Utilities in North America installed a large number of transformers from the early 1960’s to the end of the 70’s. As a result of diminished capital spending since that time, many transformers are approaching the end of their technical life and most have reached the end of their financial life. Driven to reach an increasingly higher level of reliable electrical service, the trade-off for diminished capital investment is to spend more on equipment maintenance. However, many utilities operate under budget restraints and need to get the biggest-bang-for-their-buck by allocating maintenance spending based on need within the transformer fleet. In addition, T&D system operators are developing other condition-based asset management tools, techniques and criteria to manage these critical assets as a way of maintaining reliable operation at a reasonable level of risk and expense.
At this time, a significant increase in failure rates is not yet apparent for this older population. However, it is also apparent that substation transformers, like all electromechanical equipment, do not have an infinite technical life. T&D utilities that, for the most part, replace transformers only for capacity increases or failures are now starting to rethink their approach. As the risk of failure increases with deteriorating condition, and as the risk of consequential costs rise, proactive transformer replacement has started to become a strategic option.
Although this situation has become clearer to North American utility managers, available capital to reinvest in this aged infrastructure is not readily available and projections of future peaks of needed capital, required to maintain reliable service across the system, are very large indeed. Therefore, "Condition-Based" Strategies are not only being applied to prioritize maintenance expense, but the same condition ranking systems are being applied to forecast and allocate future capital spending.
The challenge facing the industry today is in leveraging the most out of existing assets without reducing customer service, while increasing the stakeholder’s value. This requires operations and maintenance managers to fully understand the probable condition of old and often highly loaded units. In many cases, this requires "re-rating" the transformer's planned loading capacity for normal and contingent operation. In many cases, use of these planned loading limits may be dependent on the condition of the unit. Refurbishment or options for enhancing transformer performance to reduce temperature, increase life and/or increase load capability are often considered as O&M options to defer capital spending on new equipment.
The following chart indicates that optimization of risk, based on limited capital and O&M spending and increased loading limits, is the ultimate management challenge that affects customer satisfaction and bottom-line performance in today's electric utility environment. This challenge can only be met with a thorough understanding of transformer health and criticality on the system.
Utility managers are today using condition-based tools that rank the health and criticality of the equipment, as the starting-point for prioritizing maintenance expenses, for proactive capital reinvestment for groups of transformers or for making decisions about replacement of individual problem units on the system.
Determining Health and Criticality for Operating Power Transformers
Statistical methods, based on historical failure modes, are often used to establish the probable condition of all units or groups of transformers on the system. However, this method cannot identify the condition state or vulnerability of individual operating units. Unfortunately, there is no single scientific method available and condition evaluation is often subjective. Evaluation methods are often modified or limited by the availability of information from the manufacturer or from the system's operations and maintenance records. Added to this, the skill level and experience of the people involved in the process are a key variable in making decisions related to the quality of the available information and, subsequently, the probable condition of the unit. A complete appraisal method for an individual unit will often involve field inspections and testing. This decision often depends on the feasibility of taking units out of service, balanced against the importance of the unit on the system and the related cost.
The process for benchmarking the probable condition of an individual unit, compared to other units on the system, is often controlled by moving through three gates or levels:
Level 1 - Data and Design Analysis
Level 2 - Energized and De-Energized Testing
Level 3 - External and Internal Inspection
Condition evaluation methods are subjective and are generally based on the quality of information, requiring the results to be weighted depending on each of the factors or condition indicators that have been selected. Typical factors used for evaluation are related to the equipment design, environment, usage and historical maintenance or testing data and are listed in the following Table.
It is normal to select up to 10 factors (Condition Indicators) for Level 1 evaluation, which can be used as a preliminary process (and as the only method) for evaluating large groups of units. When used with transformer priority (discussed in the following section), Level 1 ranking can provide the basis for deciding if subsequent Level 2 and 3 inspection and testing, using as many as 25 or 30 factors (Condition Indicators) will be required for evaluating smaller groups of critical units.
