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Projects: Projects for Investigator
Reference Number	NIA_NGGT0107
Title	Project EVA - Extreme Value Analysis
Status	Completed
Energy Categories	Fossil Fuels: Oil Gas and Coal(Oil and Gas, Refining, transport and storage of oil and gas) 100%;
Research Types	Applied Research and Development 100%
Science and Technology Fields	SOCIAL SCIENCES (Business and Management Studies) 25%; PHYSICAL SCIENCES AND MATHEMATICS (Applied Mathematics) 75%;
UKERC Cross Cutting Characterisation	Not Cross-cutting 100%
Principal Investigator	Project Contact No email address given National Grid Gas Transmission
Award Type	Network Innovation Allowance
Funding Source	Ofgem
Start Date	01 January 2017
End Date	01 July 2018
Duration	18 months
Total Grant Value	£438,000
Industrial Sectors	Technical Consultancy
Region	London
Programme	Network Innovation Allowance
Investigators	Principal Investigator	Project Contact , National Grid Gas Transmission (100.000%)
Web Site	http://www.smarternetworks.org/project/NIA_NGGT0107
Objectives	The objective of this project is to develop an innovative approach to modelling extreme value risks that support investment decisions ongoing or as part of the Network Development Process (NDP). The analysis should encompass financial, asset and operational modelling to address extreme value events (low probability, high impact asset failures) and facilitate stakeholder engagement in investment decision making. Success will be the application of the extreme value analysis in providing a consistent and detailed approach to a range of NGGT investment projects either ongoing or forecast as part of the Network Development Process (NDP). The approach should be innovative in systems modelling, encompassing financial, asset and operational modelling to address extreme value events (low probability/high impact asset failures), alongside the ability to facilitate stakeholder engagement in investment decision making. The success of the solution will be: A dynamic model that supports rapid scenario analysis, so that scenarios and assumptions can be tested in a timely fashion. A flexible product that has the ability to be applied to multiple investment decisions Strong financial modelling ability ensuring the monetised impact of risks and investment options are robustly modelled. A number of scenarios run that produce a risk-adjusted NPV as well as articulation of the extreme risk scenarios, providing visibility of the tail end risk and confidence it is accounted for in the NPV calculation. Reporting capabilities using the Power BI Dashboards application Use as a high-level simulation tool of network activity and performance. It does not replace dedicated hydraulic model tool in this role, but provide a tool to rapidly run a wide range of network scenarios. In this role it can provide decision support that can inform high level analysis and identify where more detailed hydraulic or engineering modelling or analysis need to be carried out.
Abstract	Many investment decisions within NGGT involve evaluating extreme value risks, which are low probability, high impact events. The tools and approaches that currently exist are not best suited to evaluate these situations. These decisions are made on schemes that could range from £10million to £200million in value. The difficulty in quantifying the value of mitigated risks means that over or underinvestment could occur, with the impact in both scenarios resulting in additional cost to consumers. Over investment can occur where the risk has been quantified at a higher severity therefore driving more costly work, whereas under quantifying the risk can result in higher overall costs due to further risks materialising. There are two key challenges: The volume and diversity of data generated by impact assessments makes the incorporation of quantitative risk assessments and scenario analysis within a single decision making framework challenging The common approaches to cost benefit and net present value analysis tend to emphasise mean or expected values while undervaluing extreme value risks (low probability, high impact) and ignore uncertainty. The solution proposed under this project seeks to address the shortcomings in quantifying the value of investments that involve mitigating extreme value risks. Business Modelling Associates (BMA) will apply risk analysis expertise to develop a model that encompasses financial, asset connectivity and operational risk modelling. It will deliver a methodology that will be broader and more far reaching in dealing with tail end risk and complexity. The technology used (Enterprise Optimizer) has been chosen due to its flexibility in modelling risk, which can accommodate a wide range of data yet to be applied in the UK gas sector. The platform is conducive to rapid and agile model development which will be used to deliver the dynamic model that supports rapid scenario analysis. A methodology that will enable robust assessment of the cost and benefits of investments that include extreme risks and extreme uncertainties will be developed. This will be achieved in 3 key work packages: Constraint-based systems modelling approach: A comprehensive systems map will be build out drawing together all the information available from the existing risk and impact assessment. This system will include all events, options and constraints. This will ensure that all costs/benefits are appropriately captured for each investment option. The systems map will not only represent major events, such as catastrophic failure, but include operational costs, operational mitigations, planned and unplanned maintenance. Whenever possible, uncertainty around events and interventions will be included. Where interventions result in future options which can be included and valued these will also be included, capturing the real value of options. All probabilities, uncertainties and impacts will be defined by time period to ensure that asset deterioration and increasing uncertainty are valued. Modelling uncertainty: Where data is available, risks will be formally represented as probability density functions (PDFs) and a full Monte Carlo simulation will be run to quantify the full range of impacts of each risk. Where this is not possible tail end risks can be represented as discrete risk events following a best case, expected case, worst case approach. This ability to model a detailed event tree including multiple outcomes (from functional, to partial failures and catastrophic failure), coupled with an ability to tailor the representation of risk to the granularity of data available will allow the widest possible representation of risk to be included, making best use of the data available. This will allow a robust simulation of the outcomes, including risk events, of all decision options. Net Present Value approach: For each outcome, event and intervention, a monetary value will be assigned. This will be weighted by the associated likelihood to derive a risk-adjusted net present value. Where uncertainty has been modelled using PDFs, net present value will be returned as a frequency density distribution. In this way, the uncertainty around NPV for different scenarios can be compared as well as the expected value.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	26/10/18