Projects
Projects: Projects for Investigator |
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| Reference Number | NIA_UKPN0006 | |
| Title | The Prediction of Weather-Related Faults | |
| 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) 50%; ENVIRONMENTAL SCIENCES (Earth Systems and Environmental Sciences) 50%; |
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| UKERC Cross Cutting Characterisation | Not Cross-cutting 100% | |
| Principal Investigator |
Project Contact No email address given Eastern Power Networks plc |
|
| Award Type | Network Innovation Allowance | |
| Funding Source | Ofgem | |
| Start Date | 01 May 2015 | |
| End Date | 01 February 2016 | |
| Duration | 15 months | |
| Total Grant Value | £128,310 | |
| Industrial Sectors | Power | |
| Region | London | |
| Programme | Network Innovation Allowance | |
| Investigators | Principal Investigator | Project Contact , Eastern Power Networks plc (99.998%) |
| Other Investigator | Project Contact , UK Power Networks (0.001%) Project Contact , South Eastern Power Networks plc (0.001%) |
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| Web Site | http://www.smarternetworks.org/project/NIA_UKPN0006 |
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| Objectives | The objectives of the project are to: Improve understanding of the relationship between weather and faults (including ice accretion and faults on the network. )Develop a forecast model which estimates the frequency of daily precipitation and wind-related faults on the distribution network (LV, HV) for each individual licence area. Identify areas which are more susceptible to lightning than others and develop a model if a reasonable relationship can be found. Reduce operational costs due to non-utilisation of standby staff Reduce Customer Minutes Lost Success criteria for the project are defined below :( 1) Better correlation between observed number of faults and the forecast impact of weather condition on faults. (2) A reduction in non-utilisation of staff on standby | |
| Abstract | Key challenges faced by Distribution Network Operators (DNOs) include: Poor understanding of the impact of various combinations of weather conditions on specific asset types and their components Limited forecasting capability for faults Limited local resources during a significant weather event (in these instances fault volumes are usually significantly higher than normal so often require additional contractor resources)Increasing operational costs for dealing with weather-related faults Within UK Power Networks, resource requirements for forecast weather conditions are determined based on engineering judgment and a subjective view of the impact of historical weather events. A detailed analysis of historical fault and weather data will provide a better understanding of the specific relationship between different combinations of weather conditions and overhead and underground assets. This will enable us to develop algorithms that would feed into a faults forecast model. A validated faults forecast model will improve the accuracy of fault forecasts and provide the enabler to improve deployment of resources, reduce, CMLs and operating costs. The faults forecast model will allow us to carry out localised impact assessments for weather conditions in different geographical areas. The prediction of weather-related faults is being carried out as a two-stage project: Phase 1 Proof of concept Phase 2 Prediction of weather-related faults Phase 1 of the project was completed by the Met Office and funded by UK Power Networks. Analyses by the Met Office on LPN data showed that there was indeed some relationship between a combination of weather conditions (rainfall, dry spells, soil condition etc. ) and faults. This proved that there was some benefit in carrying out a more detailed analysis to understand the relationship between faults and weather data. In phase 2 the intention is to carry out a more detailed analysis using more granular weather data (hourly 2km data). This will focus on underground cable faults and overhead line faults in the three licence areas. The product that will be delivered by the project will be a faults forecast model and the outputs will be faults impact assessments that will accompany the daily/weekly weather forecasts that we receive from the Met Office. In phase 2 the intention is to carry out a more detailed analysis using more granular weather data (hourly 2km data). This will concentrate on underground cable faults and overhead line faults in the three licence areas. The product that will be delivered by the project will be a faults forecast model and the outputs will be faults impact assessments that will accompany the daily weather reports that we receive from the Met Office. The data will provide daily (and potentially sub daily) fault forecasts up to five days ahead for the three UK Power Networks licence areas and be delivered daily or sub-daily. The project will be broken down into five key work packages; data restoration, precipitation,) wind speed and direction, lightning and (ice accretion. This will allow each element of the work to progress independently so that forecast services for the various aspects can be implemented as soon as that particular work package is completed. Data restoration The work outlined in the different work packages requires historical gridded weather information (hourly 2km data covering the UK). This information is held on off-line storage media, by the Met office, and takes some time to restore. This would be the first task to be undertaken and would take three months to complete including quality assurance and validation of the data. Historical data analyses Analyses of historical fault data to identify trends in relation to precipitation, wind speed and direction, lightning and ice accretion will be carried out. The results of these analyses will be used to develop algorithms which will help implement the fault forecast models. Annual Verification Annual verification of the forecast models will be carried out using updated UK Power Networks faults data to ensure that the models remain fit for purpose. Changes may need to be made to reflect the changing resilience of the distribution network due to investment and ageing. Model improvements may also be necessary to capture important influences not yet incorporated in to the models. An annual report on performance would highlight how well the models are performing and make recommendations for future improvements. The Met Office will retain all of the forecasts that is has issued and analyse how well each performed at varying forecast lead times. UK Power Networks could use this information to determine how far in advance decisions should be made relating to the forecast services. Deliverables The product that will be delivered by the project will be a faults forecast model and the outputs will be faults impact assessments that will accompany the daily weather reports that at we receive from the Met Office. The data will provide daily (and potentially sub daily) fault forecasts up to five days ahead for the three UK Power Networks licence areas and be delivered daily or sub-daily. The main benefits from the project include:- Better understanding of the relationship between faults and weather including understanding of the relationship between ice accretion and faults on the network. - Development of a faults forecast model which: Estimates the frequency of daily precipitation related faults on the low voltage network for each individual licence area. Estimates the frequency of daily wind related faults on the high voltage network for each individual licence area. Identifies areas which are more susceptible to lightning than others. This is dependent on the quality of historical lightning data. If a reasonable relationship can be found then a forecast model will be developed. - Improved CML performance due to better utilisation of operational resources- Reduced operational costs by accurately predicting the number of resources required and reducing the number of non-utilized standby resources.Note : Project Documents may be available via the ENA Smarter Networks Portal using the Website link above | |
| Publications | (none) |
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| Final Report | (none) |
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| Added to Database | 17/12/18 | |
