157

References

[1] Verma P, “Review of Modern Diagnostics Techniques for assessing Insulation

condion in aged Transformer”, Electrical Review, Nov.2005, Vol XII, No-11, pp

26-29.

[2] Fabre, A. Pichon. “Deteriorating Processes and Products of paper in oil,

Application to transformers” Int Conf. on large high voltage electric systems

(CIGRE), paper 137, Paris 1960.

[3] Manual T90/T90+ “UV/VIS Spectrophotometer” [PG Instrument] TIFAC-CORE

“NIT- HAMIRPUR”.

[4] www.kelman.co.uk “Photoaquastic spectroscopy”.

[5] www.sciencefair.math.iit.edu “spectrophotometer”.

[6] www.gmi.inc.com“PG Instrument T90 UV/VIS Spectrophotometer”.

[7] M. Wanr and A. J. Vandermaar “Review of condition assessment of power

transformers in service”, in IEEE Electrical insulation Magazine, vol. 18, no. 6,

pp. 12-25, Nov-Dec.92.

[8] David Woodcock “Risk-Based Reinvestment-Trends in Upgrading the Aged T&D

System”, www.energypulse.net/centers/article2004

[9] Lapworth John and McGrail Tony, “Transformer Failure Modes and Planned

Replacement”, IEE Colloquium on Transformer life management (Ref. No.

1998/510), 22 Oct. 1998, pp:9/1 - 9/7

[10] Prevost T.A.; Oommen T.V, “Cellulose insulation in oil-filled power

transformers: Part I- History and development”, IEEE Electrical Insulation

Magazine, vol.22, Issue 1, Jan.-Feb. 2006, pp. 28-35.

[11] Chendong. X., “Monitoring paper insulation aging by measuring furfural content

of oil”, in Proc. 7th Int. Symp. High Voltage Eng., Aug. 26-30, 1991, pp.139-42.

[12] Shkolnik A. B.,. Bigin K.M, and Kelly J.J. (S D Myers Inc.), “Creating a

preliminary model for estimating degree of polymerization of thermally upgraded

158

paper based on furan concentrations in transformer oil,” Doble Conf. Paper,

Boston, Apr. 1999

[13] Pahlavanapour B., “Power transformer insulation aging,” CIGRE SC 15 Symp.,

Sydney, Australia, 1995.

[14] Fabre, A. Pichon. “Deteriorating Processes and Products of paper in oil,

Application to transformers” International Conf. on large high voltage electric

systems (CIGRE), paper 137, Paris 1960.

[15] Thor Hjartarson, Shawn Otal, "Predicting Future Asset Condition Based on

Current Health Index and Maintenance Level" IEEE 11th International Conference

on Transmission & Distribution Construction, Operation and Live-Line

Maintenance, 2006, ESMO, Oct. 2006

[16] Nick Dominelli, "Equipment Health Rating of Power Transformers", IEEE

International Symposium on Elecmcal Insulation, Indianapolis, IN USA, 19-22

September 2004, pp. 163 -168.

[17] Hasmat malik, Abdul Azeem and R.K. Jarial, "Application Research Based on

Modern-Technology for Transformer Health Index Estimation", in Proc. IEEE Int.

Multi-Conf. on Systems, Signals and Devices (SSD), Pp. 1-7, 2012, Germany

[18] M. Wanr! and A. J. Vandermaar “Review of condition assessment of power

transformers in service”, in IEEE Electrical insulation Magazine, vol. 18, no. 6,

pp. 12-25, NoviDecZG92.

[19] David Woodcock “Risk-Based Reinvestment-Trends in Upgrading the Aged T&D

System”, www.energypulse.net/centers/article2004.

[20] "Component-wise failure of transformers & reactors-worldwide-Survey"

[21] C. Myers, “Transformers – Condition Monitoring by Oil Analysis, Large or

Small; Contentment or Catastrophe”, Proceedings of the 1998 1st IEE

International Conference on Power Station Maintenance – Profitability through

Reliability”, pp.53-58.

[22] Church, J.O. , Haupert, T.J. and Jakob, Fredi (1987). “Analyze Incipient Faults

with Dissolved-gas Nomograph.” Elecrical World. Oct. Pgs. 40-44.

159

[23] British Standards Institution (1979). “Guide for the Interpretation of the Analysis

of Gases in Transformers and other Oil-filled Electrical Equipment in Service.”

London: (BS 5800).

[24] Deepika Bhalla, Raj Kumar Bansal, and Hari Om Gupta, "Application of

Artificial Intelligence Techniques for Dissolved Gas Analysis of Transformers-A

Review" in Proc. World Academy of Science, Engineering and Technology-62,

Pp. 221-229, 2010.

[25] ANSI/IEEE C57.104-2008 "IEEE Guide for the Interpretation of Gases Generated

in Oil-Immersed Transformers" IEEE Power Engineering Society, 1992-2008.

[26] IEC Publication Standard 60599, "Guide to the interpretation of dissolved and free

gas analysis" 1999-2007-05.

[27] IEC 60599-2007/05 Guide to the interpretation of dissolved and free gases

analysis of Mineral oil-impregnated electrical equipment in service.

[28] K. F. Thang, R. K. Aggarwal, A. J. MacGrail and D. G. Esp, “Application of Self-

Organizing Map Algorithms for Analysis and Interpretation of Dissolved Gases in

Power Transformers,” Power Engineering Society Summer Meeting, 2001. IEEE,

Vancouver, BC, Canada,07 /15/2001 Vol. 3,pp 1881-1886.

[29] K. F. Thang, R. K. Aggarwal, D. G. Esp, and A. J. MacGrail, “Statistical and

Neural Analysis of Dissolved Gases in Power Transformers,”Eighth International

Conference on Dielectric Materials, Measurements and Applications, 2000. (IEE

Conf. Publ. No. 473) 09/17-21/2000, Edinburgh, UK, pp 324-329.

[30] N. Yadaiah and Nagireddy Ravi, “Fault Detection Techniques for Power

Transformers,” Industrial & Commercial Power Systems Technical Conference,

2007. ICPS 2007. IEEE/IAS Vol.6, Issue ,11 May 2007, pp:1 – 9.

[31] Lapworth John and McGrail Tony, “Transformer Failure Modes and Planned

Replacement”, IEE Colloquium on Transformer life management (Ref. No.

1998/510), 22 Oct. 1998, pp:9/1 - 9/7.

