Voltage collapse risk index prediction for real time system's security monitoring

N. Aminudin, T. K.A. Rahman, N. M.M. Razali, M. Marsadek, N. M. Ramli, M. I. Yassin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Risk based security assessment (RBSA) for power system security deals with the impact and probability of uncertainty to occur in the power system. In this study, the risk of voltage collapse is measured by considering the L-index as the impact of voltage collapse while Poisson probability density function is used to model the probability of transmission line outage. The prediction of voltage collapse risk index in real time requires precise, reliable and short processing time. To facilitate this analysis, Artificial Intelligent using Generalize Regression Neural Network (GRNN) technique is proposed where the spread value is determined using Cuckoo Search (CS) optimization method. To validate the effectiveness of the proposed method, the performance of GRNN with optimized spread value obtained using CS is compared with heuristic approach.

Original languageEnglish
Title of host publication2015 IEEE 15th International Conference on Environment and Electrical Engineering, EEEIC 2015 - Conference Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages415-420
Number of pages6
ISBN (Electronic)9781479979936
DOIs
Publication statusPublished - 22 Jul 2015
Event15th IEEE International Conference on Environment and Electrical Engineering, EEEIC 2015 - Rome, Italy
Duration: 10 Jun 201513 Jun 2015

Publication series

Name2015 IEEE 15th International Conference on Environment and Electrical Engineering, EEEIC 2015 - Conference Proceedings

Other

Other15th IEEE International Conference on Environment and Electrical Engineering, EEEIC 2015
CountryItaly
CityRome
Period10/06/1513/06/15

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All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Energy Engineering and Power Technology

Cite this

Aminudin, N., Rahman, T. K. A., Razali, N. M. M., Marsadek, M., Ramli, N. M., & Yassin, M. I. (2015). Voltage collapse risk index prediction for real time system's security monitoring. In 2015 IEEE 15th International Conference on Environment and Electrical Engineering, EEEIC 2015 - Conference Proceedings (pp. 415-420). [7165198] (2015 IEEE 15th International Conference on Environment and Electrical Engineering, EEEIC 2015 - Conference Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EEEIC.2015.7165198