Artificial Neural Network for Power System Static Security Assessment: A Survey

Authors

  • I. S. Saeh No. 76, Sri Pulai Perdana, PO box 81310, Johor Bahru, Malaysia
  • M. W. Mustafa Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia

DOI:

https://doi.org/10.11113/jt.v66.1802

Keywords:

Artificial neural network, hybrid techniques, static security assessment

Abstract

According to the growth rate of Machine Learning (ML) application in some power system subjects, this paper introduce a comprehensive survey of Artificial Neural Network (ANN) in Static Security Assessment (SSA). Advantages and disadvantages of using ANN in above mentioned subjects and the main challenges in these fields have been explained, too. We explore the links between the fields of SSA and NN in a unified presentation and identify key areas for future research. Recent developments in the solution methods for SSA are reviewed. Hybrid techniques in SSA are also discussed and reviewed and future directions for research are suggested.

 

Author Biography

  • I. S. Saeh, No. 76, Sri Pulai Perdana, PO box 81310, Johor Bahru, Malaysia
    Faculty of Electric Engineering (FKE)

References

Niazi, K., C. Arora, and S. Surana. 2004. Power System Security Evaluation using ANN: Feature Selection Using Divergence. Electric Power Systems Research. 69(2): 161–167.

Kirschen, D. S. 2002. Power System Security. Power Engineering Journal. 16(5): 241–248.

Dy Liacco, T. 1967. The Adaptive Reliability Control System. Power Apparatus and Systems. IEEE Transactions on. 5: 517–531.

Grillo, S. 2008. Static Security Assessment of Electrical Power Systems Using Neural Classification Techniques. Mathematical Problems in Engineering, Aerospace and Sciences.

Fouad, A. et al. 1988. Dynamic Security Assessment Practices in North America. Power Systems. IEEE Transactions on. 3(3): 1310–1321.

Balu, N. et al. 1992. On-line Power System Security Analysis. Proceedings of the IEEE. 80(2): 262–282.

Mahadev, P. M. and R. D. Christie. 1994. Envisioning Power System Data: Vulnerability and Severity Representations for Static Security Assessment. Power Systems. IEEE Transactions on. 9(4): 1915–1920.

Shahidehpour, M. and Y. Wang. 2003. Communication and Control in Electric Power Systems: Applications of Parallel and Distributed Processing. Wiley-IEEE Press.

Zaborszky, J., K.W. Whang, and K. Prasad. 1980. Fast Contingency Evaluation Using Concentric Relaxation. Power Apparatus and Systems. IEEE Transactions on. 1: 28–36.

Singh, S. and S. Srivastava. 1998. Improved Contingency Selection Algorithm for Voltage Security Analysis. Electric Machines and Power Systems. 26(8): 855–871.

Ejebe, G. and B. Wollenberg. 1979. Automatic Contingency Selection. Power Apparatus and Systems. IEEE Transactions on. 1: 97–109.

Verma, K. and K. Niazi. 2012. Supervised Learning Approach to Online Contingency Screening and Ranking in Power Systems. International Journal of Electrical Power & Energy Systems.

Stott, B. and O. Alsac. 1974. Fast Decoupled Load Flow. Power Apparatus and Systems. IEEE Transactions on. 3: 859–869.

Mori, H., H. Tanaka, and J. Kanno. 1995. A Preconditioned Fast Decoupled Power Flow Method for Contingency Screening. in Power Industry Computer Application Conference. Conference Proceedings, IEEE. 1995: IEEE.

Brandwajn, V. and M. Lauby, Complete bounding method for AC contingency screening. Power Systems, IEEE Transactions on, 1989. 4(2): p. 724-729.

Pang, C. K., A. J. Koivo, and A. H. El-Abiad. 1973. Application of Pattern Recognition to Steady-State Security Evaluation in a Power System. IEEE Transactions on Systems, Man and Cybernetics. SMC-3(6): 622–631.

Pang, C. K., et al. 1974. Security Evaluation in Power Systems Using Pattern Recognition. IEEE Trans Power Appar Syst. PAS-93(3): 969–976.

Ozdemir, A., J. Y. Lim, and C. Singh. 2002. Line Outage Simulation by Bounded Network Solution. IEEE.