[32] K. F. Thang, R. K. Aggarwal, A. J. MacGrail and D. G. Esp,“Application of Self-

Organizing Map Algorithms for Analysis and Interpretation of Dissolved Gases in

Power Transformers,” Power Engineering Society Summer Meeting, 2001. IEEE,

Vancouver, BC, Canada,07 /15/2001 Vol. 3,pp 1881-1886.

160

[33] K. F. Thang, R. K. Aggarwal, D. G. Esp, and A. J. MacGrail, “Statistical and

Neural Analysis of Dissolved Gases in Power Transformers” Eighth International

Conference on Dielectric Materials, Measurements and Applications, 2000. (IEE

Conf. Publ. No. 473) 09/17-21/2000, Edinburgh, UK, pp 324-329.

[34] N. Yadaiah and Nagireddy Ravi, “Fault Detection Techniques for Power

Transformers,” Industrial & Commercial Power Systems Technical Conference,

2007. ICPS 2007. IEEE/IAS Vol.6, Issue, 11 May 2007, pp:1 – 9.

[35] Diego Roberto Moaris and Jacqueline Gisete Rolim, “An artificial Neural

Network Approach to Transformer Fault Diagnosis,” IEEE Transactions on Power

Delivery , Vol. 11, No. 4, April 1996, pp 1836-1841.

[36] IS 10593:2006 Indian Standard “Mineral Oil-impregnated Electrical Equipment in

service-Guide to interpretation of dissolved and free gas analysis.” ( Second

Revision).

[37] Xiaohui Li, Huaren Wu and Danning Wu, "DGA Interpretation Scheme Derived

From Case Study" in IEEE TRANSACTIONS ON POWER DELIVERY, VOL.

26, NO. 2, Pp. 1292-1293, APRIL 2011.

[38] L.E. Lundgaard, “Partial Discharge – Part XIV: Acoustic Partial Discharge

Detection – Practical Application”, IEEE Electrical Insulation Magazine, Vol.8,

No.5, Sept/Oct 1992, pp.34-43.

[39] Abbas Zargari, Trevor R. Blackburn, “Application of Optical Fiber Sensor for

Partial Discharge Detection in High-Voltage Power Equipment”, IEEE Annual

Report – Conference on Electrical Insulation and Dielectric Phenomena, San

Francisco, Oct 20-23, 1996, pp.541-544.

[40] H. Borsi, E. Gockenbach, D. Wenzel, “Separation of Partial Discharges From

Pulse-Shaped Noise Signals With the Help of Neural Networks”, IEE Proc. – Sci.

Meas. Technol., Vol.142, No.1, Jan 1995, pp.69-74.

[41] V. Nagesh, B.I. Gururaj, “Automatic Detection and Elimination of Periodic Pulse

Shaped Interferences in Partial Discharge Measurements”, IEE Proc. – Sci. Meas.

Technol., Vol.141, No.5, Sept 1994, pp.335-342.

161

[42] Ronald T. Harrold, “The Relationship Between Ultrasonic and Electrical

Measurements of Underoil Corona Sources”, IEEE Transactions on Electrical

Insulation, Vol.11, No.1, 1976, pp.8-11.

[43] Deheng Zhu, Kexiong Tan, Xianhe Jin, “The Study of Acoustic Emission Method

for Detection of Partial Discharge in Power Transformers”, Tsinghua University,

Beijing, China, presented at 3rd International Conference on Properties and

Applications of Dielectric Materials, July 8-12, 1991,Tokyo, Japan

[44] L.E. Lundgaard, “Partial Discharge – Part XIII: Acoustic Partial Discharge

Detection – Fundamental Considerations”, IEEE Electrical Insulation Magazine,

Vol.8, No.4, July/Aug 1992, pp.25-31

[45] T. Bengtsson, M. Leijon, L. Ming, B. Jonsson, “Directivity of Acoustic Signals

from Partial Discharges in Oil”, IEE Proc. – Sci. Meas. Technol., Vol.142, No.1,

Jan 1995, pp.85-88

[46] Robert Meunier, Georges H. Vaillancourt, “Propagation Behavior of Acoustic

Partial Discharge Signals in Oil-Filled Transformers”, Conference Record of the

ICDL ’96 12th International Conference on Conduction and Breakdown in

Dielectric Liquids, Roma, Italy, July 15-19, 1996, pp.401-404

[47] E. Howells, E.T. Norton, “Location of Partial Discharge Sites in On-Line

Transformers”, IEEE Transactions on Power Apparatus and Systems, Vol.PAS-

100, No.1, Jan 1981, pp.158-162

[48] H. Kawada, M. Honda, T. Inoue, T. Amemiya, “Partial Discharge Automatic

Monitor for OilFilled Power Transformer”, IEEE Transactions on Power

Apparatus and Systems”, Vol.PAS-103, No.2, Feb 1984, pp.422-428

[49] Peter M. Eleftherion, “Partial Discharge XXI: Acoustic Emission-Based PD

Source Location in Transformers”, IEEE Electrical Insulation Magazine, Vol.11,

No.6, 1995, pp.22-26

[50] Liang Tang, Zhirong Wu, Huangzhang Li, Dexin Nie, “Location of Partial

Discharges in Power Transformers Using Computer-Aided Acoustic Techniques”,

Canadian Journal of Electrical and Computer Engineering, Vol.21, No.2, 1996,

pp.67-71

162

[51] Wang Chang chang, Dong Xuzhu, Wang Zhongdong, et al, “On-Line Partial

Discharge Monitoring System for Power Transformer”, 10th International

Symposium on High Voltage Engineering, Montreal, Canada, 1997, paper

No.3387

[52] L.E. Lundgaard, “Partial Discharge – Part XIII: Acoustic Partial Discharge

Detection – Fundamental Considerations”, IEEE Electrical Insulation Magazine,

Vol.8, No.4, July/Aug 1992, pp.25-31

[53] B.F. Lzbasarov, M.Kh.Ul’masova, P.K. Khabibullaev, “Acoustic Dispersion in

Transformer Oil”, Soviet Physics Acoustics, Vol.28, No.1, Jan/Feb 1982, pp.74-

75

[54] E. Howells, E.T. Norton, “Parameters Affecting the Velocity of Sound in

Transformer Oil”, IEEE Trans., Vol.PAS-103, No.5, May 1984, pp.1111-1115

[55] I.J. Kemp, “Partial Discharge Plant Monitoring Technology: Present and Future

