Investigation of Nigerian 330 Kv Electrical Network with Distributed Generation Penetration – Part III: Deterministic and Probabilistic Analyses.

Funso K. Ariyo

doi:doi:10.11648/j.epes.20130201.12

| Peer-Reviewed

Investigation of Nigerian 330 Kv Electrical Network with Distributed Generation Penetration – Part III: Deterministic and Probabilistic Analyses.

Funso K. Ariyo

Published in American Journal of Electrical Power and Energy Systems (Volume 2, Issue 1)

Published: 10 January 2013

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

Abstract

The concluding part of this work (Part III) presents the non-probabilistic (deterministic) assessment of failure effects under given contingencies and reliability analysis is an automation and probabilistic extension of contingency evaluation. Also, PowerFactory generation adequacy tool is design specifically for testing of system adequacy using Monte-Carlo method. Running adequacy analysis produces convergence plots, distribution plots and Monte-Carlo draw plots. PowerFactory’s contingency analysis module offers two distinct contingency analysis methods: single time phase and multiple time phase contingency analysis, while an analytical assessment of the network reliability indices is initiated by the following actions (failure modeling, load modeling, system state production, failure effect analysis (FEA), statistical analysis and reporting) within PowerFactory. Lastly, voltage sag analysis is a calculation that assesses the expected frequency of voltage sags within a network.

Published in	American Journal of Electrical Power and Energy Systems (Volume 2, Issue 1)
DOI	10.11648/j.epes.20130201.12
Page(s)	7-22
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), 2013. Published by Science Publishing Group

Keywords

Deterministic, Assessment, Probabilistic, Contingencies, Generation Adequacy, Monte-Carlo Method, Relia-bility, Failure, Failure Effect Analysis, Statistical Analysis, Voltage Sag, Powerfactory

References

[1]	DIgSILENT PowerFactory Version 14.1 Tutorial, DIgSI-LENT GmbH Heinrich-Hertz-StraBe 9, 72810 Gomaringen, Germany, May, 2011.
[2]	D’Annunzio C., "Generation Adequacy Assessment of Power Systems with Significant Wind Generation: A System Planning and Operations Perspective", Unpublished Thesis, the University of Texas at Austin, 2009.
[3]	Hegazy Y. G., M. M. A. Salama and A. Y. Chikhani, "Ade-quacy Assessment of Distributed Generation Systems Using Monte Carlo Simulation", Proc. IEEE Transaction on Power Systems, Vol. 18, No 1, February, 2003.
[4]	Amjady N. ‘Generation Adequacy Assessment of Power Systems by Time Series and Fuzzy Neural Network’, IEEE Transactions on Power Systems, Vol. 21, No. 3, August 2006.
[5]	http://www.ece.tamu.edu/People/bios/singh/coursenotes/ part2.pdf.
[6]	Chen Q. and McCalley J., "Identifying high risk N ¡ k con-tingencies for online security assessment," IEEE Transactions on Power Systems, vol. 20, no. 2, pp. 823–834, May 2005.
[7]	V. Donde, V. L´opez, B. C. Lesieutre, A. Pinar, C. Yang, and J. Meza, "Identification of severe multiple contingencies in electric power networks," in Proceedings of the North American Power Symposium, Ames, IA, October 2005.
[8]	Z. Feng, V. Ajjarapu, and D. Maratukulam, "A practical minimum load shedding strategy to mitigate voltage ollapse," IEEE Transactions on Power Systems, vol. 13, no. 4, pp. 1285–1291, November 1998.
[9]	Zhu D. ‘Power System Reliability Analysis with Distributed Generators’ Unpublished M.Sc. Thesis, Virginia Polytechnic Institute and State University, Blacksburg, VA, U.S.A., May, 2003.
[10]	Wangdee W. ‘Bulk Electric System Reliability Simulation and Application’, Unpublished PhD Thesis, University of Saskatchewan, Saskatoon, December 2005.
[11]	Xie Z., Manimaran G., Vittal V., Phadke A. G., and Centeno V., ‘An Information Architecture for Future Power Systems and Its Reliability Analysis’, IEEE Transactions on Power Systems, Vol. 17, No. 3, August 2002.
[12]	http://triton.elk.itu.edu.tr/~ozdemir/rel.pdf.
[13]	Lamoree, J., Smith, J. C., Vinett, P., Duffy, T., and Klein, M., "The Impact of Voltage Sags on Industrial Plant Loads." Paper presented at the First International Conference on Power Quality: End-Use Applications and Perspectives, Paris, France, October 14-16, 1991.
[14]	Conrad L., Little K., and Grigg C., ‘Predicting and Preventing Problems Associated with Remote Fault-Clearing Voltage Dips," IEEE Transactions on Industry Applications, vol. 27, pp. 167-172, Jan. 1991.
[15]	Eddy C. Aeloíza, Prasad N. Enjeti, Luis A. Morán, Oscar C. Montero-Hernandez, and Sangsun Kim ‘Analysis and Design of a New Voltage Sag Compensator for Critical Loads in Electrical Power Distribution Systems’, IEEE Transactions On Industry Applications, Vol. 39, No. 4, July/August 2003.
[16]	Pirjo Heine, and Matti Lehtonen ‘Voltage Sag Distributions Caused by Power System Faults’, IEEE Transactions on Power Systems, Vol. 18, No. 4, November 2003.
[17]	Murta-Vale M.H., Campici P., Menezes T.V., Visacro S. and Nietzsch-Dias R. ‘Power System Expansion Planning: Ap-plying LLS Data to Evaluate Lightning-Related Voltage Sags’, 19th International Lightning Detection Conference, Tucson, Arizona, U.S.A., 24th – 25th April, 2006.19th International Lightning Detection Conference.

