peles S. Towards Efficient Alternating Current Optimal Power Flow Analysis on Graphical Processing Units. In 2023 29th International Conference on Information, Communication and Automation Technologies, ICAT 2023 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2023. (2023 29th International Conference on Information, Communication and Automation Technologies, ICAT 2023 - Proceedings). doi: 10.1109/ICAT57854.2023.10171317

Towards Efficient Alternating Current Optimal Power Flow Analysis on Graphical Processing Units

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