Probabilistic Voltage Stability Analysis Based on Unscented Transformation and Maximum Entropy Principle

Zhang Jianfen; Tse Chitong; Liu Yi; Wang Kewen

doi:doi:10.11648/j.epes.20160506.14

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Probabilistic Voltage Stability Analysis Based on Unscented Transformation and Maximum Entropy Principle

Zhang Jianfen, Tse Chitong, Liu Yi, Wang Kewen

Published in American Journal of Electrical Power and Energy Systems (Volume 5, Issue 6)

Received: 11 November 2016 Accepted: 28 November 2016 Published: 6 January 2017

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Abstract

Considering the uncertainty of load and the random variation of wind farm output power in power system, a probabilistic voltage stability analysis method is proposed based on unscented transformation technique. According to the statistical characteristics of random variables in power system, the statistical characteristics of voltage stability margins, such as mean, standard deviation and moments, can be calculated by using a small number of samples and the conventional method. The maximum entropy method is applied to determine the probability distribution of voltage stability margin. In compared with Monte Carlo method, the effectiveness of the proposed method is verified on 39-bus and IEEE 57-bus system. The results show that the proposed method can accurately compute the statistical characteristics and the probability distribution of the voltage stability margin, and the computational efficiency is improved.

Published in	American Journal of Electrical Power and Energy Systems (Volume 5, Issue 6)
DOI	10.11648/j.epes.20160506.14
Page(s)	81-90
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2017. Published by Science Publishing Group

Keywords

Voltage Stability, Probabilistic Voltage Stability Margin, Unscented Transformation Technique, Sigma Points, Maximum Entropy Principle

References

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APA Style

Zhang Jianfen, Tse Chitong, Liu Yi, Wang Kewen. (2017). Probabilistic Voltage Stability Analysis Based on Unscented Transformation and Maximum Entropy Principle. American Journal of Electrical Power and Energy Systems, 5(6), 81-90. https://doi.org/10.11648/j.epes.20160506.14

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ACS Style

Zhang Jianfen; Tse Chitong; Liu Yi; Wang Kewen. Probabilistic Voltage Stability Analysis Based on Unscented Transformation and Maximum Entropy Principle. Am. J. Electr. Power Energy Syst. 2017, 5(6), 81-90. doi: 10.11648/j.epes.20160506.14

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AMA Style

Zhang Jianfen, Tse Chitong, Liu Yi, Wang Kewen. Probabilistic Voltage Stability Analysis Based on Unscented Transformation and Maximum Entropy Principle. Am J Electr Power Energy Syst. 2017;5(6):81-90. doi: 10.11648/j.epes.20160506.14

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@article{10.11648/j.epes.20160506.14,
  author = {Zhang Jianfen and Tse Chitong and Liu Yi and Wang Kewen},
  title = {Probabilistic Voltage Stability Analysis Based on Unscented Transformation and Maximum Entropy Principle},
  journal = {American Journal of Electrical Power and Energy Systems},
  volume = {5},
  number = {6},
  pages = {81-90},
  doi = {10.11648/j.epes.20160506.14},
  url = {https://doi.org/10.11648/j.epes.20160506.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.epes.20160506.14},
  abstract = {Considering the uncertainty of load and the random variation of wind farm output power in power system, a probabilistic voltage stability analysis method is proposed based on unscented transformation technique. According to the statistical characteristics of random variables in power system, the statistical characteristics of voltage stability margins, such as mean, standard deviation and moments, can be calculated by using a small number of samples and the conventional method. The maximum entropy method is applied to determine the probability distribution of voltage stability margin. In compared with Monte Carlo method, the effectiveness of the proposed method is verified on 39-bus and IEEE 57-bus system. The results show that the proposed method can accurately compute the statistical characteristics and the probability distribution of the voltage stability margin, and the computational efficiency is improved.},
 year = {2017}
}

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TY  - JOUR
T1  - Probabilistic Voltage Stability Analysis Based on Unscented Transformation and Maximum Entropy Principle
AU  - Zhang Jianfen
AU  - Tse Chitong
AU  - Liu Yi
AU  - Wang Kewen
Y1  - 2017/01/06
PY  - 2017
N1  - https://doi.org/10.11648/j.epes.20160506.14
DO  - 10.11648/j.epes.20160506.14
T2  - American Journal of Electrical Power and Energy Systems
JF  - American Journal of Electrical Power and Energy Systems
JO  - American Journal of Electrical Power and Energy Systems
SP  - 81
EP  - 90
PB  - Science Publishing Group
SN  - 2326-9200
UR  - https://doi.org/10.11648/j.epes.20160506.14
AB  - Considering the uncertainty of load and the random variation of wind farm output power in power system, a probabilistic voltage stability analysis method is proposed based on unscented transformation technique. According to the statistical characteristics of random variables in power system, the statistical characteristics of voltage stability margins, such as mean, standard deviation and moments, can be calculated by using a small number of samples and the conventional method. The maximum entropy method is applied to determine the probability distribution of voltage stability margin. In compared with Monte Carlo method, the effectiveness of the proposed method is verified on 39-bus and IEEE 57-bus system. The results show that the proposed method can accurately compute the statistical characteristics and the probability distribution of the voltage stability margin, and the computational efficiency is improved.
VL  - 5
IS  - 6
ER  -

