Severe pollution and harsh weather are one of the main issues for electric utilities causing flashovers and unplanned line outages. Currently, there is no pollution measurement information across the network. This project will use insulator leakage current monitoring 
sensors to capture and share information remotely. This will help characterise the risk of equipment degradation due to pollution and assist with designing and maintaining Overhead Lines (OHLs) in pollution-high-risk areas of the network. With this, early design mitigation 
and maintenance procedures can be carried out to prevent faults due to flashovers. 

Benefits

If the system can reduce the number of unplanned outages caused by flashovers and/or the need to carry out maintenance, then this will reduce the costs for consumers. Financial penalties for faults will also be avoided. Having data regarding pollution risks could be useful information for communities to take steps to reduce pollution risks. 

This project will seek to capture information that can characterise the risk of asset degradation from pollution. A short section of the 132kV OHL case site will be used as the innovation use case.

Data on the frequency of flashovers and their cause will be determined after the results of the trial, so at this stage the CBA conducted reflects the minimum investment case incorporating a risk factor using a simple probabilistic method. The risk analysis considered the below risks:

• Flashovers/faults are not caused by pollution.
• The reasons for the faults and flashovers faults were not properly diagnosed and continue to occur regardless of the implementation of the pollution monitoring projects.
• Despite information obtained on pollution and remedial design actions, flashovers due to pollution still occur.

The CBA compares the innovative monitoring system scenario with the counterfactual scenario of not installing the monitoring system at all in a short section of the extreme case site and so a high frequency of flashovers continues to occur. Benefits considered account for the cost savings from outage avoidance and ignore any other co-benefits at this moment. Therefore, the potential lifetime risk-adjusted cost benefits have been calculated as follows –

• Counterfactual (“do nothing”) base case: Outage cost (61 outages per lifetime x £12,000) = £732,000
• Innovative monitoring system case: Outage cost (8 outages per lifetime x £12,000) = £96,000
• Innovative monitoring system case: Monitoring system cost (supply £120,435 + installation £1,050) =£121,485
• Net risk-adjusted cost benefit: 66.7% x (£732,000 – £96,000) – £121,485 = £302,727

If this cost saving is capital budgeted considering our model’s discount rate and depreciation is estimated to £108,288. 

Main assumptions considered:

• Asset life 45 years
• Lifetime flashover frequency scenarios for the risk analysis 10, 20, 40 faults.
• Average flashover outage cost £12k
• Average of 61 outages per lifetime at the case site
• Drop in faults using monitoring systems assumed 8 outages at case site per lifetime.
• Average outage duration 3 hours
• Probability of any kind of flashovers to occur 66.7%

The results showed that, the potential benefits considering risk are estimated to be at least £303k only from the avoidance of outages. The trial will help obtain more data on the cause of the degradation, with cost estimations being revisited on project completion. If successful, the dissemination of learnings can lead to further benefits being realised across similar schemes.