Siemens TMDS® Transformer Monitoring and Diagnostic System
© Siemens AG 2014 All Right Reserved.
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Siemens Transformer Lifecycle Management
Diagnostics
Engineered Solutions
Planning Studies
Field Services
• Sensors (GAS-Guards)
• SIT DRY®
• Condition Assessment
• Centralized (TMDS® )
• Replacements Parts: A/C, FP, ELIN, Siemens
• Contingency Planning
• Turnkey Replacement Projects
• Distributed ( TMDS® SM)
• ARMA • Uprate Studies
• Emergency Response • Testing Specialty HV Test Standard (PF etc.)
© Siemens AG 2014 All Rights Reserved. Page 2
Smart Grid Division
Siemens TMDS® Transformer Monitoring & Diagnostic System TMDS® suite of solutions are expert monitoring systems which integrate and analyze multiple transformer parameters to provide complete asset health assessment and management • Advanced detection of abnormal conditions by capturing statistically significant data based on transformer operation • ANSI/IEEE co-relational engineering models convert monitored data in to actionable information • Dynamic modeling to facilitate real time transformer loading without increased ageing • Self-Diagnostics - Automatically detects bad sensor data to avoid false diagnosis • Supportive of different preferences in sensing technologies and integration © Siemens AG 2014 All Rights Reserved. Page 3
Smart Grid Division
Siemens TMDS® - Knowledge Application -Ambient Temperature -Oil Temperature -Winding Temperature -Hot Spot Temperature
Model Alarm & Statistical Variance Codes
IEEE/IEC Thermal Model
-Relative Capacitance Deviation Bushing Model A
-H2, CH4, C2H4, C2H6, C2H2,O2 CO2, CO DGA Model - Thermal Calc with Oommen Curve Analysis
Prognosis & Correlation Model (Rule/Table based)
Rule based correlation data request
Moisture Model - Oil Level Calculation with Thermal Expansion Oil Level Model - Model incorporates statistical significance analysis, identifies data falling within predefined limits of confidence intervals (95%, 80% etc..), quickly identifies statistical breakout prior to alarms and trips
• Codes generate/diagnostic messages displayed in TMDSL Screen • Recommended Action, Trend and Prognosis driven by Rules based on logic tree and correlation of other model variables • Screen Graphic driven by codes generated and values measured
© Siemens AG 2014 All Rights Reserved. Page 4
Smart Grid Division
Siemens TMDS® - Knowledge Application Operational recommendations to reduce probability of catastrophic failure
System provides continuous diagnosis of condition & recommended action if appropriate
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Smart Grid Division
Siemens TMDS® - Knowledge Application
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Smart Grid Division
TMDS® Supports Central Diagnostics Strategies TMDS 2000L (Centralized Solution)
-Am bie nt Temp erature -Oil Tem perat ure -Winding Tem peratu re -Hot Sp ot Temp erature
TMDS Components
IEEE/IEC Therma l Model
- Hot Spot Temp L imit Prediction @ cu rren t lo ad - Hot Spot Temp fo r new load point Opera tiona l Therma l Load Limit M ode ls
Local Cu bicle
-Relative Capacitance De viation Bushing M ode l
Master Cu bicle
Remote Monitoring
-H2, CH 4, C2H4 , C2H 6, C2H2 ,O2 CO 2, C O DGA Model
Sub stat ion Gatewa y
- Installat ion & Co nfiguration - Data Analysis - Lon g Term Stora ge - Diagno stic Messages
Typical Substation Configuration Note; In addition to transformer models TMDS has built in diagnostics associated with I/O communication (broken wire), data runaway (sensor error data acquisition) and panel doors and temperature
- Therma l Ca lc w ith Oo mme n Cu rve Ana lysis
- Trend in g An alysis Trending Model
- Hot Spot Temp vs Accelerated Aging Cumulativ e Aging Model
Mois ture M ode l - Oil Level Ca lculation with The rm al Exp ansio n Oil Lev el M ode l
- Coo ling Syste m Effectiven ess
Cooling System M odel
- Mo del in corpo rates statistica l sig nificance a nalysis, ide ntif ies da ta falling within p re defined limits o f confiden ce int ervals (95%, 8 0% et c..), q uickly iden tifies statistica l b re akout p rior to ala rm s and trips
© Siemens AG 2014 All Rights Reserved. Page 7
Smart Grid Division
TMDS® Supports Central Diagnostics Strategies – And Data Integration TMDS 2000L (Centralized Solution)
TMDS 2000L (Centralized Solution) TMDS Components
TMDS Components
Local Cu bicle
Local Cu bicle
Master Cu bicle
Master Cu bicle
Substat ion Gatewa y
Substat ion Gatewa y
Typical Substation Configuration
Typical Substation Configuration
Enterprise Gateway Web access - eMail - Paging
Remote Monitoring
- Installat ion & Co nfiguration - Data Analysis - Diagno stic Messages
Sensor Data sent to TMDS periodically for analysis Calculated data and alarms, messages sent to data bases or other applications
Central Data Repository Non-Operational
Maintenance Mgmt System
Workforce Mgmt System
Operational Data Store
© Siemens AG 2014 All Rights Reserved. Page 8
Smart Grid Division
TMDS® SMART MONITOR Supports Distributed Diagnostics Strategies - Coo ling System Effectiven ess -Coolin g System Co ntrol
-Am bie nt Temp erature -Oil Tem peratu re -Winding Tem peratu re -Hot Sp ot Temp erature -Limit Based IEEE/IEC The rmal Model
Smart Monitor (Distributed Solution) Smart Monitor
Cooling System M ode l
-Relative Capacita nce De viation -Limit Based Bushing M ode l -H2, CH 4, C2H4, C2H 6, C2H2, O2 CO 2, C O -Limit Based
Installation & Configuration
- Trend ing An alysis - Defined Pe riod
Remote Monitoring
Trending Model
- Trend ing An alysis - Mu ltiple Pe riod
DGA Model - Thermal Ca lc w ith Oo mme n Cu rve Ana lysis -Limit Based
Sub stat ion Gatewa y
Trending Model
Mois ture Model - Oil Level Ca lculatio n with The rm al Exp ansion -Limit Based Oil Lev el M ode l
- Hot Spot Temp vs Accelerated Aging
Cumulative A gi ng M odel
Typical Substation Configuration
Offline Analysis & Long Term Data Capture
- Lap To p ba sed tools for off lin e an alysis of d ata fo r multip le perio ds
© Siemens AG 2014 All Rights Reserved. Page 9
Smart Grid Division
TMDS® Supports Central Diagnostics Strategies
Central Panel
Front View
© Siemens AG 2014 All Rights Reserved. Page 10
Rear view
Local Panel Smart Grid Division
TMDS® SMART MONITOR Supports Distributed Diagnostics Strategies
© Siemens AG 2014 All Rights Reserved. Page 11
Smart Grid Division
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