Projects
Projects: Projects for Investigator |
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| Reference Number | NIA2_NGET0038 | |
| Title | Network Intelligence through Probabilistic Risk Assessment Methodology (NIPRAM) to improve electricity system restoration | |
| Status | Completed | |
| Energy Categories | Other Power and Storage Technologies(Electricity transmission and distribution) 100%; | |
| Research Types | Applied Research and Development 100% | |
| Science and Technology Fields | ENGINEERING AND TECHNOLOGY (Electrical and Electronic Engineering) 100% | |
| UKERC Cross Cutting Characterisation | Not Cross-cutting 100% | |
| Principal Investigator |
Project Contact No email address given National Grid Electricity Transmission |
|
| Award Type | Network Innovation Allowance | |
| Funding Source | Ofgem | |
| Start Date | 01 July 2023 | |
| End Date | 31 March 2024 | |
| Duration | ENA months | |
| Total Grant Value | £437,968 | |
| Industrial Sectors | Power | |
| Region | London | |
| Programme | Network Innovation Allowance | |
| Investigators | Principal Investigator | Project Contact , National Grid Electricity Transmission (100.000%) |
| Industrial Collaborator | Project Contact , National Grid Electricity Transmission (0.000%) |
|
| Web Site | https://smarter.energynetworks.org/projects/NIA2_NGET0038 |
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| Objectives | "NGET recognises that the first step to address the challenges highlighted above is to select an LJRP as a use case to analyse and optimise using probabilistic risk assessment (PRA) methods. NGET will provide system architectural data (one line diagrams), asset health data (mean time between failure, asset health indices, effective ages, etc.) and SME input. This will enable the supplier to perform a normative analysis, utilising quantitative methods to establish the risk factors and resilience of assets both individually and collectively as an LJRP route option. The analysis methods will include: PRA analysis of the selected LJRP. This includes preliminary data gathering and analysis, the PRA effort, sensitivity analysis around key model parameters, and what-if analyses.Aggregating asset level data to construct a Bayesian network that describes the functional characteristics of the LJRP. This quantitative framework will be used to make probabilistic inferences on the system as a whole and enables the analyst to identify:The top-level system probability of failureA complete set of potential root causes of failure and their probabilities of occurrenceRanking of assets by risk importanceProduction of a technical report in the form of a standard operating procedure, which outlines optimised routing patterns given various asset failure configurations.Production of decision analysis guidance for implementation of the LJRP and expected implementation timings. This will include asset criticality, risk factors and probability of successful re-energisation within a defined timescale.The result of this analysis will provide operators operational insight regarding asset management decisions that will maximally ensure successful re-energisation of the LJRP. " "The scope of this project is limited to the assessment of a single LJRP consisting of 3 restoration route options. This use case has been selected to provide diversity of substation design, asset class and restoration routes. In total there are 11 transmission substations and 17 transmission circuits which will be subjected to detailed PRA analysis. Each option within the LJRP will be assessed to provide: Quantitative measure of re-energisation risk factors.Probability of successful LJRP implementation.Establishment of optimum routing options based on network topology and time to completion.Asset criticality scoring. Targeted / enhanced asset maintenance and end of life recommendations. " "The objective of this project is to demonstrate the use of probabilistic risk assessments (PRA) & analysis for the purpose of system restoration. The project will provide a data driven assessment of risk factors associated with the selected LJRP. This will facilitate more advanced, intelligent decision-making during implementation of the LJRP and improve the situational awareness of current resilience levels. This effort will utilise innovative analytical methodologies to do the following: Demonstrate the implementation of PRA methods and techniques applicable to system restoration strategies.Demonstrate the establishment of a data-driven, quantitative restoration plan which considers key factors such as asset criticality.Compute probabilistic measures that indicate re-energisation risk factors and the probability of successful re-energisation.Incorporate asset conditions data into the calculation of optimal re-energisation patterns in LJRP implementation.Delivery of a technical report in the form ofa standard operating procedure, which outlines optimised routing patterns given various asset failure configurations. " | |
| Abstract | "Local Joint Restoration Plans (LJRP) detail the agreed method and procedures used to restore the total system following a total or partial shutdown. For Transmission Licensees, an LJRP defines the critical assets and substations selected for initial re-energisation of the transmission network. NGET forecasts a growth in LJRPs across the transmission system. In many cases this is where the network by design offers less redundancy or is depleted whilst network reinforcements are carried out. In these instances, optimising LJRP energisation strategies is critical. This project seeks to demonstrate a rigorous quantitative risk analysis methodology for the pre-planning and selection of assets and substations included within LJRPs. The project will enable a greater level of intelligence relating to network performance and decision optimisation following a shutdown. " | |
| Publications | (none) |
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| Final Report | (none) |
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| Added to Database | 01/11/23 | |
