go to top scroll for more


Projects: Projects for Investigator
Reference Number NIA_NGGD0068
Title Network Outperformance Measure Risk Trading Methodology Stage 2
Status Completed
Energy Categories Fossil Fuels: Oil Gas and Coal(Oil and Gas, Other oil and gas) 50%;
Fossil Fuels: Oil Gas and Coal(Oil and Gas, Refining, transport and storage of oil and gas) 50%;
Research Types Applied Research and Development 100%
Science and Technology Fields SOCIAL SCIENCES (Economics and Econometrics) 100%
UKERC Cross Cutting Characterisation Not Cross-cutting 100%
Principal Investigator Project Contact
No email address given
Cadent Gas
Award Type Network Innovation Allowance
Funding Source Ofgem
Start Date 01 December 2015
End Date 01 January 2017
Duration 15 months
Total Grant Value £406,287
Industrial Sectors Technical Consultancy
Region London
Programme Network Innovation Allowance
Investigators Principal Investigator Project Contact , Cadent Gas (99.997%)
  Other Investigator Project Contact , Wales and West Utilities (0.001%)
Project Contact , Northern Gas Networks (0.001%)
Project Contact , SGN (0.001%)
Web Site http://www.smarternetworks.org/project/NIA_NGGD0068
Objectives The objective of this projects is to: Develop Event Tree models to enable quantification of monitised risk for the 5 proposed risk models listed above covering reportable asset groups. Provide a solution that must be readily accessible and easily incorporated into the asset management working activities of the GDNs. Throughout the project there will be frequent meetings held by the SRWG and with the external company to update on project progress and keep within key milestones. Each stage will have its own deliverables and targets which the project will measure against the original scope. The project seeks to deliver: Demonstrable models for deriving monitised risk for each of the 5 asset groupsProvide a solution that meets the needs of Ofgem namelyAssets Groups are modeled at an optimum levelWill enable risk trading and demonstrate this through multiple investment scenariosIntegration of the models into the businesses of the GDNsProvide final project report detailing: How the model have been developed and agreed including data sources and assumptionsCost benefit of investment for each asset group through monitised risk analysisRisk trading approach and the outputs of risk trading principles
Abstract Following submission of the Gas Distribution Network’s (GDN’s) business plans, Ofgem recognised the significant work carried out by the GDNs to report asset health, probability of failure and deterioration. However, it was recognised that the proposed framework did not provide consistent results between the GDNs and did not enable risk trading i. e. risk justification for the transfer of investment across asset groups. Ofgem have 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 (theAsset Group or Sub-group), but to enable GDNs to target investment on specific assets based on the optimum risk reduction value. As it was communicated that Ofgem were not satisfied with the proposal on the assessment of Asset Health and Criticality the GDNs prepared an alternative methodology for asset risk reporting and trading based on an Event Tree analysis approach. This approach will enable the benefits of expenditure across different gas distribution asset groups to be articulated on a consistent basis, compared and traded off. Ofgem has provided initial comments that they favour this proposed approach, but there is still some uncertainty over the level of detail required to achieve Ofgem’s requirement for the approach to deliver both output reporting and the optimised targeting of asset investment over the GD1 period. To provide the consistency that the license condition requires, the Safety & Reliability Working Group (SRWG) have been working to derive a consistent methodology for each of the 19 agreed asset groups for reporting to Ofgem by Oct 2015. For these asset groups the SRWG have derived "simple" methodologies. For the more complex asset groups a more complex methodology is required and the SRWG have established that external consultation is required. The proposed solution is to provide a consistent framework for reporting monitised risk removal utilising asset health data, probability of failure and deterioration rates data already developed by the GDNs. The project will seek assistance from an external service provider to liaise with the GDNs and work to create this consistent risk trading framework reportable to Ofgem. Although all asset groups within the GDNs will need to be scored on a monitised risk basis, this project will focus on the next set of 5 asset groups as a follow on from the proof-of-concept work done alongside Phase 1 and 2. Development timescales will be agreed for the remaining 9 asset groups upon receipt of Ofgem’s response to the proposed methodology but this is not in the scope of this NIA project. Phase 3 Application of the methodology to complex asset groups, including Risers (MOBs), Offtake/PRS Filters, Offtake/PRS Slam-shuts & Regulators, Offtake Odorisation, Offtake Meters. The development of these models is inherently more complicated than those covered in phase 2 due to an increased level of co-dependencies, redundancy considerations, and the volume of separate replacement and refurbishment interventions options. As part of the development and application of the methodology, each of the proposed Event Trees for each Asset Group and Sub-asset Group need to be validated and approved. This will be delivered by: Confirming completeness and accuracy of Event Trees developed to date with GDN experts. Confirming which Asset Sub-groups need to be included to enable a useful list of "trade-offs" to be produced for comparison in the ‘Evaluate Costs and Benefits of Intervention’ stage. This may include the development and finalization of individual risk maps for any subgroups that will be required to differentiate failure/deterioration rates and investment costs. An example of how Asset Groups could be disaggregated include: a. Materialb. Pressure Tierc. Function/purposed. Geography / Networke. Asset Health categoryTo support the overall development, on-going maintenance and liaison with all stakeholders, it is proposed that a series of libraries be developed. Develop a Data Requirements Specification (DRS) for each Event Tree, identifying potential data sources for asset volumes, intervention types, failure probabilities and failure consequences. The development of these risk models will enable the GDNs to demonstrate network risk removal as a result of the investment strategies outlined in their Final Proposals and how risk trading can be applied across asset groups.Note : Project Documents may be available via the ENA Smarter Networks Portal using the Website link above
Publications (none)
Final Report (none)
Added to Database 14/09/18