Pang, C. and A. Wood. 1975. Multi-Area Generation System Reliability Calculations. Power Apparatus and Systems. IEEE Transactions on. 94(2): 508–517.

Billinton, R. 1969. Composite System Reliability Evaluation. Power Apparatus and Systems. IEEE Transactions on. 4: 276–281.

Ranade, S. J. and R. Sullivan. 1981. A Reliability Analysis Technique For Bulk System Planning. Power Apparatus and Systems. IEEE Transactions on. (7): 3658–3665.

Mikolinnas, T., W. Puntel, and R. Ringlee. 1982. Application of Adequacy Assessment Techniques for Bulk Power Systems. Power Apparatus and Systems. IEEE Transactions on. 5: 1219–1228.

Mamandur, K. and G. Berg. 1982. Efficient Simulation of Line and Transformer Outages in Power Systems. Power Apparatus and Systems. IEEE Transactions on. 10: 3733–3741.

Srivani, J. and K. Swarup. 2008. Power System Static Security Assessment and Evaluation Using External System Equivalents. International Journal of Electrical Power & Energy Systems. 30(2): 83–92.

Panciatici, P., G. Bareux, and L. Wehenkel. 2012. Operating in the Fog: Security Management Under Uncertainty. Power and Energy Magazine, IEEE. 10(5): 40–49.

Carpentier, J. 1993. Static Security Assessment and Control: A Short Survey. IEEE.

Niebur, D. and A.J. Germond. 1992. Unsupervised Neural Net Classification of Power System Static Security States. International Journal of Electrical Power & Energy Systems. 14(2–3): 233–242.

Swarup, K. S. 2008. Artificial Neural Network Using Pattern Recognition for Security Assessment and Analysis. Neurocomputing. 71(4): 983–998.

Zhou, Q., J. Davidson, and A. Fouad. 1994. Application of Artificial Neural Networks in Power System Security and Vulnerability Assessment. Power Systems, IEEE Transactions on. 9(1): 525–532.

Wehenkel, L. A. 1997. Automatic Learning Techniques in Power Systems. Springer.

Niebur, D. and A. J. 1992. Germond, Power System Static Security Assessment Using the Kohonen Neural Network Classifier. Power Systems, IEEE Transactions on. 7(2): 865–872.

Mohammadi, M. and G. Gharehpetian. 2008. Power System On-line Static Security Assessment by Using Multi-Class Support Vector Machines. Journal of Applied Sciences. 8(12): 2226–2233.

Rathinam, A. and S. Padmini. 2007. Security Assessment of Power Systems Using Artificial Neural Networks-A Comparison Between Euclidean Distance Based Learning and Supervised Learning Algorithms. IEEE.

Aggoune, M., et al. 1989. Preliminary Results on Using Artificial Neural Networks for Security Assessment [of power systems]. IEEE.

Aggoune, M., et al. 1989. Artificial Neural Networks for Power System Static Security Assessment. IEEE.

El-Sharkawi, M. and R. Atteri. 1993. Static Security Assessment of Power System Using Kohonen Neural network. IEEE.

Weerasooriya, S., et al. 1992. Towards Static-security Assessment of a Large-Scale Power System Using Neural Networks. Generation, Transmission and Distribution [see also IEE Proceedings-Generation, Transmission and Distribution], IEE Proceedings. 139(1): 64–70.

El-Keib, A. and X. Ma. 1995. Application of Artificial Neural Networks in Voltage Stability Assessment. Power Systems, IEEE Transactions on. 10(4): 1890–1896.

Sobajic, D. J. and Y. H. Pao. 1989. Artificial Neural-net Based Dynamic Security Assessment for Electric Power Systems. Power Systems, IEEE Transactions on. 4(1): 220–228.

Karami, A. 2011. Power System Transient Stability Margin Estimation Using Neural Networks. International Journal of Electrical Power & Energy Systems. 33(4): 983–991.

Lin, Y. J. 2011. Prevention of Transient Instability Employing Rules Based on Back Propagation based ANN for Series Compensation. International Journal of Electrical Power & Energy Systems.

Hassan, L. H. et al. 2013. Current state of Neural Networks Applications in Power System Monitoring and Control. International Journal of Electrical Power & Energy Systems. 51: 134–144.