As we have seen from the criteria given in the above Table, many factors must be considered and weighted against each other to result in a realistic condition evaluation. However, the probable condition of the internal insulation is usually a key consideration due to the fact that the condition is, for the most part, "irreversible". Spontaneous and non-spontaneous events will have combined to lead to this irreversible condition. Years of use or high loading, frequent and/or close-in faults, high moisture or oxygen in oil over time, high measured furan levels and/or low measured degree of polymerization (DP) are all key indicators of this condition.
However, defective ancillary equipment, bushings, cooling systems, tap changer mechanisms etc, can be placed in the "as new" condition with a scheduled maintenance outage. The decision to invest capital dollars in refurbishing the unit is often based on a thorough economic evaluation. It is also a fact that failures from internal insulation damage or deficiency often result in major damage or even catastrophic failure with long-term loss of service and severe financial implications. Determination of the associated risk of operation for condition-based loading limits, and selection of appropriate margins to mitigate risk, should consider all of the above factors. Additional factors for more detailed Level 2 condition evaluation are discussed later in this article.
Establishing Group Ranking and Priority
For most substation transformers, knowledge about the probable condition of an individual unit does not in itself provide the basis for making good maintenance, loading or capital spending decisions. As an example, two units of equally poor condition may result in one being placed on a high level of care and attention while the other is placed on a "run-to-failure" status. It is important to compare the unit's probable condition or Weighted Condition Factor (WCF) versus the level of its importance or criticality for future use on the system (TPI). For the utility to determine this importance, the criteria must be selected by a cross-section of appropriate asset managers, maintenance staff, operations managers and engineers. These criteria can be determined by canvassing a list of the above selected people and by voting based on the most/least important factors for future use.
Typical factors are shown in the Table below. The individual unit's Transformer Priority Index (TPI) can be calculated by scoring the available data for the unit being evaluated against a quantitative or qualitative subset for each of the selected factors.
The combination of the individual unit's Weighted Condition Factor and Transformer Priority Index can be used to make decisions about the extent to which the unit can be operated and maintained. For instance, a unit rated in poor condition, and in a position vital to the system's operation would warrant a high level of attention; whereas a unit rated in similarly poor condition but not crucial to future system operation, may be operated with a minimum of attention.
Testing and Technologies as Indicators for Detailed Condition Assessment
Selection of the applicable and preferred types of testing, for use as an indicator for Level 2 condition evaluation, will depend on the transformer design area or ancillary component of interest. In addition, the selection of testing type will depend on the number of units in the assessment process, criticality of the unit on the system, available skill sets and cost associated with the available technology and test methods. A list of available on-line and off-line testing techniques and technologies is shown on the following chart.
Applicable Transformer Design Area or Ancillary Components.
1. Solid Insulation (Moisture, Dirt, Destruction)
2. Magnetic System (core compression,
component to tank insulation damage)
3. Windings (buckling and other deformation)
4. Transformer Oil Condition
5. Systems for oil cooling, treatment and
protection
6. Bushings
7. Voltage Regulation and contact systems
The following chart makes the connection between the test type and it’s applicability to the above listed area of interest.
An example of the Condition Ranking method is shown in the following Table. The units are ranked into four groups: Red, Yellow, Blue and Green, indicating the level of risk associated with operating older units, and can be used as a "Decision Matrix" for all areas of Asset Managementv
For the purpose of determining risk associated with health and criticality it is necessary to couple condition assessment with failure probability. Transformer failure rate is a subject for debate throughout the industry and very little real failure data is available. However, despite the fact that some units last for 80 years, most fail in their middle years and this depends on many factors such as design, application on the system, loading, type of ancillary equipment, systems protection etc.
As a rule of thumb the following simple table applies to estimating failure probability versus assessed condition.
Condition Rating Failure Rate
Good 0.6%
Satisfactory 1.0%
Fair 1.5%
Poor 2.0%
Bad 3.0%
Current use of condition-based tools increasingly provides T&D asset managers with the ability to make intelligent decisions about allocation of maintenance expenses and potentially to determine future transformer loading limits as part of a condition-based dynamic loading program. In the future, risk and financial models, based on a better understanding of the health and criticality of substation transformers, will be required to support a "Risk-Based Reinvestment Strategy" aimed at predicting the future peaks of capital needed to operate the system at a predetermined level of reliability.