Developments”, IEE Proc. –Sci. Meas. Technolo., Vol.142, No.1, Jan 1995, pp.4-

10

[56] Donald Chu, Andre Lux, “On-Line Monitoring of Power Transformers and

Components: A Review of Key Parameters”, IEEE Electrical Insulation

Conference & Electrical Manufacturers and Coil Winding Exposition, Cincinnati,

Ohio, Oct 25, 1999

[57] IEEE PES Transformers Committee, “IEEE Trial-Use Guide for Partial Discharge

Measurement in Liquid-Filled Power Transformers and Shunt Reactors”,

IEEE/NEMA, C57.113-1988

[58] IEEE PES Transformers Committee, “IEEE Standard Requirements,

Terminology, and Test Code for Shunt Reactors Rated Over 500 kVA”, IEEE

Standards Board, C57.21-1991

[59] IEEE PES Transformers Committee, “IEEE Guide for Failure Investigation,

Documentation, and Analysis for Power Transformers and Shunt Reactors”, IEEE

Standards Board, C57.125-1991

[60] M. Darveniza, T.K. Saha, D.J.T. Hill, T.T. Le, “Investigation into Effective

Methods for Assessing the Condition of Insulation in Aged Power Transformers”,

IEEE PES WM 1997, PE-343-PWRD-0-11-1997

163

[61] Donald Chu, Andre Lux, “On-Line Monitoring of Power Transformers and

Components: A Review of Key Parameters”, IEEE Electrical Insulation

Conference & Electrical Manufacturers and Coil Winding Exposition, Cincinnati,

Ohio, Oct 25, 1999

[62] T.W. Hayes, “Investigation to Determine the Location of a Low-Energy, Audible

Electrical Arcing in a Power Transformer”, Minutes of Fifty-Third International

Conference of Doble Clients, 1986, Section 6-301

[63] P.L. Austin, “Use of DGA and Acoustic Devices to Detect and Locate Faults in a

588 MVA Generator Step-Up Transformer”, Minutes of Fifty-Ninth International

Conference of Doble Clients, 1992, Section 1-18.1

[64] D. Berent, “Acoustic Monitoring and Gas-in-oil Analysis for Transformers”,

Minutes of SixtySecond International Conference of Doble Clients, 1995, Section

8-3.1

[65] FIST, and Techniques Guide for "Transformer Diagnostics" Hydroelectric

Research and Technical Services Group, Vol.3-31, June 2003.

[66] Yang Hong-Tzer and Huang Yann-Chang, “Intelligent Decision Support for

Diagnosis of Incipient Transformer Faults Using Self-Organizing polynomial

Networks”, in IEEE trans. On Power Delivery, Vol. 13, No. 3, Pp. 946-952, Aug.

1998.

[67] Guardado J.L., Naredo J.L., Moreno P. and Fuerte C.R, “A comparative study of

neural network efficiency in power transformers diagnosis using dissolved gas

analysis”, IEEE Trans. Power Del., vol.16, no. 4, Pp. 643-647, Oct. 2001.

[68] Thang K.F., Aggarwal R.K., McGrail A.J and Esp D.G., “Application of Self-

Organizeing Map Algorithm for Analysis and Interpretation of Dissolved Gases in

Power Transformers”, in IEEE Power Engineering Society Summer Meeting, Vol.

3, Pp. 1881-1886, 2001.

[69] Huang Y.C, “Power transformer Fault Detection Using Intelligent Neural

Networks”, Proc. IEEE TENCON, Pp. 1761-1764, 2002.

[70] Huang Y.C,”Evolving neural nets for fault diagnosis of power transformers”, in

IEEE Trans. On Power Delivery, Vol. 18, No. 3, Pp. 843-848, July 2003.

164

[71] Sarma D.V.S.S. Siva and Kalyani G.N.S, “ANN Approach for Condition

Monitoring of Power Transformers Using DGA”, in Proc. IEEE Int. Conf. 0-

7803-8560-8/04, Pp. 444-447, 2004

[72] W. M. Lin, C. H. Lin and M. X. Tasy, "Transformer-fault diagnosis by integrating

field data and standard codes with training enhancible adaptive probabilistic

network" in IEE Proc.-Gener. Transm. Distrib., Vol. 152, No. 3, Pp. 335-341,

May 2005.

[73] R. Xianwen, Zhangfeng, Z. Lingfeng and Men Xianwen, "Application of

Quantum Neural Network Based on Rough Set in Transformer Fault Diagnosis",

in Proc. IEEE Int. Conf. Record No. 978-1-4244-4813-5/10/$25.00 ©2010 IEEE,

Pp. 1-4, 2010.

[74] Y.M. TU, J.M.Huang, N.Gao, Z.S.Zhu and Z.Yan, "Transformer Insulation

Diagnosis Based On Improved ANN Analysis" in Proc. IEEE Int. Conf. on

Properties and Applications of Dielectric Materials, Pp. 263-266, May 25-

30,1997, Seoul, Korea.

[75] Gao Wensheng, Qian Zheng and Yan Zhang, "A Multi Resolution System

Approach to Power Transformer Insulation Diagnosis", In Proc. IEEE Int.

Symposium on Electrical Insulating Materials, in conjunction with 1998 Asian

International Conference on Dielectrics and Electrical Insulation and the 30tlh

Symposium on Electrical Insulating Materials, Toyohashi, Japan, Sept. 27-30,

1998, pp.385-388.

[76] Liao Ruijin, Sun Caixin, Chen Weigen, and Wang Caisheng, "On-line Detection

of Gases Dissolved in Transformer Oil and the Fault Diagnosis", in Proc. IEEE

Int. Symposium on Electrical Insulating Materials, Japan, Sept. 27-30, 1998, pp.

771-774.

[77] Tu Yanming and Qian Zheng, "DGA Based Insulation Diagnosis of Power

Transformer via ANN", in Proc. IEEE Int. Conf. on Properties and Applications

of Dielectric Materials, Pp. 133-136, June 21-26, 2000.

[78] I. N. da Silva, M.M. Imamura and A. N. de Souza, "The Application of Neural

Networks to the Analysis of Dissolved Gases in Insulating Oil Used in

165

Transformers", in Proc. IEEE Int. Conf. Record No. 0-7803-6583-6/00/$10.00

IEEE, pp. 2643-2648, 2000.

