extended-abstract

Distributed Lagrangian Method for Tie-Line Scheduling in Power Grids under Uncertainty

Authors:

Thinh T. Doan,

Subhonmesh Bose,

Carolyn L. BeckAuthors Info & Claims

ACM SIGMETRICS Performance Evaluation Review, Volume 45, Issue 2

Pages 88 - 90

https://doi.org/10.1145/3152042.3152069

Published: 11 October 2017 Publication History

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Abstract

System operators (SOs) manage the grid and its assets in different parts (areas) of an interconnected power network. One would ideally seek to co-optimize the grid assets across multiple areas by solving a centralized optimization problem. Gathering the dispatch cost structures and the network constraints from all areas for a centralized solution remains difficult due to technical, historical, and sometimes legal barriers. Motivated by the need for a distributed solution architecture for multi-area power systems, we propose a distributed Lagrangian algorithm in this paper.We establish convergence rates for our algorithm that solves the deterministic tie-line scheduling problem as well as its robust variant (with policy space approximations). Our algorithm does not need any form of central coordination. We illustrate its efficacy on IEEE test systems.

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Cited By

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Huang FChi WYao LYu JLi Y(2023)Reconstruction Optimization of Economic Operation of Distribution Network Based on Data Mining Algorithm2023 IEEE 4th Annual Flagship India Council International Subsections Conference (INDISCON)10.1109/INDISCON58499.2023.10269804(01-06)Online publication date: 5-Aug-2023
https://doi.org/10.1109/INDISCON58499.2023.10269804
Doan TBeck C(2021)Distributed Resource Allocation Over Dynamic Networks With UncertaintyIEEE Transactions on Automatic Control10.1109/TAC.2020.304124866:9(4378-4384)Online publication date: Sep-2021
https://doi.org/10.1109/TAC.2020.3041248
Doan TBose SNguyen DBeck C(2019)Convergence of the Iterates in Mirror Descent MethodsIEEE Control Systems Letters10.1109/LCSYS.2018.28548893:1(114-119)Online publication date: Jan-2019
https://doi.org/10.1109/LCSYS.2018.2854889
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Distributed Lagrangian Method for Tie-Line Scheduling in Power Grids under Uncertainty
1. Theory of computation
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Information

Published In

cover image ACM SIGMETRICS Performance Evaluation Review

ACM SIGMETRICS Performance Evaluation Review Volume 45, Issue 2

Setember 2017

131 pages

ISSN:0163-5999

DOI:10.1145/3152042

Editor:
Nidhi Hegde
Bell Labs, Nokia, Nozay, France

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Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 11 October 2017

Published in SIGMETRICS Volume 45, Issue 2

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Cited By

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Huang FChi WYao LYu JLi Y(2023)Reconstruction Optimization of Economic Operation of Distribution Network Based on Data Mining Algorithm2023 IEEE 4th Annual Flagship India Council International Subsections Conference (INDISCON)10.1109/INDISCON58499.2023.10269804(01-06)Online publication date: 5-Aug-2023
https://doi.org/10.1109/INDISCON58499.2023.10269804
Doan TBeck C(2021)Distributed Resource Allocation Over Dynamic Networks With UncertaintyIEEE Transactions on Automatic Control10.1109/TAC.2020.304124866:9(4378-4384)Online publication date: Sep-2021
https://doi.org/10.1109/TAC.2020.3041248
Doan TBose SNguyen DBeck C(2019)Convergence of the Iterates in Mirror Descent MethodsIEEE Control Systems Letters10.1109/LCSYS.2018.28548893:1(114-119)Online publication date: Jan-2019
https://doi.org/10.1109/LCSYS.2018.2854889
Doan TBeck CSrikant R(2018)Convergence Rate of Distributed Consensus with Nonuniform Delays2018 52nd Asilomar Conference on Signals, Systems, and Computers10.1109/ACSSC.2018.8645450(1294-1298)Online publication date: Oct-2018
https://doi.org/10.1109/ACSSC.2018.8645450

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De-centralized job scheduling on computational Grids using distributed backfilling: Research Articles

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