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Siemens TMDS™ transformer monitoring and diagnostic systemSolutions for transformer life-cycle management

Selecting a transformer monitoring solution is a critical step in achieving your company’s Smart Grid asset management strategy. Transformer monitoring requires the integration of sensors, data management and analysis to turn sensor data into useful knowledge, and then an overlay of software applications to turn knowledge into actionable information. Appropriate online monitoring and diagnostic tools can help utilities avoid unplanned failures, lower maintenance costs and extend useful transformer life.

Siemens TMDS™ is an expert system combining multiple engineering models with advanced techniques of statistical learning, far exceeding existing monitoring concepts of simple measurement of operative condition with pre-fixed limits. Designed to provide transformer monitoring and diagnostics for transformers in a substation or across multiple substations, TMDS™ turns transformer monitoring data into actionable information by translating combustible dissolved gas, bushing capacitance deviation, moisture and other sensor measured data into diagnostic and prognostic messaging.

TMDS™ provides alarming and trending using models that work with rule-based logic, derived from accepted IEEE/ANSI guidelines and Siemens extensive transformer design, production and testing expertise, to perform correlations on both measured and calculated data. Alarm messaging includes maintenance support and suggested loading recommendations should TMDS™ classify that the observed deviation may result in the damage or potential failure of the transformer.

Additionally the TMDS™ can perform cooling system control functions by initiating staged cooling to optimize transformer operating temperatures.

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We strive to unlock value in your transformer monitoring and Smart Grid investments.

TMDS™ delivers decision support to the right personnel in the context of actionable information

The Siemens TMDS™ advantages include the following:

Best-in-class transformer monitoring and diagnostic system

Advanced detection of abnormal conditions

Provides 24/7 access to current operational data, trends, alarm history and messaging remotely or from a central location

Flexible, scalable architecture

Supports customer preferences in transformer sensing technologies

Automatically detects bad sensor data to avoid false diagnosis

Configurable for legacy transformers.

The Siemens advantage:

More than 100 years of transformer manufacturing expertise

Over 500 employees dedicated to developing innovative transformer life-extension solutions to support legacy transformers

Globally, we have over $108B in sales, 480,000 employees and spend $7.3B in R&D investment per year.

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Configurable to monitor a single transformer or an entire fleet of transformers to support a customer’s centralized approach to asset management

TMDS™ architecture uses models that work with rule-based logic, derived from accepted IEEE/ANSI guidelines, to perform correlations on measured and calculated data

TMDS™ turns transformer monitoring data into actionable information through diagnostic and prognostic messaging

TMDS™ - 24/7 expert looking after your most valuable asset

Is the monitored parameter normal?

Is there a detectable trend?

If so, how important is it?

Any operational risk?

Any historical behavior associated with the deviation?

How are the peer phases or other units?

Any correlation with other monitored parameters?

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Efficient data acquisition

TMDS™ can detect statistically significant breakouts before hard limits are reached to avoid nuisance trips and alarms, far exceeding existing monitoring concepts of simple measurement of operative condition with pre-fixed limits. Only meaningful data is retained to support correlation between variables.

TMDS™ data handling process

Performs continuous calculations and diagnosis

Assesses deviations from normality

Compares historical behavior of correlated variables, peer phases and similar monitored units

Sends report encompassing the observed deviation and behavior of other monitored phases/units

Recommends maintenance activity to address abnormal operation

Suggests loading recommendations

Provides overview of possible consequences (prognostics) if current trend or parameter deviation continues.

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Rule

Prognosis and correlation model (rule/table based)

Complete data access

Customer has 24/7 access to current operational data, trends, alarm history and diagnostic/prognostic messaging from a central location or remotely.

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TMDS™ creates statistical definitions (mean, standard deviation with 95% confidence interval) during defined learning period.

Statistical definition changes are monitored for potential statistical breakouts by analyzing shifts of means and spread of standard deviations.

Duval’s analysis was performed. In case gas formation shows stability, no further action is recommended. TMDS™ will re-assess Duval’s analysis within 24 hours. Region of Duval’s Triangle = T2 - Thermal Fault, 200(degrees) C < T < 700 (degrees) C. Reduce load by 25 percent and re-assess transformer behavior. In case it persists, must undertake immediate internal inspection to establish cause of fault.

Cooling system model- Cooling system

monitoring- Cooling system control

Moisture model- Paper moisture

calculation using thermal model and Oommen curve analysis

Cumulative aging model- Accelerated aging derived

from hot spot temperature

DGA model- H2, C2H4, C2H2,

C2H6, CH4,O2

CO, CO

Trending model- Trending analysis

Operational thermal load limit models - Hot spot temperature for

new load point

IEEE/IEC thermal model- Ambient temperature- Oil temperature- Winding temperature- Hot spot temperature

Bushing model- Relative capacitance deviation

LTC monitoring model- Evaluation of position

indication, contact wear and torque

Variables monitored, depending on sensors installed, include: 1. Winding temperature

2. Top and bottom oil temperatures

3. Ambient temperature

4. Load current

5. Fan motor current

6. Oil flow (pump motor)

7. Moisture in oil

Aquaoil

Vaisala

8. Dissolved gas in oil

Multi-gas Serveron TM8

Siemens GAS-Guard 8

Kelman MULTITRANS

Single-gas Calisto

Hydran

9. Bushing condition

Doble IDD

HSP

10. LTC monitoring

11. Oil level

Actionable information

Delivers statistically relevant abnormal operating data and alarm conditions

Indicates potentially related or causal relationships between transformer components and alarmed condition

Provides maintenance support to address abnormal operation

Suggests loading recommendations through models using actual field data.

