Failure of transmission towers or their associated components can cause a cascading failure involving a number of adjacent towers along the line. Repair is very costly: it involves replacement of overhead lines and towers affected, and includes other costs associated with power disruption and litigation. Therefore utilities spend a significantly amount of money on inspection and maintenance programmes to prevent failures occurring. Over the RIIO-ED1 period it is anticipated nearly UK DNO’s will spend £1B on this activity alone.

The main failure mechanisms are wear or corrosion related. There is a need for a decision making process that can be adapted in response to known wear and corrosion rates in each particular area, so that towers at risk of failure can be identified more effectively and maintained to avoid unexpected failure.

Objectives

To develop a model that considers how tower components are affected by corrosion and wear due to particular environmental conditions. This model assesses tower components’ condition estimates their lifetime expectancy at specific sites providing invaluable support to the decision making process

Method

The development of the project at PNDC comprised the following steps:

  • Identification of factors with highest impact on corrosion process through literature review
  • Review of state art of the hazard models to predict corrosion
  • Creation of database containing information on tower components condition and environmental factors on site, e.g. temperature, wind speed, pollution concentration, etc.
  • Correlation study to identify factors that have the highest impact on the deterioration of towers components
  • Develop model and implement model to determine remaining life of components

Outcome

A hazard model was created and implemented for particular areas of the transmission network. The model helps identifying areas were corrosion process develops faster and estimate remaining life. The model is expected to be integrated in the CBRM tool and complement existent models.

  • Estimation of remaining tower components life
  • Visualisation of deterioration progress in particular areas – Survival curves
  • Rating of components risk of failure

Results

  • £1bn Estimated Inspection & Maintenance spend for UK DNOS over RIIO-ED1
  • 1,543 towers data included in study
  • 30 circuits assessed as part of study
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