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Frontiers in Energy

ISSN 2095-1701

ISSN 2095-1698(Online)

CN 11-6017/TK

邮发代号 80-972

2019 Impact Factor: 2.657

Frontiers in Energy  0, Vol. Issue (): 288-299   https://doi.org/10.1007/s11708-013-0265-7
  RESEARCH ARTICLE 本期目录
Well-being analysis of GSU transformer insulation incorporating the impact on power generation using fuzzy logic
Well-being analysis of GSU transformer insulation incorporating the impact on power generation using fuzzy logic
Alagarsamy KRISHNAVEL1(), Dusmata Kumar MOHANTA1, M. Jaya Bharata REDDY2
1. Department of Electrical and Electronics Engineering, Birla Institute of Technology, Mesra 835215, India; 2. Department of Electrical and Electronics Engineering, National Institute of Technology, Tiruchirappalli 620015, India
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Abstract

With the prevailing power scenario, every watt-second of electrical energy has its own merit in satisfying the consumer demand. At the state of such a stringent energy demanding era, failure of a power generation equipment compounds the energy constraints which will not only result in a huge loss of generation but also have an impact on capital revenue. The unexpected failure of generator step-up (GSU) transformer is especially a major disturbance in the power system operation and leads to unscheduled outages with power delivery problems. The time lag in bringing back the equipment in service after rectification or replacement may increase the criticality as the process involves mobilization of spares and maintenance professionals. Hot atmosphere existing in the vicinity of thermal power stations running round-the-clock with more than 100% plant load factor (PLF) increases the thermal stress of the electrical insulation which leads to premature failure of windings, bushings, core laminations, etc. The healthy state of the GSU transformer has to be ensured to minimize the loss of power generation. As the predication related to failure of a GSU transformer is associated with some uncertainties, a fuzzy approach is employed in this paper along with actual field data and case studies for the well-being analysis of GSU transformer.

Key wordsgenerator step-up (GSU) transformer    well-being analysis    dissolved gases in oil analysis (DGA)    tan delta (TD)    sweep frequency response analysis (SFRA)    fuzzy inference system (FIS)
收稿日期: 2012-10-23      出版日期: 2013-09-05
Corresponding Author(s): KRISHNAVEL Alagarsamy,Email:krishna_vel@hotmail.com   
 引用本文:   
. Well-being analysis of GSU transformer insulation incorporating the impact on power generation using fuzzy logic[J]. Frontiers in Energy, 0, (): 288-299.
Alagarsamy KRISHNAVEL, Dusmata Kumar MOHANTA, M. Jaya Bharata REDDY. Well-being analysis of GSU transformer insulation incorporating the impact on power generation using fuzzy logic. Front Energ, 0, (): 288-299.
 链接本文:  
https://academic.hep.com.cn/fie/CN/10.1007/s11708-013-0265-7
https://academic.hep.com.cn/fie/CN/Y0/V/I/288
Fig.1  
Fig.2  
GasTemperature/°CGasTemperature/°C
Hydrogen50-100Acetylene900-1000
Methane50-100Carbon monoxide110
Ethane150-200Carbon dioxide110
Ethylene600-700
Tab.1  
H2/10-6CO/10-6CO2/10-6CH4/10-6C2H6/10-6C2H4/10-6C2H2/10-6
75-150400-8505300-1200035-13050-70110-25080-270
Tab.2  
CaseCharacteristic faultsGas ratios
C2H2 /C2H4CH4/ H2C2H4/C2H6
PDPartial dischargesNon-significant<0.1<0.2
D1Discharges of low energy>10.1-0.5>1
D2Discharges of high energy0.6-2.50.1-1>2
T1Thermal fault t<300°CNon-significantNon-significant<1
T2Thermal fault 300°C<t<700°C<0.1>11-4
T3Thermal fault t>700°C<0.2>1>4
Tab.3  
Name of OEM
TNEBELECTRA (1978)ALSTHOM (1980)ERDAIEC 60599
H2/10-620028.6200100150
CH4/10-620042.2200200110
80085.620020090
C2H4/10-620074.6200300280
C2H2/10-6150-2003050
CO2/10-69000377110000-13000
CO/10-6-2891000-900
Tab.4  
GasesName of the OEM
CPRICBIP
0-4 a4-10 a10 a<4 a4-10 a>10 a
H2150300500100/150200/300300/400
CH4308013050/70100/150200/300
C2H6305011030/50100/150800/1000
C2H43050150100/150150/200200/400
C2H215304020/3030/50100/150
CO24000-100003000/50004000/50009000/12000
CO300500700200/300400/500600/700
Tab.5  
Fig.3  
Fig.4  
Fig.5  
Fig.6  
Fig.7  
Fig.8  
CodeDetailsHealthyMarginalRisky
FromToFromTo
H2Hydrogen/10-60299300399>400
CH4Methane/10-60199200299>300
C2H6Ethane/10-60799800999>1000
C2H4Ethylene/10-60199200399>400
C2H2Acetylene/10-6099100149>150
CO2Carbon-dioxide/10-608999900011999>12000
COCarbon monoxide/10-60599600699>700
FuranLevel of 2-furaldehyde/10-902502511000>1000
SFRAdB deviation/%0114>4
TDWinding TD at 20°C/%00.50.512>2
Tab.6  
Fig.9  
Fig.10  
GasesDate of oil samples
07.01. 200825.10. 200808.04. 200915.04. 2009
H2/10-661225876
CH4/10-611459151418
C2H6 /10-6516784995
C2H4/10-614441215188
C2H2/10-602.171.760.06
CO2/10-644376061509825
Probabilistic index0.1030.4790.5240.123
Well-being stateNormalMarginalRiskyNormal
Tab.7  
GasesDate of oil sample
07.01. 200808.04. 200915.04. 2009
H2 /10-67223174
CH4/10-6161729
C2H6/10-61749
C2H4/10-66330
C2H2/10-600.020.49
CO2/10-620929872337
Probabilistic index0.1030.1170.122
Well-being stateNormalNormalNormal
Tab.8  
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