Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 31225
Application of Neural Network for Contingency Ranking Based on Combination of Severity Indices

Authors: S. Jadid, S. Jalilzadeh

Abstract:

In this paper, an improved technique for contingency ranking using artificial neural network (ANN) is presented. The proposed approach is based on multi-layer perceptrons trained by backpropagation to contingency analysis. Severity indices in dynamic stability assessment are presented. These indices are based on the concept of coherency and three dot products of the system variables. It is well known that some indices work better than others for a particular power system. This paper along with test results using several different systems, demonstrates that combination of indices with ANN provides better ranking than a single index. The presented results are obtained through the use of power system simulation (PSS/E) and MATLAB 6.5 software.

Keywords: Neural Network, Transient Stability, composite indices

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1334043

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1909

References:


[1] S.Kirshna and K.R.Padiyar" Transient stability assessment using artificial neural network". Industrial Technology 2000,Proceeding of IEEE International conference on,Vol.1,,2000,pp 627-632
[2] A.A.Fouad .et.al "Transient stability program output analysis" IEEE Transaction on power systems ,Vol.1,No.1,pp 2-9
[3] M.H.Haque"Hybrid method of determining the transient stability margin of a power system".IEE,Proceeding in Generation ,Transmission and Disturbution,Vol 143,No.1,January1996 ,pp 27-32
[4] D.J.Sobajic and Y.H.Pao" Artificial neural network based dynamic security assessment for electric power system". IEEE Transaction on power systems,Vol.4,No.1,1989,pp 220-228.
[5] C. K. Pang , F. S. prabhakara , A. H. EI - Abiad and A. J. Koivo" Security evaluation in power system using pattern recognition". IEEE , Trans. PAS - 93,1974, pp 969-975 .
[6] L. Wehenkel , T. h. Van custem and M. R. pavella" An artificial intelligence framework for on line Transient stability assessment of power system". IEEE Transaction on power systems,Vol.4 ,1989, pp 789-800 .
[7] Chengjun.F.U and Anjan Bose" Contingency ranking based on severity indices in dynamic security analysis". IEEE Transaction on power system,Vol.14,No.3,August1999,pp254-259
[8] K.W.Chan,R.W.Dunn,A.R.Daniels,J.A.Padget,P.H.Buxton,M.J.Rawlins, and A.O.Likwue" Online dynamic security contingency screening and ranking".IEE Proceeding,Part-C,Vol.144,No.2,March1997,pp 132-138
[9] A.L.Bettiol et.al "Transient stability constraint maximum allowable transfer". IEEE Transaction on power system,PE-334-PWRS-0-06,1998.
[10] Wenping Li and Anjan Bose" A coherency based rescheduling method for dynamic security",.IEEE Transaction on power systems, Vol.13,No.3,August1998,pp 254-259
[11] M. A. EI - Kady , A. A. Found. And C. C. Liu" Knowledge - based system for direct stability analysis". EPRI. Final Report No. EL - 6796 , Electr , power Res. Inst. Paloalto , CA , APR,1990.
[12] A. B. R. Kumar , A. Ipakehi , V. Brandwajn , M. E I - Sharkawi and G. Cauley "Neural Network for dynamic security assessment of large power system requirments overview"Proceeding. 1st Int , forum application of artificial neural networks to power system , seattle , WA ,USA ,1991, pp 62-71