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Real-time OPF based on quasi-Newton methods

Tang, Yujie and Dvijotham, Krishnamurthy and Low, Steven (2017) Real-time OPF based on quasi-Newton methods. In: 51st Annual Conference on Information Sciences and Systems (CISS). IEEE , Piscatway, NJ. ISBN 978-1-5090-4780-2. http://resolver.caltech.edu/CaltechAUTHORS:20170517-151532951

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Abstract

Optimal power flow is a central problem in the operation of power systems. So far the majority of the literature deals with offline algorithms for traditional applications, but the proliferation of distributed energy resources and smart appliances in power networks motivates real-time and scalable algorithms. We introduce a real-time OPF algorithm based on quasi-Newton methods that can track the optimal operation when the state of the network is changing. Theory and simulations show that the proposed algorithm has guaranteed tracking performance and is computationally efficient.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://doi.org/10.1109/CISS.2017.7926163DOIAbstract
http://ieeexplore.ieee.org/document/7926163/PublisherAbstract
ORCID:
AuthorORCID
Tang, Yujie0000-0002-4921-8372
Dvijotham, Krishnamurthy0000-0002-1328-4677
Additional Information:© 2017 IEEE.
Record Number:CaltechAUTHORS:20170517-151532951
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20170517-151532951
Official Citation:Yujie Tang, K. Dvijotham and S. Low, "Real-time OPF based on quasi-Newton methods," 2017 51st Annual Conference on Information Sciences and Systems (CISS), Baltimore, MD, USA, 2017, pp. 1-1. doi: 10.1109/CISS.2017.7926163
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:77532
Collection:CaltechAUTHORS
Deposited By: Kristin Buxton
Deposited On:17 May 2017 22:44
Last Modified:03 May 2018 20:54

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