[79] M.-H. Wang, "Extension neural network for power transformer incipient fault

diagnosis" in IEE Proc-Gener. Trns. Distb., Vol. 150, No. 6, Pp. 679-685, Nov.

2003.

[80] A. Akbari, A. Setayeshmehr, H. Borsi and E. Gockenbach, "Intelligent Agent-

Based System Using Dissolved Gas Analysis to Detect Incipient Faults in Power

Transformers", in IEEE Electrical Insulation Magazine, November/December-

Vol. 26, No. 6, Pp. 27-40, 2010.

[81] Huaren Wu, Xiaohui Li and Danning Wu, "RMP Neural Network Based

Dissolved Gas Analyzer for Fault Diagnostic of Oil-filled Electrical Equipment",

in IEEE Transactions on Dielectrics and Electrical Insulation Vol. 18, No. 2, pp.

495-498, April 2011.

[82] Ahmed E. B. Abu-Elanien, M. M. A. Salama and Malak Ibrahim, "Determination

of Transformer Health Condition Using Artificial Neural Networks", in Proc.

IEEE Int. Conf. Record No. 978-1-61284-922-5/11/$26.00 ©2011 Crown, pp. 1-5,

2011

[83] Huixin Tian, Kun Li, and Bo Meng, "Multiple ANNs Combined Scheme for Fault

Diagnosis of Power Transformers", in Proc. IEEE Int. Conf. on 2011 Chinese

Control and Decision Conference (CCDC), pp. 2557-2560, 2011.

[84] P. GHong, LI Lei-jun and LI Yun-jie, "Model of Gas Warning System Based on

Neural Network Expert", in Proc. IEEE Int. Conf. on Computer Design And

Appliations, pp.395-398, 2010.

[85] I. S. Msiza, M. Szewczyk, A. Halinka, J-H. C. Pretorius, P. Sowa, and T.

Marwala, "Neural Networks on Transformer Fault Detection" in Proc. IEEE Int.

Conf. Record No. 978-1-61284-788-7/11/$26.00 ©2011 IEEE, pp.1-6, 2011.

[86] Li Song, Li Xiu-ying and Wang Wen-xu, "Fault diagnosis of transformer based on

probabilistic neural network", in Proc. IEEE Int. Conf. on Intelligent Computation

Technology and Automation, Pp. 128-131, 2011.

166

[87] Cai Guowei, Liu Ning and Yang Deyou, "The Transformer Fault Diagnosis Based

on Quantum Neural Network", in Proc. IEEE Int. Conf. on Computer,

Mechatronics, Control and Electronic Engineering, pp.396-400, 2010.

[88] Khaled Shaban, Ayman El-Hag and Andrei Matveev, "A Cascade of Artificial

Neural Networks to Predict Transformers Oil Parameters", in IEEE Transactions

on Dielectrics and Electrical Insulation Vol. 16, No. 2; pp. 516-523, April 2009

[89] Tomosovic K., Tapper M. and Ingvarsson T., “A Fuzzy Information Approach to

Integrating Different Transformer Diagnostic Methods”, in IEEE Transactions on

PWRD, Vol. 8, No. 3, Pp. 1638-1646, 1993

[90] Chen An-Pin and Lin Chang-Chun, “Fuzzy approaches for fault diagnosis of

transformers”, Fuzzy Sets and Systems 118, Pp. 139-151, 2001

[91] Su Q., Mi C., Lai L.L and Austin P., “A Fuzzy Dissolved Gas Analysis Method

for the Diagnosis of Multiple Incipient Faults in a Transformer, in IEEE Trans. On

Power Delivery, Vol. 15, No. 2, pp. 593-598, May 2000.

[92] Islam, Syed Mofizul, Wu, Tony and Ledwich, “A Novel Fuzzy-Logic Approach

to Transformer Fault Diagnosis”, in IEEE Trans. On Dielectrics and Electrical

Insulation, Vol. 7, No. 2, Pp. 177-186, April 2000

[93] Zhou Ping and Xu Shiheng, "a fuzzy-logic expert system for fault diagnosis and

security assessment of power transformers" in IEEE Proc. Int. Conf. on Tools with

AI, Boston, Massachusetts, Pp. 480-481,Nov. 1993.

[94] Adriano S. Carvalho and Armando J. M. Sousa, "Embedded Fuzzy Logic

Controller for Drying Oil Filled Transformers" in IEEE Proc. ISIE'97- GuimarPes,

Portugal, Pp. 1147-1150, 1997.

[95] M.Dong, Z. Yan and Yasuhiko Taniguchi, "Synthetic Analysis Technique of Oil-

impregnated Insulation" in Proc. IEEE Int. Conf. on Properties and Applications

of Dielectric Materials, June 1-5 2003, Nagoya, Pp.455-458.

[96] D. Wenzel D., H. Borsi and E. Gockenbach, "Partial Discharge Recognition and

Localization on Transformers via Fuzzy Logic", in Proc. IEEE Int. Symposium on

Electrical Insulation, Pittsburgh, PA USA, Pp. 233-236, June 5-8, 1994.

[97] Q. Su, "A Fuzzy-Logic Tool for Transformer Fault Diagnosis", in Proc. IEEE Int.

Conf. Record 0-7803-6338-8, pp. 265-268, 2000.

167

[98] Hongzhong Ma, Zheng Li, P.Ju, Jingdong Han and Limin Zhang, "Diagnosis of

Power Transformer Faults Based On Fuzzy Three-Ratio Method", in Proc. IEEE

Int. Conf.

[99] W. Flores, E. Mombello, J.A. Jardini and G. Rattá, "A Novel Algorithm for the

Diagnostics of Power Transformers Using Type -2 Fuzzy Logic Systems", in

Proc. IEEE Int. Conf. Record No. 978-1-4244-1904-3/08, Pp. 1-5, 2008.

[100] A. Abu-Siada, M. Arshad and S. Islam, "Fuzzy Logic Approach to Identify

Transformer Criticality using Dissolved Gas Analysis", in Proc. IEEE Int. Conf.

Record No. 978-1-4244-6551-4/10, Pp. 1-5, 2010.

[101] Deepika Bhalla, Raj Kumar Bansal, and Hari Om Gupta, "Transformer Incipient

Fault Diagnosis Based on DGA using Fuzzy Logic" in Proc. IEEE Int. Conf.

