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Asset management For the
utilities industry.
Presented By :
Syed Atif Naseem
Problem and Challenges:
• Electric utilities face regulatory and public pressure to achieve two
opposing goals: making overdue upgrades while holding down costs
and rates to customers.
• Following an investment wave during the 1970s and 1980s,
transmission and distribution (T&D) companies put far less money
into improving their networks over the next few decades
• Now those networks are nearly obsolete and need enhancements to
improve grid availability and security and to bring renewable energy,
distributed generation, and other advanced technologies online
Problem and Challenges
• As the costs of remote-monitoring gear and analytical software
continue to fall, we see promising opportunities for T&D companies
to make their asset-management programs more productive.
• Advanced analytics, using real-time performance data and predictive
algorithms, can help T&D firms prevent asset failures, concentrate
asset-management efforts on critical assets, avoid excess
maintenance work or premature asset replacements, and
institutionalize the valuable knowledge of in-house experts
Problem and Challenges
• Compared to dealing with equipment failures as they occur or
following overly conservative maintenance protocols, experience
suggests that an analytics-powered approach to managing assets can
bring down costs, improve customer satisfaction, and increase the
reliability of T&D networks.
• And since asset management can account for 20 to 30 percent of a
transmission or distribution company’s operating expenses and 15 to
20 percent of its capital expenditures (excluding capital spending to
support growth), the savings opportunities alone can be significant
Problem Statement
• Varying age & condition health
• Poor performance of Asset over longer period
• Failure of Asset
• End of life of Asset
• Unplanned outage
• Unreliable power supply
Objective
• Using advanced analytics to manage T&D assets
• Development of Asset Health Index model for assets in our scope
• measures of Asset Criticality for assets in our scope
• An integrated analytical model for devising an asset-management
plan for a transmission or distribution network.
Asset Fleet for Utility Industry
• Over head Structures
• Over head Conductors
• Cables
• Zone substations
• Distribution transformers
• Distribution switch gear
• Secondary system
Asset management before the age of analytics
• Without standards, T&D firms have had to create asset-management plans
of their own. Typically, companies turn to their engineers and maintenance
workers to determine, largely on the basis of their experience, when and
how assets should be serviced.
• At many T&D companies, asset management has mostly been a matter of
maintaining and replacing assets according to fixed schedules that might
have been established years earlier.
• For example, it is common for T&D companies to check the quality of the
oil in their power transformers every two to three years, regardless of the
actual rate at which oil quality worsens.
• This sort of routine-based method has endured for several reasons. It is
easy to document and report to regulators, simple to implement, and
highly predictable, which helps with planning spending and investments.
Asset management before the age of analytics:
Draw Backs
• Maintenance programs tend to vary across companies.
• Even among departments within the same company, there is typically
no standard maintenance framework.
• A unit responsible for overhead power lines might use sophisticated
measures of asset criticality and health to decide when maintenance
is needed, while auxiliary systems and high-voltage units have no
asset-management system at all
• When various departments follow different approaches to
maintaining their assets, management has much more difficulty
comparing their effectiveness and allocating resources efficiently
Building an analytical approach to asset
management
• T&D companies can manage assets more efficiently thanks
to improvements in technology
• Sensors, communications devices, and other hardware that allow objects
to be tracked and controlled remotely have become increasingly affordable
and reliable
• So have the analytical tools for processing, interpreting, and responding to
data from equipment
• These shifts make it possible for T&D companies to retire the old model of
relying on specialists to set maintenance schedules based on experience in
favor of a flexible, streamlined, and analytically rigorous approach that
uses real-time performance data and predictive models to guide asset-
management decisions
Building an analytical approach to asset
management
• Three essential elements of an asset-management system powered
by analytics:
1)measures of asset health, which indicate the probability that assets
might fail
2)measures of asset criticality, which gauge the importance of those
assets to clients, employees, regulators, and other people and
organizations that rely on them.
3) an asset-management decision model that combines asset health
and criticality measures with executives’ priorities to recommend a
comprehensive plan for asset maintenance and replacement across a
transmission or distribution network.
Risk Based Preventive replacement policies (Asset Health Index + Criticality)
• Positives:
• Takes into account assed health calculated based on data in central system
• Takes into account asset criticality
• Efficient allocation of replacement budget
• Negatives:
• Requires collection & processing of data about individual assets
Industry Case Study
POWER TRANSFORMERS FLEET MANAGEMENT
POPULATION, RATINGS AND AGE STATISTICS
Power Transformer Age Profile:
• The average age of all our zone substation transformers is 31 years.
Methodology Used
For Switch Gear
Software
• Matlab
• Python
• PRISM model checker
Results
• Prediction of Asset performance over a long period.
• Predict the rate at which Asset deteriorate.
