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Title: Non-Invasive Identification of Inertia Distribution Change in High Renewable Systems Using Distribution Level PMU

Abstract

Here, this letter proposed an approach to identify the change of inertia distribution in high renewable power systems. Using the footprints of electromechanical wave propagation at the distribution level, this approach provides a new and non-invasive way to aware the system inertia distribution for primary frequency response. Actual measurements and high renewable dynamic models validated effectiveness of the approach.

Authors:
ORCiD logo [1]; ORCiD logo [1];  [2];  [1];  [1];  [1]; ORCiD logo [3];  [4]
  1. Univ. of Tennessee, Knoxville, TN (United States). Dept. of Electrical Engineering and Computer Science
  2. Dominion Virginia Power, Richmond, VA (United States)
  3. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  4. Univ. of Tennessee, Knoxville, TN (United States). Dept. of Electrical Engineering and Computer Science; Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE; National Science Foundation (NSF)
OSTI Identifier:
1474558
Grant/Contract Number:  
AC05-00OR22725
Resource Type:
Accepted Manuscript
Journal Name:
IEEE Transactions on Power Systems
Additional Journal Information:
Journal Volume: 33; Journal Issue: 1; Journal ID: ISSN 0885-8950
Publisher:
IEEE
Country of Publication:
United States
Language:
English
Subject:
24 POWER TRANSMISSION AND DISTRIBUTION; Electromechanical wave propagation; inertia; renewable generation; synchrophasor measurement

Citation Formats

You, Shutang, Liu, Yong, Kou, Gefei, Zhang, Xuemeng, Yao, Wenxuan, Su, Yu, Hadley, Stanton W., and Liu, Yilu. Non-Invasive Identification of Inertia Distribution Change in High Renewable Systems Using Distribution Level PMU. United States: N. p., 2018. Web. doi:10.1109/TPWRS.2017.2713985.
You, Shutang, Liu, Yong, Kou, Gefei, Zhang, Xuemeng, Yao, Wenxuan, Su, Yu, Hadley, Stanton W., & Liu, Yilu. Non-Invasive Identification of Inertia Distribution Change in High Renewable Systems Using Distribution Level PMU. United States. doi:10.1109/TPWRS.2017.2713985.
You, Shutang, Liu, Yong, Kou, Gefei, Zhang, Xuemeng, Yao, Wenxuan, Su, Yu, Hadley, Stanton W., and Liu, Yilu. Mon . "Non-Invasive Identification of Inertia Distribution Change in High Renewable Systems Using Distribution Level PMU". United States. doi:10.1109/TPWRS.2017.2713985. https://www.osti.gov/servlets/purl/1474558.
@article{osti_1474558,
title = {Non-Invasive Identification of Inertia Distribution Change in High Renewable Systems Using Distribution Level PMU},
author = {You, Shutang and Liu, Yong and Kou, Gefei and Zhang, Xuemeng and Yao, Wenxuan and Su, Yu and Hadley, Stanton W. and Liu, Yilu},
abstractNote = {Here, this letter proposed an approach to identify the change of inertia distribution in high renewable power systems. Using the footprints of electromechanical wave propagation at the distribution level, this approach provides a new and non-invasive way to aware the system inertia distribution for primary frequency response. Actual measurements and high renewable dynamic models validated effectiveness of the approach.},
doi = {10.1109/TPWRS.2017.2713985},
journal = {IEEE Transactions on Power Systems},
number = 1,
volume = 33,
place = {United States},
year = {2018},
month = {1}
}

Journal Article:
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Cited by: 13 works
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Figures / Tables:

Fig. 1. Fig. 1.: Seasonal change of wave propagation speed distribution based on FNET/GridEye measurements ((a) 2014 winter and (b) 2014 autumn)

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    Figures/Tables have been extracted from DOE-funded journal article accepted manuscripts.