[102] Deyin Ma, Yanchun Liang, Xiaoshe Zhao, Zhexue Li and Xiaohu Shi, "The

application of Fuzzy System Group in Intelligent Diagnosis for Power

Tranformer" in Proc. IEEE Int. Conf. on Digital Manufacturing & Automation,

Pp.1206-1209, 2011.

[103] Teo B., Sergio B., Massimo L.S., Silvia L., Giuseppe R. and Ugo S., "A Fuzzy-

Logic Approach to Preventive Maintenance of Critical Power Transformers" in

Proc. C I R E D Int. Conf. on Electricity Distribution, Prague, 8-11 June 2009, pp.

1-5 (0944)

[104] M. Kumbhat, H. H. Ammar and M. A. Choudhry, "The Application of Fuzzy-

Logic to the Design of On-line Monitoring Systems", in Proc. IEEE Int. Conf.

Record No. 0-7803-0510-8/1992IEEE, pp.1036-1039, 1992.

[105] Bálint Németh, Szilvia Laboncz and István Kiss, "Condition Monitoring of Power

Transformers using DGA and Fuzzy Logic" in Proc. IEEE Int. Conf. on Electrical

Insulation, 31 May - 3 June 2009, pp. 373-376.

[106] Y. J. Yin, J. P. Zhan, C. X. Guo, Q. H. Wu, and J. M. Zhang, "Multi-Kernel

Support Vector Classifier for Fault Diagnosis of Transformers", in Proc. IEEE Int.

Conf. Record No.978-1-4577-1002-5/11/$26.00 ©2011 IEEE, pp. 1-7, 2011

[107] Xiaoyun Sun, J. Bian, D. Liu and Z. Li, "The Study of Transformer Fault

Diagnosis Based on Means Kernel Clustering and SVM Multi-class Object

168

Simplified Structure" in Proc. IEEE World Congress on Intelligent Control and

Automation June 25 - 27, 2008, Chongqing, China, pp. 5158-5161.

[108] Xiaodong Yu and Li Zhang, "Transformer Fault Diagnosis Based on Improved

SVM Model", in Proc. IEEE Int. Conf. on Natural Computation, Pp.578-582,

2009

[109] Hui Ma, Tapan K. Saha and C. E., "Power Transformer Insulation Diagnosis

under Measurement Originated Uncertainties", in Proc. IEEE Int. Conf. Record

No. 978-1-4244-6551-4/10/$26.00 ©2010 IEEE, Pp. 1-8, 2010

[110] Ganyun LV, J. Zheng and H. Zhang, "Multi-tie SVMs Classifier based Power

Equipment Fault Diagnosis", in Proc. IEEE Int. Conf. Record No. 1-4244-0134-

8/06/$200.00 ©2006 IEEEE, pp. 570-573, 2006

[111] L.V. Ganyun, C. H., Z. H. and D. Lixin, "Fault diagnosis of power transformer

based on multi-layer SVM classifier", in Elsevier Electric Power Systems

Research, ISSS No. 0378-7796, Vol. 74 (2005), Pp. 1–7

[112] Khmais Bacha, S. Souahlia and M. Gossa, "Power transformer fault diagnosis

based on dissolved gas analysis by support vector machine", in Elsevier Electric

Power Systems Research, ISSN No. 0378-7796, Vol. 83 (2012), Pp. 73– 79

[113] Dukarm J.J, “Transformer oil diagnosis using fuzzy logic and neural network”,

Canadian Conference on Electrical and computer Engineering, Vol. 1, Pp. 329-

332, 1993

[114] Yang Hong-Tzer and Huang Yann-Chang, “Intelligent Decision Support for

Diagnosis of Incipient Transformer Faults Using Self-Organizing polynomial

Networks”, in IEEE trans. On Power Delivery, Vol. 13, No. 3, Pp. 946-952, Aug.

1998.

[115] Lzzularab M.A, Aly G.E.M and Mansour D.A, “On-line Diagnosis of Incipient

Faults and Cellulose Degradation Based on Artificial Intelligence Methods”, in

Proc. Int. Conf. on Solid Dielectrics, Toulouse, France, July 2004.

[116] Kuo Hsing-Chia, Chang Hui-Kuo and Wang Yen-Zen, “Symbiotic evolution-

Based Design of Fuzzy-Neural Transformer Diagnostic System”, in Proc. Electric

Power Systems Research 72, Pp. 235-244, 2004.

169

[117] Miranda Vladimiro and Castro Adriana Rosa Garcez, “Improving the IEC Table

for Transformer Failure Diagnosis With Knowledge Extraction From Neural

Networks”, in IEEE Trans. On Power Delivery, Vol. 20, No. 4, Pp. 2509-2516,

Oct. 2005.

[118] Morais D.R. and Rolim J.G., “A Hybrid Tool for Detection of Incipient Faults in

Transformers Based on the dissolved Gas-Analysis of the Oil”, In IEEE Trans. On

Power Delivery, Pp. 1-7, April 2006.

[119] Lee J.P., Lee D.J, Ji P.S, Lim J.Y and Kim S.S., “Diagnosis of Power Transformer

Using Fuzzy Clustering and Redial Basis Function Neural Network”, in Proc. Int.

Joint Conf. on Neural Networks Sheration Vancouver Wall Centre Hotel,

Vancouver, BC, Canada, July 2006.

[120] R. Naresh, Veena Sharma, and Manisha Vashisth, "An Integrated Neural Fuzzy

Approach for Fault Diagnosis of Transformers", in IEEE TRANSACTIONS ON

POWER DELIVERY, VOL. 23, NO. 4, Pp. 2017-2024, OCTOBER 2008

[121] Hong-Tzer Yang, C. C. Liao and J. H. Chou, "Fuzzy Learning Vector

Quantization Networks for Power Transformer condition Assessment" in IEEE

Transactions on Dielectrics and Electrical Insulation, Vol. 8 No. 1, Pp. 143-149,

February 2001

[122] Stanislaw Osowski and K. Brudzewski, "Fuzzy Self-Organizing Hybrid Neural

Network for Gas Analysis System" in IEEE Transaction on Instrumentation and

Measurement, Vol. 49, No. 2, Pp. 424-428, April, 2000

[123] Hongsheng Su, "An ANFIS-based Transformer Insulation Fault Diagnosis

Method Using Emotional Learning", in Proc. IEEE Int. Conf. on Natural

Computation (ICNC), Pp. 1-5, 2007

[124] M. Surya K., B. R. Reddy and B.P. Singh, "Transformer Fault Diagnosis using

Fuzzy Logic and Neural Network" in Proc. IEEE Int. Conf. on Electrical

Insulation and Dielectric Phenomena, Pp. 486-489, 2005

[125] Huida Duan and Dejun Liu, "Application of Improved Elman neural network

based on fuzzy input for Fault Diagnosis in oil-filled power transformers" in Proc.