• Replace the asset before failure.
• New inspection technique implemented
Project Schedule
Thank You

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Asset management

  • 1. Asset management For the utilities industry. Presented By : Syed Atif Naseem
  • 2. Problem and Challenges: • Electric utilities face regulatory and public pressure to achieve two opposing goals: making overdue upgrades while holding down costs and rates to customers. • Following an investment wave during the 1970s and 1980s, transmission and distribution (T&D) companies put far less money into improving their networks over the next few decades • Now those networks are nearly obsolete and need enhancements to improve grid availability and security and to bring renewable energy, distributed generation, and other advanced technologies online
  • 3. Problem and Challenges • As the costs of remote-monitoring gear and analytical software continue to fall, we see promising opportunities for T&D companies to make their asset-management programs more productive. • Advanced analytics, using real-time performance data and predictive algorithms, can help T&D firms prevent asset failures, concentrate asset-management efforts on critical assets, avoid excess maintenance work or premature asset replacements, and institutionalize the valuable knowledge of in-house experts
  • 4. Problem and Challenges • Compared to dealing with equipment failures as they occur or following overly conservative maintenance protocols, experience suggests that an analytics-powered approach to managing assets can bring down costs, improve customer satisfaction, and increase the reliability of T&D networks. • And since asset management can account for 20 to 30 percent of a transmission or distribution company’s operating expenses and 15 to 20 percent of its capital expenditures (excluding capital spending to support growth), the savings opportunities alone can be significant
  • 5. Problem Statement • Varying age & condition health • Poor performance of Asset over longer period • Failure of Asset • End of life of Asset • Unplanned outage • Unreliable power supply
  • 6. Objective • Using advanced analytics to manage T&D assets • Development of Asset Health Index model for assets in our scope • measures of Asset Criticality for assets in our scope • An integrated analytical model for devising an asset-management plan for a transmission or distribution network.
  • 7. Asset Fleet for Utility Industry • Over head Structures • Over head Conductors • Cables • Zone substations • Distribution transformers • Distribution switch gear • Secondary system
  • 8. Asset management before the age of analytics • Without standards, T&D firms have had to create asset-management plans of their own. Typically, companies turn to their engineers and maintenance workers to determine, largely on the basis of their experience, when and how assets should be serviced. • At many T&D companies, asset management has mostly been a matter of maintaining and replacing assets according to fixed schedules that might have been established years earlier. • For example, it is common for T&D companies to check the quality of the oil in their power transformers every two to three years, regardless of the actual rate at which oil quality worsens. • This sort of routine-based method has endured for several reasons. It is easy to document and report to regulators, simple to implement, and highly predictable, which helps with planning spending and investments.
  • 9. Asset management before the age of analytics: Draw Backs • Maintenance programs tend to vary across companies. • Even among departments within the same company, there is typically no standard maintenance framework. • A unit responsible for overhead power lines might use sophisticated measures of asset criticality and health to decide when maintenance is needed, while auxiliary systems and high-voltage units have no asset-management system at all • When various departments follow different approaches to maintaining their assets, management has much more difficulty comparing their effectiveness and allocating resources efficiently
  • 10. Building an analytical approach to asset management • T&D companies can manage assets more efficiently thanks to improvements in technology • Sensors, communications devices, and other hardware that allow objects to be tracked and controlled remotely have become increasingly affordable and reliable • So have the analytical tools for processing, interpreting, and responding to data from equipment • These shifts make it possible for T&D companies to retire the old model of relying on specialists to set maintenance schedules based on experience in favor of a flexible, streamlined, and analytically rigorous approach that uses real-time performance data and predictive models to guide asset- management decisions
  • 11. Building an analytical approach to asset management • Three essential elements of an asset-management system powered by analytics: 1)measures of asset health, which indicate the probability that assets might fail 2)measures of asset criticality, which gauge the importance of those assets to clients, employees, regulators, and other people and organizations that rely on them. 3) an asset-management decision model that combines asset health and criticality measures with executives’ priorities to recommend a comprehensive plan for asset maintenance and replacement across a transmission or distribution network.
  • 12. Risk Based Preventive replacement policies (Asset Health Index + Criticality) • Positives: • Takes into account assed health calculated based on data in central system • Takes into account asset criticality • Efficient allocation of replacement budget • Negatives: • Requires collection & processing of data about individual assets
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  • 17. Industry Case Study POWER TRANSFORMERS FLEET MANAGEMENT
  • 18. POPULATION, RATINGS AND AGE STATISTICS
  • 19. Power Transformer Age Profile: • The average age of all our zone substation transformers is 31 years.
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  • 26. Results • Prediction of Asset performance over a long period. • Predict the rate at which Asset deteriorate. • Replace the asset before failure. • New inspection technique implemented