Cite This Article

Plain Text BibTeX RIS

APA Style

Funso K. Ariyo. (2013). Investigation of Nigerian 330 Kv Electrical Network with Distributed Generation Penetration – Part III: Deterministic and Probabilistic Analyses.. American Journal of Electrical Power and Energy Systems, 2(1), 7-22. https://doi.org/10.11648/j.epes.20130201.12

Copy | Download

ACS Style

Funso K. Ariyo. Investigation of Nigerian 330 Kv Electrical Network with Distributed Generation Penetration – Part III: Deterministic and Probabilistic Analyses.. Am. J. Electr. Power Energy Syst. 2013, 2(1), 7-22. doi: 10.11648/j.epes.20130201.12

Copy | Download

AMA Style

Funso K. Ariyo. Investigation of Nigerian 330 Kv Electrical Network with Distributed Generation Penetration – Part III: Deterministic and Probabilistic Analyses.. Am J Electr Power Energy Syst. 2013;2(1):7-22. doi: 10.11648/j.epes.20130201.12

Copy | Download

@article{10.11648/j.epes.20130201.12,
  author = {Funso K. Ariyo},
  title = {Investigation of Nigerian 330 Kv Electrical Network with Distributed Generation Penetration – Part III: Deterministic and Probabilistic Analyses.},
  journal = {American Journal of Electrical Power and Energy Systems},
  volume = {2},
  number = {1},
  pages = {7-22},
  doi = {10.11648/j.epes.20130201.12},
  url = {https://doi.org/10.11648/j.epes.20130201.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.epes.20130201.12},
  abstract = {The concluding part of this work (Part III) presents the non-probabilistic (deterministic) assessment of failure effects under given contingencies and reliability analysis is an automation and probabilistic extension of contingency evaluation. Also, PowerFactory generation adequacy tool is design specifically for testing of system adequacy using Monte-Carlo method. Running adequacy analysis produces convergence plots, distribution plots and Monte-Carlo draw plots. PowerFactory’s contingency analysis module offers two distinct contingency analysis methods: single time phase and multiple time phase contingency analysis, while an analytical assessment of the network reliability indices is initiated by the following actions (failure modeling, load modeling, system state production, failure effect analysis (FEA), statistical analysis and reporting) within PowerFactory. Lastly, voltage sag analysis is a calculation that assesses the expected frequency of voltage sags within a network.},
 year = {2013}
}

Copy | Download

TY  - JOUR
T1  - Investigation of Nigerian 330 Kv Electrical Network with Distributed Generation Penetration – Part III: Deterministic and Probabilistic Analyses.
AU  - Funso K. Ariyo
Y1  - 2013/01/10
PY  - 2013
N1  - https://doi.org/10.11648/j.epes.20130201.12
DO  - 10.11648/j.epes.20130201.12
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  - 7
EP  - 22
PB  - Science Publishing Group
SN  - 2326-9200
UR  - https://doi.org/10.11648/j.epes.20130201.12
AB  - The concluding part of this work (Part III) presents the non-probabilistic (deterministic) assessment of failure effects under given contingencies and reliability analysis is an automation and probabilistic extension of contingency evaluation. Also, PowerFactory generation adequacy tool is design specifically for testing of system adequacy using Monte-Carlo method. Running adequacy analysis produces convergence plots, distribution plots and Monte-Carlo draw plots. PowerFactory’s contingency analysis module offers two distinct contingency analysis methods: single time phase and multiple time phase contingency analysis, while an analytical assessment of the network reliability indices is initiated by the following actions (failure modeling, load modeling, system state production, failure effect analysis (FEA), statistical analysis and reporting) within PowerFactory. Lastly, voltage sag analysis is a calculation that assesses the expected frequency of voltage sags within a network.
VL  - 2
IS  - 1
ER  -

