UK Power Networks has over 24,000 km (comprising of over 280,000 spans) of HV overhead line conductors on its distribution network but holds limited information regarding their age and condition. Conductors are visually assessed from the ground, during routine full patrols, every twelve years. However, there is engineering consensus that visual assessments alone are not sufficient to determine the condition of overhead line conductors, since they only correctly assess the condition of conductors when deterioration of the conductor is at an advance stage and evidence of the deterioration is evident through stranding or bird-caging (deformation of strands) of the conductor. As a result, the existing replacement strategy on HV OHL conductors is reactive (apart from load related reinforcement), and HV OHL conductors are replaced when they have failed (post-fault repair). In UK Power Networks, faults on the HV overhead line conductors represent approx. 15% of the HV faults volume per annum. These faults result in Customer Interruptions (CIs) and Customer Minutes Lost (CMLs) affecting the quality of supply and the overall experience of the consumers.
Objectives
The objectives of this project include:
1. Developing and performing a set of tests which test the mechanical, structural and electrical parameters of the OHL samples.
2. Calculation of the deterioration rate and expected end of life for HV overhead line conductors.
3. Development of an algorithm that determines the condition and expected end of life for HV overhead conductors based on a set of attributes (e.g. age, location, size).
Learnings
Outcomes
A condition assessment was performed on the 291 overhead line conductor (OHL) samples supplied, using EA Technology’s standard OHL conductor assessment procedure. This procedure involves a combination of a visual examination of the individual strand layers and mechanical testing of selected strands; the exact tests undertaken vary slightly between conductor types.
From the results of the condition assessment, an expected remnant service life was calculated for each conductor. These estimates ranged from less than five years (considered end of life) to 20 years (the upper limit of estimation).
The full set of condition assessment results for all 291 conductor samples together with the final report is available on request.
Although the statistical analysis did find evidence of some correlation between degradation rates and proximity to coast for both ACSR and copper conductors, the variability in age at end of life would suggest that other factors are significantly influencing the results. There are a number of unknown variables and factors which it would be reasonable to expect have influenced the results to a degree, although the extent of this influence cannot be determined with the information available.
The results indicated there is some evidence that ACSR conductors deteriorate more rapidly near the coast, but distance to coast alone did not fully explain the variability in age at end of life, even after taking account of conductor type, greasing and corrosion zone. This is likely to be due to the small sample sizes after the effects of greasing and corrosion zone have been considered. Increasing the number of samples may help, particularly focusing on conductors that are closer to the coast (i.e. within 20 km of the coast) and conductors that are at or approaching end of life.
In addition, it may be important to consider what other factors may influence the rate of degradation. Other factors known to influence the rate of degradation of conductors is operating temperature and number of faults. Therefore, it is suggested that in future the analysis is extended to explore whether a deterioration algorithm based on location, temperature and fault records can be formulated.
Lessons Learnt
The analysis indicated that there is evidence to suggest that the expected service life for both ACSR and copper type overhead line conductor does reduce with proximity to the coast. This is to be expected, primarily due to the higher levels of sodium chloride in the atmosphere, a known aggressive pollutant for the metal/metal alloys used in the construction of conductor. However, the ability to explore this relationship was limited due to the sample sizes across the condition ranges.
Variability in age at end of life would suggest that other factors are significantly influencing the results. Increasing the sample sizes, with particular focus on conductors that are closer to the coast (i.e. within 20 km of the coast) and conductors that are at, or approaching, end of life could help strengthen the correlation between proximity to coast and expected service life.
In addition, it is recommended to explore whether information exists regarding operating temperature and number of faults experienced for the conductor samples assessed during this project. These are both considered to be contributing factors that influence the rate of degradation of the conductor and may be useful in the formation of a deterioration algorithm.
It is also recommended to investigate the feasibility of a collaborative project with other DNOs in order to expand the sample base and lead to results which are more statistically significant. A business review was then conducted and it was concluded that there will be no follow-on project due to the difficulty of collecting the volume of data required to achieve conclusive results.
