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Reference Number NIA_NGET0148
Title Network Reliability Asset Replacement Decision Support Tool
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 PHYSICAL SCIENCES AND MATHEMATICS (Applied Mathematics) 75%;
ENGINEERING AND TECHNOLOGY (Electrical and Electronic Engineering) 25%;
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 2014
End Date 01 July 2016
Duration 24 months
Total Grant Value £315,000
Industrial Sectors Power
Region London
Programme Network Innovation Allowance
Investigators Principal Investigator Project Contact , National Grid Electricity Transmission (100.000%)
Web Site
Objectives 1. Upgrade and document the existing reliability assessment software (based on Non-Sequential Monte Carlo approach) for application to the whole National Grid network model in DIgSILENT/Power Factory environment. Test and debug the model and software by collaboration between National Grid and The University of Manchester staff. 2. Provide a prioritised list of transformer replacement candidates (rank transformers based on criticality for system reliability as defined by Energy Not Supplied Index) across the whole National Grid network under a variety of scenarios. 3. Report on results of performed sensitivity studies to give a clear understanding of the required level of detail of network modelling and accuracy of input parameters for power system and asset condition to validate the model outputs and indicate areas where additional data may be required. The success criteria for the project will be; Proof that the methodology can be applied to the whole network Provision of a new prioritised list of replacement candidates that can be benchmarked against existing methodology to show value of approach The development of software which is fit for purpose, user friendly, documented and supportable
Abstract National Grid has a licence obligation to maintain a safe, reliable and economic electrical transmission system. The electrical system is made up of high value capital assets: high voltage overhead lines, cables, switchgear and transformers. In order to transmit electricity efficiently it is necessary to increase the voltage, hence lowering the electrical current and reducing corresponding transmission losses. Over 700 Super Grid Transformers (SGT) are employed on National Grid’s system to carry out these step-up and step-down voltage transformations. Transformers are utilised on a 24/7 basis and are only taken out of service for necessary maintenance and inspections. They are physically large assets, consisting of copper windings, iron cores, insulation materials and cooling equipment. A typical ex works cost for a transmission transformer can be up to £2. 5m and take 10 to 18 months to be manufactured and installed. Transformers are key assets requiring careful management to ensure their continued reliability and safe working. The National Grid network was originally designed and built in the late 1950s and 60s, with many transformer assets now approaching 50 to 60 years of age. Transformers have a finite asset life: National Grid has carried out research in the field of transformer condition assessment over many years in order to determine condition and predict the likelihood of failure with increasing levels of certainty. Whilst deterioration is usually slow, it is inevitable and proceeds over a wide range of rates, determined by transformer design, utilisation and asset care. A single transformer failure carries safety, environmental and system reliability risks. Redundancy (multiple transformers feeding a particular load), asset condition and system topology greatly influence customer loss of load probability following a transformer failure. These interdependent factors make the accurate targeting of transformer asset replacement due to condition to achieve a sustainable level of system reliability and optimal capital efficiency a complex problem. There are some 80 SGT replacements planned over the next 8 years. The resulting transformer replacement expenditure budgets can be up to £40m per year, with a single transformer replacement including transport and installation costing up to £4m per unit. A significant loss of demand incident caused by operating transformer failure would affect National Grid customers to an extent far beyond the value of the electricity not supplied. The alternative option is to replace transformers early; this is inefficient losing financial value for customers and does not necessarily improve reliability. Some transformers can become more critical to the system at certain points in time due to circuit outages for necessary maintenance and construction work. Whilst the system is designed to be resilient for the loss of a subsequent single transformer due to a fault, if there are other transformers in the local area which are sufficiently deteriorated, this first failure could cause cascading failures, which would result in serious widespread issues within the electrical network. National Grid has already developed a risk and criticality based methodology applied to transformer replacement, however this depends on a relatively simple and generalised method of combining asset health and system criticality to produce a replacement priority. This methodology doesnot take into account the possible consequences sympathetic failures, the interaction with the wider power network (HV/LV) or the actions of the system operator. The level of MWhrs lost and the resultant financial impact can only be predicted manually on a localised basis with a limited number of scenarios. ‘What if’ scenarios for the whole network can only be carried out using unconnected power system analysis tools and limited manual statistical modelling and analysis. In testing the technical challenges of this project, the work will aim to answer, but not be limited to, the following questions: Can National Grid’s transformer asset replacement prioritisation be improved? Can value and risk be quantified and explained to stakeholders? Will this work enable commercially available software to be produced? Once the work is complete, who could and should deliver this service? How will this work affect other network users, such as Distribution and generation companies? What is the impact on the end consumer? How would such an approach be implemented?The answers to these questions will provide an understanding of the viability and value of these techniques in managing an ageing complex power system. Research The proposed work will provide an independent method and Decision Support Tool (DST) that directly combines asset condition and system HV/LV topology to identify which clusters of assets contribute the most to potential unreliability. The DST will work within the established system design commercial software used by National Grid. Using this DST on the whole system has the potential to refine replacement candidate selection and replacement timing to enable further value to be obtained from the capital plan. The DST, carries out network reliability analysis, using individual asset reliability estimation (from condition assessment) Power system network model, sequenced and non-sequenced automatic and operator post fault actions Monte Carlo simulation techniques The DST will then output The quantity and financial value of lost load. Probabilistic criticality indicators of individual and cascading asset failure Specifically, the work will aim to meet: The technical challenges of accurately predicting the priority order of transformer asset replacement candidates The technical challenges of modelling a large interconnected system from an electrical and statistical perspective. The methodology and DST will then lend itself to the studies of other critical assets such as cables, overhead lines and switchgear.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