Copy | Download

Author Information

Funso K. Ariyo

Department of Electronic and Electrical Engineering, Ile-Ife, Nigeria

Download PDF

Sections

Plain Text BibTeX RIS

APA Style

Funso K. Ariyo. (2013). Investigation of Nigerian 330 Kv Electrical Network with Distributed Generation Penetration – Part III: Deterministic and Probabilistic Analyses.. American Journal of Electrical Power and Energy Systems, 2(1), 7-22. https://doi.org/10.11648/j.epes.20130201.12

Copy | Download

ACS Style

Funso K. Ariyo. Investigation of Nigerian 330 Kv Electrical Network with Distributed Generation Penetration – Part III: Deterministic and Probabilistic Analyses.. Am. J. Electr. Power Energy Syst. 2013, 2(1), 7-22. doi: 10.11648/j.epes.20130201.12

Copy | Download

AMA Style

Funso K. Ariyo. Investigation of Nigerian 330 Kv Electrical Network with Distributed Generation Penetration – Part III: Deterministic and Probabilistic Analyses.. Am J Electr Power Energy Syst. 2013;2(1):7-22. doi: 10.11648/j.epes.20130201.12

Copy | Download

@article{10.11648/j.epes.20130201.12,
  author = {Funso K. Ariyo},
  title = {Investigation of Nigerian 330 Kv Electrical Network with Distributed Generation Penetration – Part III: Deterministic and Probabilistic Analyses.},
  journal = {American Journal of Electrical Power and Energy Systems},
  volume = {2},
  number = {1},
  pages = {7-22},
  doi = {10.11648/j.epes.20130201.12},
  url = {https://doi.org/10.11648/j.epes.20130201.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.epes.20130201.12},
  abstract = {The concluding part of this work (Part III) presents the non-probabilistic (deterministic) assessment of failure effects under given contingencies and reliability analysis is an automation and probabilistic extension of contingency evaluation. Also, PowerFactory generation adequacy tool is design specifically for testing of system adequacy using Monte-Carlo method. Running adequacy analysis produces convergence plots, distribution plots and Monte-Carlo draw plots. PowerFactory’s contingency analysis module offers two distinct contingency analysis methods: single time phase and multiple time phase contingency analysis, while an analytical assessment of the network reliability indices is initiated by the following actions (failure modeling, load modeling, system state production, failure effect analysis (FEA), statistical analysis and reporting) within PowerFactory. Lastly, voltage sag analysis is a calculation that assesses the expected frequency of voltage sags within a network.},
 year = {2013}
}

Copy | Download

TY  - JOUR
T1  - Investigation of Nigerian 330 Kv Electrical Network with Distributed Generation Penetration – Part III: Deterministic and Probabilistic Analyses.
AU  - Funso K. Ariyo
Y1  - 2013/01/10
PY  - 2013
N1  - https://doi.org/10.11648/j.epes.20130201.12
DO  - 10.11648/j.epes.20130201.12
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  - 7
EP  - 22
PB  - Science Publishing Group
SN  - 2326-9200
UR  - https://doi.org/10.11648/j.epes.20130201.12
AB  - The concluding part of this work (Part III) presents the non-probabilistic (deterministic) assessment of failure effects under given contingencies and reliability analysis is an automation and probabilistic extension of contingency evaluation. Also, PowerFactory generation adequacy tool is design specifically for testing of system adequacy using Monte-Carlo method. Running adequacy analysis produces convergence plots, distribution plots and Monte-Carlo draw plots. PowerFactory’s contingency analysis module offers two distinct contingency analysis methods: single time phase and multiple time phase contingency analysis, while an analytical assessment of the network reliability indices is initiated by the following actions (failure modeling, load modeling, system state production, failure effect analysis (FEA), statistical analysis and reporting) within PowerFactory. Lastly, voltage sag analysis is a calculation that assesses the expected frequency of voltage sags within a network.
VL  - 2
IS  - 1
ER  -

Copy | Download