As our existing HV cable assets age over time, and future demand from consumers increases as they transition to low carbon technologies, we need to optimise investment planning balancing asset health interventions and asset reinforcement that minimises the impact to consumers through Customer Interruptions (CI)/Customer Minutes Lost (CML).
The Hi-5 project, is looking to understand the time to failure indicators on our HV cable assets through the installation of low cost monitors. This insight will be used to support changes to our cable health methodologies, and therefore our future asset investment needs.
Benefits
HV Faults
During 2023- 2024 NGED spent c.£20m on repairing UG HV unplanned cable faults with an additional spend of £18.5m on CML/CI penalties. This was across around 2,103 events giving an average cost per fault of c.£18,000. This cost is a conservative estimate as fault repairs can significantly vary dependent on location and nature of the fault. Recent efficiency drives are aiming to reduce unit fault costs across the business, future costs maybe lower, however at this point we do not have confidence to use values to support forecasts. Additionally, the average CML/CI costs had a annual social cost estimated to be c.£60m. Given that NGED has 44,200km of HV UG cable it suggests an overall annual UG HV fault rate across the business of 5 faults per 100km of HV cable per year across the four NGED license areas.
The relationship between UG network faults and cable age is very complex, for example, circuits with the highest fault count may not necessarily be the circuit containing the greatest length of ageing cables. Distribution of faults are not even across the network, some geographical areas have high concentration of fault rates. Whilst an age-based asset replacement approach may result in greatest volumes of aging asset being replacement it lacks the targeted approach required to reduce fault rates and improve network reliability. Due to underground complexities, we are unaware of leading indicators of the relationship between aging/deteriorating assets and fault rates. HI-5 will identify network characteristics observed of pre-fault activity, it will also identify expected time to failure. By improving our understanding of time to failure we can ensure we balance avoiding the fault and replacing cable too early. With this knowledge an optimised risk-based approach to network replacement targeting circuits most likely to fail can be adopted.
A conservative estimation of reducing UG HV faults by 10% by the end of ED3 could save c.£3.7m per year in overall fault costs, with a further saving of c.£5m per year in societal costs
Cable replacement
During ED1 NGED replaced around 41km of non-load related UG HV cable, replacing a further 7.5km during the first 2 years of ED2, the total amount of expenditure being c.£8.1m. In the next 25 years 8454 Km of UG cable will be reaching mean life expectancy (87 years) which is c. 19% of the total underground network. If all cable were to be replaced at end of asset life the total spend of this non-load related replacement would be c.£1.5b. This level of replacement increases substantially out to 2059 where an additional 9,000 km will need to be replaced.
Learnings
Outcomes
A further three years remain in the project lifecycle; therefore, measurable outcomes are currently limited. However, significant progress has been made in the deployment of monitoring devices and in demonstrating their applicability across a range of sites, switchgear types, and HV network configurations.
Lessons Learnt
Initial waveform analysis of captured waveforms has generated valuable early insights, strengthening the anticipated outcomes of the Hi-5 project. Early-stage system development and data interrogation have identified additional learning opportunities beyond the original project scope, expanding the potential value of the deployed monitoring infrastructure.
In particular, learnings derived from HV waveform analysis have demonstrated clear applicability to other voltages. Analysis of HV waveform data has shown the capability to detect network activity at other voltage levels, revealing previously unrealised potential to support fault identification and localisation at other voltage levels. This capability could enable the development of additional enhanced asset management approaches, improving response times and reducing customer impact through faster and more targeted intervention. This capability potentially reduces the need for widespread monitoring deployment. Instead, HV-level insights could be used to effectively “range in” on areas of poor network performance, enabling more targeted and efficient work programs.
Initial findings using the CNAIM methodology suggest that the outputs have the potential to be transferable to other asset classes, including mixed networks and overhead (OH) networks.
