Issue link: https://fhpublishing.uberflip.com/i/736974
The four gas distribution network operators are jointly undertak- ing a network innovation allowance project with the aim of creat- ing a new methodology for modelling the risk value of assets which will be consistent across the four companies. Through the submission of GDN business plans, Ofgem could see that although the GDNs are fully reporting asset health, the probability of failure and deterioration of their assets, the report- ing lacks a consistent approach. The current method also does not allow for the justification for the transfer of investment across asset groups. Ofgem has an expectation that outputs are not only useful for comparing overall investment, in terms of the change in risk value generated by investment-driven changes to overall asset populations, but to enable GDNs to target investment on specific assets based on the optimum risk reduction value. The project is pioneering research into failure modes, prob- ability of failure and consequence analysis using both GDN supplied failure, investment data and industrially published data. This will facilitate the development of Event Tree models for the asset groups: mains, services, district governor, LTS pipelines and preheating systems. Although all asset groups will need to be scored on a mon- etised risk basis, the project was focussing on just these five groups to prove the concept as these groups represent approxi- mately 90% of total Capital Investment, but was then extended to 10 asset groups. Ofgem has indicated that it prefers the use of event tree analysis which will enable the benefits of expenditure across different assets to be compared and traded off, but there is some uncertainty over the level of detail required in reporting to satisfy Ofgem's requirements. A key part of the design phase will be determining the optimum level of detail required. GDNs may hold data at different levels of detail but a consistent level will be agreed during the project. If the project is successful and a methodology is finalised it will achieve value for customers by ensuring smarter spend- ing. The five initially targeted groups represent a Capex spend of around £1 billion across all four GDNs over the eight-year price control. By using the methodology, it is envisaged a reduction in spending of around 0.2% for GD2, the equivalent of £2 million. Risk trading will allow GDNs to ensure that asset risk removal is prioritised in a manner that is acceptable to stakeholders. Assets which pose the highest monetised risk relating to security of supply, process safety, public injury and environmental factors can be targeted. M o n e t i s i n g r i s k Bringing consistency to GDN outputs level of detail being explored has exposed some myths about what investment is actually achieving. WWU's analysis has revealed that death – the reason behind the acceleration of the replacement programme which will cost each GDN between £2-3 billion during this price control - is only the sixth biggest driver of the iron mains replacement programme. Instead the benefit is overwhelmingly environmental. WWU's asset strategy and performance manager Ian Dunstan said intervention plans in the future will likely be driven by consequence of action, or inaction rather than the health of the asset itself. But asset health will obviously still have an impact. SGN is utilising data to prioritise projects which will have the biggest impact on the assets deemed to pose the greatest risk to improve the efficiency of its programme. The common methodology for determining asset health being worked on within both the electricity and gas networks is forcing network operators to question why they are collecting data. Determining risk is a data hungry activity but it is difficult to sell the business case for its collection. Networks must also look beyond their own activity for outside sources of data they can use to their advantage, such as the freely available climate change data available from European project Copernicus. Electricity North West's head of asset management Jonathan Booth warned that there is "huge danger in using out of date data". He said networks have only just woken up to the fact that data is an asset in itself that needs as much maintenance as the pipes and wires. But data is not the only new asset networks must contend with. The rise of distributed generation has brought about new commercial contracts, and these must also be managed correctly to ensure they perform to their full potential. Here is an area where networks must make use of innovation funding to arm themselves with knowledge on these new assets. Data will have one final impact on how assets performance will be enhanced. The sheer volume of data points necessitates the use of soŽware that will render engineers the "thick part of the equation". This is already being demonstrated by soŽware such as Enel's smart grid technology in Milan. Who should undertake analysis saw for the first time a diversion of viewpoints. Some, understandably wish to keep hold of their new data asset, but others do not think network operators are currently the right organisations to get the best value out of that data. N NETWORK / 28 / OCTOBER 2016 ASSET PERFORMANCE ASSET BASE £ Total risk Probability of failure Consequence of failure Financial cost of failure DrivErS BEhiND iroN mAiNS rEplAcEmENT measure Distribution main (£million) Carbon 20,579,815 Joint 9,670,225 Loss of gas 5,705,568 Repair 3,019,890 Fracture 1,965,768 Death 1,922,155 Domestic 1,610,282 Survey 1,183,304 TMA order 636,766 Leakage MGM 438,114 Legal penalty 255,966 Water Ingress 265,213 Conditioning 212,995