REFERENCE
David J. Woodcock is V P of Business Development with Weidmann Systems International Inc.
At this time, a significant increase in failure rates is not yet apparent for this older population. However, it is also apparent that substation transformers, like all electromechanical equipment, do not have an infinite technical life. T&D utilities that, for the most part, replace transformers only for capacity increases or failures are now starting to rethink their approach. As the risk of failure increases with deteriorating condition, and as the risk of consequential costs rise, proactive transformer replacement has started to become a strategic option.
Although this situation has become clearer to North American utility managers, available capital to reinvest in this aged infrastructure is not readily available and projections of future peaks of needed capital, required to maintain reliable service across the system, are very large indeed. Therefore, "Condition-Based" Strategies are not only being applied to prioritize maintenance expense, but the same condition ranking systems are being applied to forecast and allocate future capital spending.
The challenge facing the industry today is in leveraging the most out of existing assets without reducing customer service, while increasing the stakeholder’s value. This requires operations and maintenance managers to fully understand the probable condition of old and often highly loaded units. In many cases, this requires "re-rating" the transformer's planned loading capacity for normal and contingent operation. In many cases, use of these planned loading limits may be dependent on the condition of the unit. Refurbishment or options for enhancing transformer performance to reduce temperature, increase life and/or increase load capability are often considered as O&M options to defer capital spending on new equipment.
The following chart indicates that optimization of risk, based on limited capital and O&M spending and increased loading limits, is the ultimate management challenge that affects customer satisfaction and bottom-line performance in today's electric utility environment. This challenge can only be met with a thorough understanding of transformer health and criticality on the system.
Utility managers are today using condition-based tools that rank the health and criticality of the equipment, as the starting-point for prioritizing maintenance expenses, for proactive capital reinvestment for groups of transformers or for making decisions about replacement of individual problem units on the system.
Determining Health and Criticality for Operating Power Transformers
Statistical methods, based on historical failure modes, are often used to establish the probable condition of all units or groups of transformers on the system. However, this method cannot identify the condition state or vulnerability of individual operating units. Unfortunately, there is no single scientific method available and condition evaluation is often subjective. Evaluation methods are often modified or limited by the availability of information from the manufacturer or from the system's operations and maintenance records. Added to this, the skill level and experience of the people involved in the process are a key variable in making decisions related to the quality of the available information and, subsequently, the probable condition of the unit. A complete appraisal method for an individual unit will often involve field inspections and testing. This decision often depends on the feasibility of taking units out of service, balanced against the importance of the unit on the system and the related cost.
The process for benchmarking the probable condition of an individual unit, compared to other units on the system, is often controlled by moving through three gates or levels:
Level 1 - Data and Design Analysis
Level 2 - Energized and De-Energized Testing
Level 3 - External and Internal Inspection
Condition evaluation methods are subjective and are generally based on the quality of information, requiring the results to be weighted depending on each of the factors or condition indicators that have been selected. Typical factors used for evaluation are related to the equipment design, environment, usage and historical maintenance or testing data and are listed in the following Table.
It is normal to select up to 10 factors (Condition Indicators) for Level 1 evaluation, which can be used as a preliminary process (and as the only method) for evaluating large groups of units. When used with transformer priority (discussed in the following section), Level 1 ranking can provide the basis for deciding if subsequent Level 2 and 3 inspection and testing, using as many as 25 or 30 factors (Condition Indicators) will be required for evaluating smaller groups of critical units.
As we have seen from the criteria given in the above Table, many factors must be considered and weighted against each other to result in a realistic condition evaluation. However, the probable condition of the internal insulation is usually a key consideration due to the fact that the condition is, for the most part, "irreversible". Spontaneous and non-spontaneous events will have combined to lead to this irreversible condition. Years of use or high loading, frequent and/or close-in faults, high moisture or oxygen in oil over time, high measured furan levels and/or low measured degree of polymerization (DP) are all key indicators of this condition.