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Author Information

Zhang Jianfen

Electrical and Information College of Jinan University, Zhuhai, China
Tse Chitong

IEEE (HK) PES/IAS/PELS/IES Joint Chapter, Hong Kong, China
Liu Yi

State Grid East China Control Center, Shanghai, China
Wang Kewen

School of Electrical Engineering, Zhengzhou University, Zhengzhou, China

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Plain Text BibTeX RIS

APA Style

Zhang Jianfen, Tse Chitong, Liu Yi, Wang Kewen. (2017). Probabilistic Voltage Stability Analysis Based on Unscented Transformation and Maximum Entropy Principle. American Journal of Electrical Power and Energy Systems, 5(6), 81-90. https://doi.org/10.11648/j.epes.20160506.14

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ACS Style

Zhang Jianfen; Tse Chitong; Liu Yi; Wang Kewen. Probabilistic Voltage Stability Analysis Based on Unscented Transformation and Maximum Entropy Principle. Am. J. Electr. Power Energy Syst. 2017, 5(6), 81-90. doi: 10.11648/j.epes.20160506.14

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AMA Style

Zhang Jianfen, Tse Chitong, Liu Yi, Wang Kewen. Probabilistic Voltage Stability Analysis Based on Unscented Transformation and Maximum Entropy Principle. Am J Electr Power Energy Syst. 2017;5(6):81-90. doi: 10.11648/j.epes.20160506.14

Copy | Download

@article{10.11648/j.epes.20160506.14,
  author = {Zhang Jianfen and Tse Chitong and Liu Yi and Wang Kewen},
  title = {Probabilistic Voltage Stability Analysis Based on Unscented Transformation and Maximum Entropy Principle},
  journal = {American Journal of Electrical Power and Energy Systems},
  volume = {5},
  number = {6},
  pages = {81-90},
  doi = {10.11648/j.epes.20160506.14},
  url = {https://doi.org/10.11648/j.epes.20160506.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.epes.20160506.14},
  abstract = {Considering the uncertainty of load and the random variation of wind farm output power in power system, a probabilistic voltage stability analysis method is proposed based on unscented transformation technique. According to the statistical characteristics of random variables in power system, the statistical characteristics of voltage stability margins, such as mean, standard deviation and moments, can be calculated by using a small number of samples and the conventional method. The maximum entropy method is applied to determine the probability distribution of voltage stability margin. In compared with Monte Carlo method, the effectiveness of the proposed method is verified on 39-bus and IEEE 57-bus system. The results show that the proposed method can accurately compute the statistical characteristics and the probability distribution of the voltage stability margin, and the computational efficiency is improved.},
 year = {2017}
}

Copy | Download

TY  - JOUR
T1  - Probabilistic Voltage Stability Analysis Based on Unscented Transformation and Maximum Entropy Principle
AU  - Zhang Jianfen
AU  - Tse Chitong
AU  - Liu Yi
AU  - Wang Kewen
Y1  - 2017/01/06
PY  - 2017
N1  - https://doi.org/10.11648/j.epes.20160506.14
DO  - 10.11648/j.epes.20160506.14
T2  - American Journal of Electrical Power and Energy Systems
JF  - American Journal of Electrical Power and Energy Systems
JO  - American Journal of Electrical Power and Energy Systems
SP  - 81
EP  - 90
PB  - Science Publishing Group
SN  - 2326-9200
UR  - https://doi.org/10.11648/j.epes.20160506.14
AB  - Considering the uncertainty of load and the random variation of wind farm output power in power system, a probabilistic voltage stability analysis method is proposed based on unscented transformation technique. According to the statistical characteristics of random variables in power system, the statistical characteristics of voltage stability margins, such as mean, standard deviation and moments, can be calculated by using a small number of samples and the conventional method. The maximum entropy method is applied to determine the probability distribution of voltage stability margin. In compared with Monte Carlo method, the effectiveness of the proposed method is verified on 39-bus and IEEE 57-bus system. The results show that the proposed method can accurately compute the statistical characteristics and the probability distribution of the voltage stability margin, and the computational efficiency is improved.
VL  - 5
IS  - 6
ER  -

Copy | Download