Bansal, R., Overview and literature survey of artificial neural networks applications to power systems (1992-2004). Journal of the Institution of Engineers (India). Part EL, 2006. 86(1): p. 282-296.

Saeh, I. and A. Khairuddin. 2008. Static Security Assessment Using Artificial Neural Network. In Power and Energy Conference, 2008. PECon 2008. IEEE 2nd International. IEEE.

Fischer, D., B. Szabados, and S. Poehlman. 2003. Automatic Contingency Grouping Using Partial Least Squares and Feed Forward Neural Network Technologies Applied to the Static Security Assessment Problem. IEEE.

Srinivasan, D., et al. 1998. Power System Security Assessment and Enhancement Using Artificial Neural Network. In Energy Management and Power Delivery, 1998. Proceedings of EMPD '98. 1998 International Conference on.

Cirrincione, G., M. Cirrincione, and F. Piglione. 1996. A Neural Network Architecture for Static Security Mapping in Power Systems. IEEE.

Tso, S., et al. 1998. A Hybrid Framework of Short-duration Simulation and ANN-based Transient Stability Assessment for Contingency Screening. IEEE.

Swarup, K. and P. B. CORTHIS. 2006. Power system Static Security Assessment Using Self-Organizing Neural Network. J. Indian Inst. Sci. 86: 327–342.

Haque, M.T. and A.M. Kashtiban. 2005. Application of Neural Networks in Power Systems; A Review. Proceedings of World Academy of Science, Engineering and Technology. 6: 53–57.

Maghrabi, H., J. Refaee, and M. Mohandes. 1998. Contingency Analysis of Bulk Power System Using Neural Networks. IEEE.

Jain, T., L. Srivastava, and S.N. Singh. 2003. Fast voltage Contingency Screening Using Radial Basis Function Neural Network. IEEE Transactions on Power Systems. 18(4): 1359–1366.

Napoli, R. and F. Piglione. 1996. On-line static Security Assessment of Power Systems By A Progressive Learning Neural Network. IEEE.

Javan, D., H. R. Mashhadi, and M. Rouhani. 2010. Static Security Assessment Using Radial Basis Function Neural Networks Based On Growing And Pruning Method. IEEE.

Ranaweera, D. and G. Karady. 1994. Active Power Contingency Ranking Using a Radial Basis Function Network. Int. J. Eng. Intell. Syst. for Elect. Eng. Communications. 2(3): 201–206.

Devaraj, D. and J. Preetha Roselyn. 2011. On-line Voltage Stability Assessment Using Radial Basis Function Network Model with Reduced Input Features. International Journal of Electrical Power & Energy Systems. 33(9): 1550–1555.

Saeh, I. and M. Mustafa. 2013. Performance Evaluation of Deregulated Power System Static Security Assessment using RBF-NN Technique. Jurnal Teknologi. 64(1).

Seyed Javan, D., H. Rajabi Mashhadi, and M. Rouhani. 2013. A Fast Static Security Assessment Method Based On Radial Basis Function Neural Networks Using Enhanced Clustering. International Journal of Electrical Power & Energy Systems. 44(1): 988–996.

Khattab, H., et al. 2012. Gene Expression Programming for Static Security Assessment of Power Systems. In Power and Energy Society General Meeting, IEEE. 2012: IEEE.

Kalyani, S. and K. Swarup. 2011. Particle Swarm Optimization Based K-Means Clustering Approach for Security Assessment In Power Systems. Expert Systems with Applications.

Kothari, D. 2012. Power system optimization. In Computational Intelligence and Signal Processing (CISP), 2012 2nd National Conference on. IEEE.

AlRashidi, M. R. and M. E. El-Hawary. 2009. A Survey of Particle Swarm Optimization Applications In Electric Power Systems. Evolutionary Computation, IEEE Transactions on. 13(4): 913–918.

Gjorgiev, B., D. KanÄev, and M. ÄŒepin. 2013. A New Model for Optimal Generation Scheduling of Power System Considering Generation Units Availability. International Journal of Electrical Power & Energy Systems. 47: 129–139.

Mohamed, A., S. Maniruzzaman, and A. Hussain. 2001. Static Security Assessment of a Power System Using Genetic-Based Neural Network. Electric Power Components and Systems. 29(12): 1111–1121.