However, defective ancillary equipment, bushings, cooling systems, tap changer mechanisms etc, can be placed in the "as new" condition with a scheduled maintenance outage. The decision to invest capital dollars in refurbishing the unit is often based on a thorough economic evaluation. It is also a fact that failures from internal insulation damage or deficiency often result in major damage or even catastrophic failure with long-term loss of service and severe financial implications. Determination of the associated risk of operation for condition-based loading limits, and selection of appropriate margins to mitigate risk, should consider all of the above factors. Additional factors for more detailed Level 2 condition evaluation are discussed later in this article.
Establishing Group Ranking and Priority
For most substation transformers, knowledge about the probable condition of an individual unit does not in itself provide the basis for making good maintenance, loading or capital spending decisions. As an example, two units of equally poor condition may result in one being placed on a high level of care and attention while the other is placed on a "run-to-failure" status. It is important to compare the unit's probable condition or Weighted Condition Factor (WCF) versus the level of its importance or criticality for future use on the system (TPI). For the utility to determine this importance, the criteria must be selected by a cross-section of appropriate asset managers, maintenance staff, operations managers and engineers. These criteria can be determined by canvassing a list of the above selected people and by voting based on the most/least important factors for future use.
Typical factors are shown in the Table below. The individual unit's Transformer Priority Index (TPI) can be calculated by scoring the available data for the unit being evaluated against a quantitative or qualitative subset for each of the selected factors.
The combination of the individual unit's Weighted Condition Factor and Transformer Priority Index can be used to make decisions about the extent to which the unit can be operated and maintained. For instance, a unit rated in poor condition, and in a position vital to the system's operation would warrant a high level of attention; whereas a unit rated in similarly poor condition but not crucial to future system operation, may be operated with a minimum of attention.
Testing and Technologies as Indicators for Detailed Condition Assessment
Selection of the applicable and preferred types of testing, for use as an indicator for Level 2 condition evaluation, will depend on the transformer design area or ancillary component of interest. In addition, the selection of testing type will depend on the number of units in the assessment process, criticality of the unit on the system, available skill sets and cost associated with the available technology and test methods. A list of available on-line and off-line testing techniques and technologies is shown on the following chart.
Applicable Transformer Design Area or Ancillary Components.
1. Solid Insulation (Moisture, Dirt, Destruction)
2. Magnetic System (core compression,
component to tank insulation damage)
3. Windings (buckling and other deformation)
4. Transformer Oil Condition
5. Systems for oil cooling, treatment and
protection
6. Bushings
7. Voltage Regulation and contact systems
The following chart makes the connection between the test type and it’s applicability to the above listed area of interest.
An example of the Condition Ranking method is shown in the following Table. The units are ranked into four groups: Red, Yellow, Blue and Green, indicating the level of risk associated with operating older units, and can be used as a "Decision Matrix" for all areas of Asset Managementv
For the purpose of determining risk associated with health and criticality it is necessary to couple condition assessment with failure probability. Transformer failure rate is a subject for debate throughout the industry and very little real failure data is available. However, despite the fact that some units last for 80 years, most fail in their middle years and this depends on many factors such as design, application on the system, loading, type of ancillary equipment, systems protection etc.
As a rule of thumb the following simple table applies to estimating failure probability versus assessed condition.
Condition Rating Failure Rate
Good 0.6%
Satisfactory 1.0%
Fair 1.5%
Poor 2.0%
Bad 3.0%
Current use of condition-based tools increasingly provides T&D asset managers with the ability to make intelligent decisions about allocation of maintenance expenses and potentially to determine future transformer loading limits as part of a condition-based dynamic loading program. In the future, risk and financial models, based on a better understanding of the health and criticality of substation transformers, will be required to support a "Risk-Based Reinvestment Strategy" aimed at predicting the future peaks of capital needed to operate the system at a predetermined level of reliability.
REFERENCE
David J. Woodcock is V P of Business Development with Weidmann Systems International Inc.
