Create New Account
Login
Search or Buy Articles
Browse Journals
Browse Proceedings
Submit your Paper
Submission Information
Journal Review
Recommend to Your Library
Call for Papers
Hybrid Fuzzy Neural Network based Contingency Ranking for Voltage Collapse
M. Pandit, L. Srivastava, and J. Sharma
References
[1] S. Greene, I. Dobson, & L.F. Alvarado, Contingency rankingfor voltage collapse via sensitivities from a single nose curve,IEEE Trans. on Power Systems, 14 (1), 1999, 232–240.
doi:10.1109/59.744538
[2] E.C. Fuchs, W. Xu, Y. Mansour, H. Hamadanizadeh, & G.K.Morison, Voltage stability contingency screening and ranking,IEEE Trans. on Power Systems, 14 (1), 1999, 256–265.
doi:10.1109/59.744541
[3] T. Van Cutsem, C. Moisse, & R. Mailhot, Determination ofsecure operating limits with respect to voltage collapse, IEEETrans. on Power Systems, 14 (1), 1999, 327–334.
doi:10.1109/59.744551
[4] L. Srivastava, S.N. Singh, & J. Sharma, Estimation of loadability margin using parallel self-organizing hierarchical neural network, International Journal of Computers and Electrical Engineering (U.S.A.), 26, 2000, 151–167.
[5] M. Pandit, L. Srivastava, & J. Sharma, Contingency ranking forvoltage collapse using parallel self-organizing hierarchical neuralnetwork, forthcoming in International Journal of ElectricalPower and Energy Systems.
[6] Y.-Y. Hsu & H.-C. Kuo, Fuzzy-set based contingency ranking,IEEE Trans. on Power Systems, 7 (3), 1992, 1189–1195.
doi:10.1109/59.207333
[7] S.K. Tso, T.X. Zhu, & K.L. Lo, Fuzzy-set approach to dynamic voltage security assessment, IEE Proc. Generation, Transmission and Distribution, 142 (2), 1995, 190–194.
doi:10.1049/ip-gtd:19951714
[8] J. Nahman & I. Okljev, Fuzzy logic and probability based real-time contingency ranking, Electrical Power & Energy Systems,22, 2000, 223–229.
doi:10.1016/S0142-0615(99)00033-2
[9] M.A. Matos, N.D. Hatziargyriou, & J.A. Pecas Lopes, Multi-contingency steady state security evaluation using fuzzy clustering techniques, IEEE Trans. on Power Systems, 15 (1), 2000, 177–183.
doi:10.1109/59.852118
[10] A.A. El-Keib & X. Ma, Application of artificial neural networkin voltage stability assessment, IEEE Trans. on Power Systems,10 (4), 1995, 1890–1896.
doi:10.1109/59.476054
[11] L. Srivastava, S.N. Singh, & J. Sharma, A hybrid neuralnetwork model for fast voltage contingency screening andranking, International Journal of Electrical Power and EnergySystems, 22 (q1), 2000, 35–42.
doi:10.1016/S0142-0615(99)00024-1
[12] Y. Mansour, E. Vaahedi, & M.A. El Sharkawi, Large-scaledynamic security contingency screening and ranking usingneural network, IEEE Trans. on Power Systems, 12 (2), 1997,954–960.
doi:10.1109/59.589789
[13] M.P. Dave & S. Chauhan, A robust artificial neural networktechnique for dynamic security assessment, Electric Machinesand Power Systems, 24 (5), 1996, 733–744.
[14] C.-W. Liu, C.-S. Chang, & M.-C. Su, Neuro-fuzzy networksfor voltage security monitoring based on synchronized phasormeasurements, IEEE Trans. on Power Systems, 13 (2), 1998, 326–332.
doi:10.1109/59.667346
[15] K.H. Abdul-Rahman, S.M. Shahidehpour, & M. Daneshdoost,AI approach to optimal VAR control with fuzzy reactive loads,IEEE Trans. on Power Systems, 10 (1), February 1995, 88–97.
doi:10.1109/59.373931
[16] K.P. Sankar & M. Sushmita, Multi-layer perceptron, fuzzysets and classification, IEEE Trans. on Neural Networks, 3 (5),1992, 683–697.
doi:10.1109/72.159058
[17] A. Rangachari, K.G. Mehrotra, C.K. Mohan, & S. Ranka,An improved algorithm for neural network classification ofimbalanced training sets, IEEE Trans. on Neural Networks,4 (6), 1993, 962–969.
doi:10.1109/72.286891
[18] Y.H. Pao, Adaptive pattern recognition and neural networks(Reading, MA: Addison-Wesley, 1989).
[19] K.L. Ho, Y.Y. Hsu, & C.C. Yang, Short-term load forecastingusing a multi-layer neural network with an adaptive learningalgorithm, IEEE Trans. on Power Systems, 7 (1), 1992, 141–149.
doi:10.1109/59.141697
[20] O.K. Ersoy & S.W. Deng, Parallel self organizing hierarchicalneural networks with continuous inputs and outputs, IEEETrans. on Neural Networks, NN-6 (5), 1995, 1037–1044.
doi:10.1109/72.410348
[21] L. Srivastava, S.N. Singh, & J. Sharma, Parallel self-organizinghierarchical neural network based fast voltage estimation, IEEProc. Generation, Transmission and Distribution, 145 (1),1998, 98–104.
doi:10.1049/ip-gtd:19981741
[22] PFLOW: Software available via anonymous ftp at iliniza.uwaterloo.ca in subdirectory pub/pflow.
[23] C.A. Canizares & F.L. Alvarado, Point of collapse and continuation methods for large AC/DC systems, IEEE Trans. Power Systems, 8, 1993, 1–8.
doi:10.1109/59.221241
[24] L.L. Freris & A.M. Sasson, Investigation of the load-flowproblem, Proc. IEE, 115 (10), 1968, 1459–1470.
[25] S.N. Singh & S.C. Srivastava, Corrective action planning to achieve a feasibl optimum power flow sloution, IEE Proc. Part C, 142, 1995, 576-582.
doi:10.1049/ip-gtd:19952216
Important Links:
Abstract
DOI:
10.2316/Journal.203.2005.2.203-3268
From Journal
(203) International Journal of Power and Energy Systems - 2005
Go Back