How CLP’s asset management was transformed by EA Technology | EA Technology
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How CLP’s asset management was transformed by EA Technology


  • 24 June 2021

  • EA Technology

Case Studies - HV

CLP Power is a global energy utility with over a century of history behind it. It was founded in Hong Kong in 1901 and now supplies power to 80% of the city’s population though its reliable vertically integrated supply model.

Background


With so much experience and expertise built up over generations, CLP already had quite an efficient operation when it came to management of its electrical assets.The health of the components of its network was being modelled based on expected life, so maintenance could be scheduled to minimise the risk of failure and to minimise downtime.What the system lacked was precision. Without a sensitive means of assessing the health of assets, there is always the risk that an overcautious approach can result in unnecessary replacements, or that the lack of precise monitoring can miss potential failures.


Actions


CLP Power asked EA Technology to collaborate with them on the design of a new transformer model. Following condition-based risk methodology (CBRM) and specific testing of the expected operating conditions, we redesigned key components such as the:
• Tapchanger;
• Connections;
• Cooling system;
• Insulating oil; and
• Transformer system

The System


Supporting the changes we helped design was the pioneering Smart Interventions process. This factors current investment into every asset and creates a cost– benefit analysis that determines precisely which assets should be first in line for investment to get the absolute most out of any intervention.Whereas the existing intervention model was quite blunt,operating at asset level, the new system could zoom in on individual components of each asset, allowing a precise and highly efficient care package to be designed.It also integrates new technologies such as online dissolved gas analysis, which builds up a precise picture of risk over the whole network.


Conclusion


The new system has had a significant effect on the efficiency of CLP Power’s maintenance scheduling. With this new precision, optimal maintenance scheduling can be carried out based on asset type, age and condition.This has meant that the guesswork and assumptions have been taken out of the equation. Some maintenance intervals were shortened; others were lengthened. That means breakdowns are less common and unnecessary maintenance work has all but stopped.The utility can now enter the amount of investment it wants to put on maintenance, and the cost benefits of prioritised intervention can be worked out over the longer term.CLP Power now has complete transparency over the assets as they are replaced, so that eventually a complete picture of risk over highly complex networks can be achieved at the touch of a button.