IEEE Int. Conf. on Mechatronic Science, Electric Engineering and Computer, Pp.

28-31, August 19-22, 2011, Jilin, China

170

[126] Zhou Ling, Y. H. and Cao Y, "Power Transformer Fault Diagnosis Based on

Fuzzy Integral Fusion", in Proc. IEEE Int. Conf. held in Hohai University, China,

Pp.1087-1090, 2004

[127] Bálint Németh, S. Laboncz, I.Kiss and G. Csépes, "Transformer condition

analyzing expert system using fuzzy neural system", in Proc. IEEE Int. Conf.

Record No. 978-1-4244-6301-5/10/$26.00 @2010 IEEE, Pp. 1-5.

[128] M. A. B. Amora, O. M. Almeida, A. P. S. Braga, F. R. Barbosa, S. S. Lima and L.

A. C. Lisboa, "Decompositional Rule Extraction from Artificial Neural Networks

and Application in Analysis of Transformers", in Proc. IEEE Int. Conf. Record

978-1-4244-5098-5/09/$26.00 ©2009 IEEE, Pp. 1-6

[129] Feng Dong and Chun Fu, "PSO-SVM Model for Gas/liquid Two-Phase Flow

Regime Recognition", in Proc. IEEE Int. Cont. Record 978-1-4244-8039-

5/11/$26.00 ©2011 IEEE, Pp. 2-4

[130] Zhi-biao Shi, Yang Li, Yun-feng Song and Tao Yu, "Fault Diagnosis of

Transformer Based on Quantum-behaved Particle Swarm Optimization-based

Least Squares Support Vector Machines", in Proc. IEEE Int. Conf. Record 978-1-

4244-4994-1/09/$25.00 ©2009 IEEE, Pp.1-4

[131] Jinling Lu and Mijia Wu, "Condition Assessment for Power Transformer Based

on Improved Particle Swarm Optimization and Support Vector Machine", in Proc.

IEEE Int. Conf. Record 978-1-4244-8081-4/10/$26.00 ©2010 IEEE, Pp. 1-6

[132] Sheng-Fa Yuan and Fu-Lei Chu, "Fault diagnostics based on particle swarm

optimization and support vector machines", in Elsevier Mechanical Systems and

Signal Processing , ISSN No. 0888-3270, Vol. 21 (2007), Pp. 1787–1798

[133] Ruijin Liao, Hanbo Zheng, Stanislaw Grzybowski and Lijun Yang, "Particle

swarm optimization-least squares support vector regression based forecasting

model on dissolved gases in oil-filled power transformers", in Elsevier Electric

Power Systems Research, ISSN No.0378-7796, Vol. 81 (2011), Pp. 2074– 2080

[134] Zhang Y. and Liu Y., “An Artificial Neural Network Approach to Transformer

Fault Diagnosis”, in IEEE Trans. On Power Delivery, Vol. 11, Pp. 1836-1841.

1996.

171

[135] Yishan Liang, Zhenyuan Wang and Yilu Liu, "An Automated On-line Monitoring

and Fault Diagnosis System for Power Transformers", in Proc. IEEE Int. Conf.

PSCE 2006, Pp.1105-1112

[136] Zhenyuan Wang, Yilu Liu and Paul J. Griffin, "A Combined ANN and Expert

System Tool for Transformer Fault Diagnosis", in Proc. IEEE Int. Conf. record 0-

7803-4403-0/98/$10.00 0 1998 IEEE, Pp.339-347

[137] Fu Yang and Zhang Hang, "Comprehensive Method Detecting the Status of the

Transformer Based on the Artificial Intelligence", in Proc. IEEE Int. Conf. on

Power System Technology - POWERCON 2004, Pp.1638-1643, Singapore, 21-24

November 2004

[138] Yishan Liang, Z. Wang and Yilu Liu, "Power Transformer DGA Data Processing

and Alarming Tool for On-line Monitors" in Proc. IEEE PES Power Systems

Conference & Exposition, Pp. 1-8, 2009

[139] Zhenyuan Wang, Yilu Liu and Paul J. Griffin, "Neural Net and Expert System

Diagnose Transformer Faults", in IEEE Trans. on Computer Application in

Power, ISSN No.0895-0156, Pp. 50-55, January 2000

[140] Zhenyuan Wang, Yilu Liu and Paul J. Griffin, "A Combined ANN and Expert

System Tool for Transformer Fault Diagnosis", in Proc. IEEE Int. Conf. record 0-

7803-5935-6/00/$10.00 (c) 2000 IEEE, pp. 1261-1269

[141] Ming-Yuan Cho, T. F. Lee, S. W. Kau1, Chin-S.S. and Chao-Ji Chou, "Fault

Diagnosis of Power Transformers Using SVM/ANN with Clonal Selection

Algorithm for Features and Kernel Parameters Selection", in Proc. IEEE Int. Conf.

on Innovative Computing, Information and Control, Pp. 1-5, 2006

[142] Sizwe M. Dhlamini and Tshilidzi Marwala, "An application of SVM, RBF and

MLP with ARD on bushings", in IEEE Int. Conf. on Cybernetics and Intelligent

Systems, Pp.1254-1259, 2004

[143] Hui Ma, Tapan K. Saha and C. Ekanayake, "Predictive Learning and Information

Fusion for Condition Assessment of Power Transformer", in Proc. IEEE Int. Conf.

record 978-1-4577-1002-5/11/$26.00 ©2011 IEEE, Pp.1-8, 2011

[144] Weigen Chen, Chong Pan, Yuxin Yun, and Yilu Liu,"Wavelet Networks in Power

Transformers Diagnosis Using Dissolved Gas Analysis", in IEEE

172

TRANSACTIONS ON POWER DELIVERY, VOL. 24, NO. 1, pp.187-194,

JANUARY 2009

[145] Honglei Li, Dengming Xiao and Yazhu Chen, “Wavelet ANN based transformer

fault diagnosis using Gas-in-oil Analysis”, Proc. 6th Int. Conf. on Properties and

Applications of Dielectric Materials, Xi’an Jiaotong University, China, June 2000.

