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Distributional analysis for model predictive deferrable load control

Chen, Niangjun and Gan, Lingwen and Low, Steven H. and Wierman, Adam (2014) Distributional analysis for model predictive deferrable load control. In: 53rd IEEE Conference on Decision and Control. IEEE , Piscataway, NJ, pp. 6433-6438. ISBN 978-1-4799-7746-8. http://resolver.caltech.edu/CaltechAUTHORS:20170810-105540217

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Abstract

Deferrable load control is essential for handling the uncertainties associated with the increasing penetration of renewable generation. Model predictive control has emerged as an effective approach for deferrable load control, and has received considerable attention. Though the average-case performance of model predictive deferrable load control has been analyzed in prior works, the distribution of the performance has been elusive. In this paper, we prove strong concentration results on the load variation obtained by model predictive deferrable load control. These results highlight that the typical performance of model predictive deferrable load control is tightly concentrated around the average-case performance.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://doi.org/10.1109/CDC.2014.7040398DOIArticle
https://arxiv.org/abs/1403.6887arXivDiscussion Paper
ORCID:
AuthorORCID
Chen, Niangjun0000-0002-2289-9737
Low, Steven H.0000-0001-6476-3048
Additional Information:© 2014 IEEE.
Subject Keywords:Load flow control, Load modeling, Prediction algorithms, Predictive models, Load management, Algorithm design and analysis, Analytical models
Record Number:CaltechAUTHORS:20170810-105540217
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20170810-105540217
Official Citation:N. Chen, L. Gan, S. H. Low and A. Wierman, "Distributional analysis for model predictive deferrable load control," 53rd IEEE Conference on Decision and Control, Los Angeles, CA, 2014, pp. 6433-6438. doi: 10.1109/CDC.2014.7040398 URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7040398&isnumber=7039338
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:80097
Collection:CaltechAUTHORS
Deposited By: Zhaojian Wang
Deposited On:10 Aug 2017 18:12
Last Modified:27 Jun 2019 21:46

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