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Distributed Algorithm for Time-varying Optimal Power Flow

Tang, Yujie and Low, Steven (2017) Distributed Algorithm for Time-varying Optimal Power Flow. In: 2017 IEEE 56th Annual Conference on Decision and Control (CDC). IEEE , Piscataway, NJ, pp. 3264-3270. ISBN 978-1-5090-2874-0. http://resolver.caltech.edu/CaltechAUTHORS:20180126-083431585

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Abstract

Future power system applications may require real-time optimization of a large network of distributed energy resources. This has motivated recent development of online algorithms for solving time-varying optimal power flow problems. We have proposed a centralized quasi-Newton algorithm and have derived theoretical guarantees for its tracking performance. In this paper we show how this algorithm can be implemented in a distributed manner by a network of controllable energy resources coordinated by an operator. The proposed distributed implementation now can handle general convex quadratic constraints on power injections, and only requires minimal communication between the operator and local controllers. Simulation shows that the proposed distributed implementation has good performance.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1109/CDC.2017.8264138DOIArticle
http://ieeexplore.ieee.org/document/8264138/PublisherArticle
ORCID:
AuthorORCID
Tang, Yujie0000-0002-4921-8372
Low, Steven0000-0001-6476-3048
Additional Information:© 2017 IEEE. Date Added to IEEE Xplore: 23 January 2018. This work was supported by NSF through grants CCF 1637598, ECCS 1619352 and CNS 1545096, ARPA-E through grant DE-AR0000699 and the GRID DATA program, and DTRA through grant HDTRA 1-15-1-0003.
Funders:
Funding AgencyGrant Number
NSFCCF-1637598
NSFECCS-1619352
NSFCNS-1545096
Advanced Research Projects Agency-Energy (ARPA-E)DE-AR0000699
Defense Threat Reduction Agency (DTRA)HDTRA 1-15-1-0003
Record Number:CaltechAUTHORS:20180126-083431585
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20180126-083431585
Official Citation:Y. Tang and S. Low, "Distributed algorithm for time-varying optimal power flow," 2017 IEEE 56th Annual Conference on Decision and Control (CDC), Melbourne, Australia, 2017, pp. 3264-3270. doi: 10.1109/CDC.2017.8264138
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:84537
Collection:CaltechAUTHORS
Deposited By: Ruth Sustaita
Deposited On:31 Jan 2018 00:48
Last Modified:31 Jan 2018 00:48

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