[146] Jiyin Zhao and Ruirui Zheng,"Study on Power Transformer Fault Diagnosis Based

on Niche Genetic Algorithm", in Proc. IEEE Int. Conf. on Natural Computation,

pp 436-440, 2009

[147] Youyuan Wang, Ruijin Liao, Caixin Sun, Lin Du and Jianlin Hu,"A GA-based

grey prediction model for predicting the gas-in-oil concentrations in oil-filled

transformer", in Proc. IEEE Int. Symposium on Electrical Insulation, Pp. 74-77,

2004

[148] Huang Y.C, “A new data mining approach to dissolved gas analysis of oil

insulated power apparatus”, in IEEE Trans. On Power Delivery, vol. 18, No. 4,

Pp. 1257-1261, Oct. 2003.

[149] Yann-Chang Huang, "A New Data Mining Approach to Dissolved Gas Analysis

of Oil-Insulated Power Apparatus", in IEEE Transactions on Power Delivery, Vol.

18, No. 4, Pp. 1257-1261, Oct 2003

[150] Yunbing Wei, Xia Li, G. Cui and A. Zheng,"A Diagnostic Approach to Power

Transformers Based on Genetic Wavelet Networks Sample", in Proc. IEEE Int.

Conf. BIC-TA 2007, pp. 285-288, 2007.

[151] A. Shintemirov, W. H. Tang and Q. H.Wu, "Genetic Programming Feature

Extraction with Bootstrap for Dissolved Gas Analysis of Power Transformers", in

Proc. IEEE Int. Conf. record 978-1-4244-4241-6/09/$25.00 ©2009 IEEE, pp. 1-6,

2009

[152] Tang Wenhu, S. Almas and Wu Q. H, "Transformer Dissolved Gas Analysis

Using Least Square Support Vector Machine and Bootstrap", in Proc. IEEE Int.

Conf. on Control, Pp. 482-486, July 26-31, 2007

[153] Hongzhi Zang and X. Yu,"Transformer Fault Diagnosis Utilizing Rough Set and

Support Vector Machine", in Proc. IEEE Int. Conf. Record 978-1-4244-2487-

0/09/$25.00 ©2009 IEEE, Pp.1-4, 2009

173

[154] Huang Y.C and Huang C.M, “Evolving wavelet networks for power transformer

condition monitoring”, in IEEE Trans. On Power Delivery, vol. 17, No.2, Pp. 412-

416, April 2002.

[155] Huang Chin Pao, Wang Mang Hui, “Diagnosis of incipient faults in the power

transformers using CMAC neural network approach”, Electric Power System

Research 71, Pp. 235-244, 2004.

[156] W. H. Tang, J. Y. Goulermas and Q. H.Wu, "A Probabilistic Classifier for

Transformer Dissolved Gas Analysis With a Particle Swarm Optimizer", in IEEE

Transactions on Power Delivery, Vol. 23, No.2,pp. 751-759, April 2008

[157] Xiong Hao and Sun Cai-xin, "Artificial Immune Network Classification

Algorithm for Fault Diagnosis of Power Transformer", in IEEE Transactions on

Power Delivery, Vol. 22, No.2, pp. 930-935, April 2007

[158] Xiaoxia Wang, Tao Wang and Bingshu Wang, "Hybrid PSO-BP Based

Probabilistic Neural Network for Power Transformer Fault Diagnosis", in Proc.

IEEE Int. Symposium on Intelligent Information Technology Application, Pp.

545-549, 2008

[159] S Birlasekaran and G. Ledwich, "Use of FFT and ANN Techniques in Monitoring

of Transformer Fault Gases", in Proc. IEEE Int. Symposium on Electrical

Insulating Materials, Pp. 75-78, Japan, 1998

[160] Lee Hui Min and C.S. Chang, "Application of Dempster-Shafer’s Theory of

Evidence for Transformer Incipient Fault Diagnosis", in Proc. IEEE Int. Conf.

paper record 978-1-4244-2810-6/08/$25.00 ©2009 IEEE, Pp. 1-6

[161] Rogers R.R, "IEEE and IEC codes to interpret incipient faults in transformers

based on the dissolved gas analysis of the oil", IEEE Trans. on Er, Vol. 13 No. 5,

Pp. 348-354, 1978.

[162] Kelly J.J, "Transformer fault diagnosis by dissolved-gas analysis", IEEE Trans. on

AI, Vol. 16, No. 6, Pp. 777-782, 1980.

[163] M. Duval, "Dissolved gas analysis: It can save your transformer", IEEE Electrical

Insulation Magazine, Vol. 5, No. 6, Pp. 22-26, 1989.

174

[164] Saha T.K, "Review of Modern Diagnostic Techniques for Assessing Insulation

Condition in Aged Transformers", IEEE Trans. on Dielectric and Electrical

Insulation, Vol.10, No. 5, Pp.903-917, Oct. 2003.

[165] Ward S.A, "Evolving Transformer Condition Using DGA Oil Analysis", 2003

Annual Report Conf. on Electrical Insulation and Dielectric Phenomena, Pp. 463-

468, 2003.

[166] MATLAB R2009b version 7.9.0.529, 32-bit.

[167] Rosenblatt R (19958), "The Perceptron: A probabilistic model for information

storage and organization in the brain", Psychological Rev. 65, Pp. 386-408, 1958.

[168] Widrow B, and Hoff ME, "Adaptive switching circuits", IRE Eastern Electronic

Show & Convention (WESCON 1960), Convention Record, 4, Pp. 96-104, 1960.

[169] Rumelhart DE, Hinton GE and Williams RJ, "Learning internal representations by

error propagation", In Rumelhart DE, McClelland JL (eds) Parallel distributed

processing: Explorations in the microstructure of cognition, 1: Foundation, 318-

362, MIT Press, Cambridge, 1986.

[170] Kohonen T, "Self-Organization and associative memory", Springer, Berlin, 1989

[171] Jianye Liu, Yongchun Liang and Xiaoyun Sun, "Application of Leaming Vector

Quantization Network in Fault Diagnosis of Power Transformer", in Proc. IEEE

Int. Conf. on Mechatronics and Automation August 9 - 12, Changchun, China,

Pp.4435-4439, 2009.