Haghifam, M. and V. Zebarjadi. 1996. Fuzzy logic and Neural Network Approach to Static Security Assessment for Electric Power Systems. In Proceedings of 4th European Congress on Intelligent Techniques and Soft Computing.

Huang, S. J. 2001. Static Security Assessment of a Power System Using Query-Based Learning Approaches with Genetic Enhancement. In Generation, Transmission and Distribution, IEE Proceedings. IET.

Gaddam, R. R., A. Jain, and L. Belede. 2013. A PSO Based Smart Unit Commitment Strategy for Power Systems Including Solar Energy. in Proceedings of Seventh International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA 2012). Springer.

Sharma, B. and M. Pandit. 2012. Security Constrained Optimal Power Flow Employing Particle Swarm Optimization. In Electrical, Electronics and Computer Science (SCEECS), 2012 IEEE Students' Conference on. IEEE.

Shi, Q., et al. 2013. Study on Bayesian network parameters learning of power System Component Fault Diagnosis Based on Particle Swarm Optimization. Int. J. Smart Grid Clean Energy. 2(1): 132–137.

Mohammed, S. N .Q. 2010. Learning Enhancement of Radial Basis Function Network with Particle Swarm Optimization.

Kalyani, S. and K. S. Swarup. 2011. Particle Swarm Optimization Based K-Means Clustering Approach for Security Assessment in Power Systems. Expert Systems with Applications. 38(9): 10839–10846.

Kalyani, S. and K.S. Swarup. 2011. Classifier Design for Static Security Assessment Using Particle Swarm Optimization. Applied Soft Computing. 11(1): 658–666.

Lin, S. W. 2008. et al. Particle Swarm Optimization for Parameter Determination and Feature Selection of Support Vector Machines. Expert Systems With Applications. 35(4): 1817–1824.

Wu, S. Z. L. and X. Y. W. Tan. Parameters Selection of SVM for Function Approximation Based on Differential Evolution.

Wu, C. H., et al. 2007. A real-valued Genetic Algorithm to Optimize the Parameters of Support Vector Machine for Predicting Bankruptcy. Expert Systems With Applications. 32(2): 397–408.

Abe, S. 2010. Support Vector Machines for Pattern Classification. Springer-Verlag New York Inc.

Chen, X. and Y. Li. Network Security Evaluation Based on Support Vector Machine. in Proceedings of the 2nd International Conference on Green Communications and Networks 2012 (GCN 2012): Volume 3. 2013: Springer.

Ye, S., et al. 2012. Power System Transient Stability Assessment Based on Adaboost and Support Vector Machines. In Power and Energy Engineering Conference (APPEEC), 2012 Asia-Pacific. IEEE.

Kalyani, S. and K.S. Swarup. 2011. Classification and Assessment Of Power System Security Using Multiclass SVM. Systems, Man, and Cybernetics, Part C: Applications and Reviews. IEEE Transactions on.. 41(5): 753–758.

Kalyani, S. and K. S. Swarup. 2009. Study of Neural Network Models for Security Assessment in Power Systems. International Journal of Research and Reviews in Applied Sciences. 1(2): 104–117.

Boudour, M. and A. Hellal. 2005. Combined Use of Supervised and Unsupervised Learning for Power System Dynamic Security Mapping. Engineering Applications of Artificial Intelligence. 18(6): 673–683.

Luan, W., K. Lo, and Y. Yu. 2000. ANN-based Pattern Recognition Technique for Power System Security Assessment. IEEE.

Kashtiban, A. M. and M. Valizadeh. Application of Neural Networks in Power System Security Assessment.

Sidhu, T.S. and L. Cui. 2000. Contingency Screening for Steady-State Security Analysis by using FFT and Artificial Neural Networks. Power Systems, IEEE Transactions on. 15(1): 421–426.

Hashemi, S. and M. R. Aghamohammadi. 2013.Wavelet Based Feature Extraction of Voltage Profile For Online Voltage Stability Assessment Using RBF Neural Network. International Journal of Electrical Power & Energy Systems. 49: 86–94.

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Published

2013-12-19

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Section

Science and Engineering

How to Cite

Artificial Neural Network for Power System Static Security Assessment: A Survey. (2013). Jurnal Teknologi, 66(1). https://doi.org/10.11113/jt.v66.1802