Self diagnostic

TDMS™ automatically detects bad sensor data to avoid false diagnosis.

Select from a suite of analysis applications. The following transformer specialist models are provided with TMDS™:

Bushing relative capacitance deviationEvaluation of bushing insulation condition.

Insulation moistureEvaluation of oil moisture condition and estimated moisture in paper.

ThermalHot spot evaluation by ANSI, IEC and Siemens proprietary methods.

Ageing and life expectancyEvaluation of relative loss of life and relative ageing by ANSI, IEC or ABNT methods.

Cooling system monitoring Evaluation of proper cooling system operation by monitoring the load current of the fan groups and oil or water flow (depending on the cooling system).

Siemens provides a comprehensive suite of transformer life-cycle management solutions specifically designed to meet your needs.

TMDS™

Supports a central diagnostic strategy where responsibility for fleet wide asset analysis and budget preparation is centralized. Field teams are typically dispatched by central maintenance or asset management groups.

Flexible architecture

Data available to enterprise data management system via OPC compliant interface to reduce cost of database management

Fiber optic ring arrangement for improved system reliability

Communicates with sensors by serial, analog and digital interfaces

Supports fiber optic and wireless based communication mediums

Can be combined with other asset monitoring systems via substation gateway.

Sensing technology agnostic

Due to the large availability of sensors in the market, TMDS™ is designed to support data acquisition from different manufacturers’ sensors.

Supports customer preference in transformer sensing technologies

Allows customer to incorporate appropriate sensing technology based upon transformer importance.

Complete data access

Customer has 24/7 access to current operational data, trends, alarm history and diagnostic/prognostic messaging from a central location or remotely.

Configurable for legacy transformers

Legacy transformers are unique in that they each have a specific operational history. Siemens TDMS™ allows easy customization of alarm levels, taking into account the specific behavior of each transformer, improving diagnostics quality.

Conservator oil volumeProvides advanced notification of conservator oil volume before reaching lowest acceptable level.

Cooling system controlControls the cooling system by calculating the future hot spot as a function of the current loading and temperature, also executing periodical cooling groups exercise.

Dissolved gas-in-oilEvaluation of limit values of gas generation in oil (depending on sensors installed, may include methane, ethylene, acetylene, ethane, carbon dioxide, hydrogen, oxygen and carbon monoxide). Analysis and indication of incipient faults using the Duval triangle CO2/CO ratio and TDCG level (total dissolved combustible gases) methods.

LTC monitoringEvaluation of position indication, contact wear calculation and torque for comparison with learned values.

TMDS™ Smart Monitor

The TMDS™ Smart Monitor supports a distributed diagnostic strategy where responsibility for responding to alarms and providing diagnostic expertise is regionally distributed. Field teams are self-sufficient in assessing asset condition, performing tests and arriving at corrective actions to be taken.

TMDS™ can easily be installed on new or legacy transformers from any manufacturer utilizing existing sensors

Comprehensive data requires powerful analytical tools

Siemens’ answers for transformer monitoring

Differences in functionality and architecture between TMDS™ and TMDS™ Smart Monitor

TMDS™ TMDS™ Smart Monitor

Provides monitoring and diagnostics for transformers in one or across multiple substations

X Stand alone monitor for single transformer

Provides advanced detection of abnormal conditions

X X

Supports customer preference in sensing technologies

X X

Automatically detects bad sensor data to avoid false diagnosis

X X

Provides maintenance support and loading recommendations to address abnormal operation

X X

Provides overview of possible consequences (prognostics) if current trend or parameter deviation continues

X X

Location of historical data and diagnostic information

Central TMDS engineering server Smart Monitor flash memory

Access to data and diagnostic information Active monitoring remotely via customer intranet

Active monitoring via Smart Monitor touch screen or remotely via Smart Monitor web

server

Cooling system control X X

Creates and monitors statistical definition for multiple parameters

X

Performs correlation between multiple parameters and across multiple transformers

X

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TMDS™ provides advanced charting capability based on transformer operational data. In this example, a change in bushing capacitive deviation with no significant change in line voltage indicates a loss of an intermediary capacitive layer. TMDS™ issues a diagnostic describing the event and recommends corrective action while also providing future trend and prognosis.

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Subject to change without prior notice. The information in this document contains general descriptions of the technical options available, which may not apply in all cases. The required technical options should therefore be specified in the contract.