[172] Michel Duval and Alfonso dePablo, "Interpretation of Gas-In-Oil Analysis Using

New IEC Publication 60599 and IEC TC 10 Databases", in IEEE Electrical

Insulation Magazine, ISSN No. 0883-7554, Vol. No. 17, No.2, Pp.31-41,

March/April 2001

[173] Specht, D.F.: ‘Probabilistic neural network for classification, mapping, or

associative memory’. Proc. IEEE Int. Conf. on Neural Networks, San Diego, CA,

July 1998, Vol. 1, pp 525–532.

[174] Specht, D.F.: ‘A general regression neural network’, IEEE Trans. Neural Netw.,

1991, pp. 568–576.

175

[175] Lin, W.-M., Lin, C.-H., Sun, Z.-C., and Tasy, M.-X.: ‘Probabilistic neural network

to fault section detection in power system’. Proc. 23rd Symp. on Electrical Power

Engineering, Taiwan, December 2002, pp. 203–207.

[176] Rzempoluck, E.J.: ‘Neural networks data analysis using simulnet’ (Springer-

Verlag, New York, 1998).

[177] K. Baburao “The experience of DP and Furan in condition assessment of power

transformer” 6th. India Doble Power Forum, November 14, 2007

[178] W.-M. Lin, C.-H. Lin and M.-X. Tasy, "Transformer-fault diagnosis by

integrating field data and standard codes with training enhancible adaptive

probabilistic network", in IEE Proc.-Gener. Transm. Distrib., Vol. 152, No. 3,

May 2005, Pp.335-341

[179] Lin, C.E., Ling, J.M. and Huang, C.L. (1993). “An Expert System for Transformer

Fault Diagnosis Using Dissolved Gas Analysis.” IEEE Transaction on Power

Delivery. Vol. 8. No. 1.

[180] Marzuki Khalid (1999). "Fuzzy Logic Control." UTM : Lecture Notes

(unpublished).

[181] V. Vapnik, “Estimation of Dependences Based on Empirical Data”, Springer-

Verlag, New York, 1982.

[182] V. N. Vapnik, “The Nature of Statistical Learning Theory”, Springer-Verlag, New

York, 1995.

[183] H. L. Pok, K. S. Yap, I. Z. Abidin, A. H. Hashim, Z. F. Hussien, and A. M.

Mohamad, “Abnormalities and Fraud Electric Meter Detection using Hybrid

Support Vector Machine and Modified Genetic Algorithm”, in Proc. of the 19th

International Conference on Electricity Distribution, CIRED, Vienna, 21-24 May,

2007.

[184] S. Gunn, “Support Vector Machines for Classification and Regression”, Technical

Report, Image, Speech and Intelligent Systems Research Group, University of

Southampton, U.S.A., 1997.

[185] N. Cristianini and J. Shawe-Taylor, “An Introduction to Support Vector Machines

and Other Kernel-based Learning Methods”, Cambridge University Press,

Cambridge, U.K., 2000.

176

[186] C. Cortes, “Prediction of Generalisation Ability in Learning Machines”, Ph.D

Thesis, University of Rochester, U.S.A., 1995.

[187] B. Scholkopf, “Support Vector Learning”. R. Oldenbourg Verlag, Munchen, 1997.

[188] C. Cortes, and V. Vapnik, “Support Vector Networks”, Machine Learning, vol.

20, no .3, pp. 273-297.

[189] V. Blanz, B. Scholkopf, H. Bulthoff, C. J. C. Burges, V. Vapnik, and T. Vetter,

“Comparison of View-Based Object Recognition Algorithms using Realistic 3D

Models”, in Proc. of the International Conference on Artificial Neural Networks.

Springer Verlag, Berlin, 1996.

[190] M. Schmidt, “Identifying Speakers with Support Vector Machines”, in Proc. of

Interface, Sydney, 1996.

[191] E. Osuna, “Applying SVMs to Face Detection”, IEEE Intelligent Systems, vol. 13,

Jul./Aug. 1998, pp. 23-26.

[192] E. Osuna, R. Freund, and F. Girosi, “Training Support Vector Machines: An

Application to Face Detection”, in Proc. of Computer Vision and Pattern

Recognition, 1997, pp. 130-136.

[193] Luenberger, D. G. & YE, Y. 2008. Linear and nonlinear programming, New York,

Springer.

[194] Camcl, F., Chinnam, R. B. and R. D. 2008. Robust kernel distance multivariate

control chart using support vector principles. International Journal of Production

Research, 46, 5075-5095.

[195] Camcl, F., Chinnam, R. B. and, R. B. 2008. General support vector representation

machine for one-class classification of non-stationary classes. Pattern

Recognition, 41, 3021-3034.

[196] C.H.Yann, "Evolving neural nets for fault diagnosis of power transformers, IEEE

Trans. Power Delivery 18 (3) (2003) 843–848.

[197] K. Tomsovic, M..Tapper, T. Ingvarsson, A fuzzy information approach to

integrating different transformer diagnostic methods, IEEE Trans. PWRD 8 (3)

(1993) 1638–1646.

[198] M. Duval, Dissolved gas analysis: it can save your transformer, IEEE Electr.

Insul. Mag. 5 (6) (1989) 22–27.

177

[199] Y. Zhang, X. Ding, Y. Liu and P. J. Griffin, "An Artificial Neural Network

Approach to Transformer Fault Diagnosis", in IEEE Transactions on Power

Delivery, Vol. 11, No. 4, Pp. 1836-1841, October 1996

[200] V. Duraisamy, N. Devarajan, D. S., A. Vasanth, S.N. Sivanandam, "Neuro fuzzy

schemes for fault detection in power transformer", in Elsevier Journal on Applied

Soft Computing, ISSN No. 1568-4946,Vol. 7, Pp. 534–539, 2007

[201] Hasmat Malik, Tarkeshwar and R.K. Jarial, "An Expert System for Incipient Fault

Diagnosis and Condition Assessment in Transformers", in Proc. IEEE Int. Conf.

on Computational Intelligence and Communication Systems, Pp. 138-142, 2011

[202] Narri Yadaiaha and N. Ravi, "Internal fault detection techniques for power

transformers", in Elsevier Journal of Applied Soft Computing, ISSN No. 1568-

4946, Vol. 11, Pp. 5259–5269, 2011

[203] Khmais Bacha, S. Souahlia and M. Gossa, "Power transformer fault diagnosis

based on dissolved gas analysis by support vector machine", in Elsevier Journal of

Electric Power Systems Research, ISSN No. 0378-7796, Vol. 83, Pp. 73-79, 2012

[204] www.google.com