Projects
Projects: Projects for Investigator |
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| Reference Number | NIA_ENWL_039 | |
| Title | LV Futures | |
| Status | Started | |
| Energy Categories | Other Cross-Cutting Technologies or Research(Energy system analysis) 20%; Other Power and Storage Technologies(Electricity transmission and distribution) 80%; |
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| 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 Electricity North West Limited |
|
| Award Type | Network Innovation Allowance | |
| Funding Source | Ofgem | |
| Start Date | 01 February 2025 | |
| End Date | 31 August 2026 | |
| Duration | ENA months | |
| Total Grant Value | £1,537,000 | |
| Industrial Sectors | Power | |
| Region | North West | |
| Programme | Network Innovation Allowance | |
| Investigators | Principal Investigator | Project Contact , Electricity North West Limited |
| Web Site | https://smarter.energynetworks.org/projects/NIA_ENWL_039 |
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| Objectives | LV Futures will analyse data from recently deployed LV monitoring and smart meters along with trends on Low Carbon Technology uptake to produce power flow and feeder load allocation for LV feeders. The outputs of this analysis will provide relevant information to inform interventions such as reinforcement or flexible services requirements.Additionally, the outputs will be presented in a format to allow them to be used as an input to the LV Predict condition assessment tool. This tool will predict any condition related issues which result from the increased power flow in the LV cables and inform the asset replacement programme.The measurements to be used to inform the forecasting will be taken from deployed LV monitoring and smart meters. These devices are manufactured, tested and certified in accordance with the relevant measurement standards.Any data generated during the project will be managed in line with the RIIO ED2 Data Best Practice Guidance and Data Assurance Guidance This project will conduct detailed analysis on data from recently deployed LV monitoring and smart meters along with trends on Low Carbon Technology uptake. This analysis will produce forecasts of HV/LV substation and LV feeder demand for a 5 year time horizon which will be regularly refreshed.The project will produce and publish all the relevant specifications and functional requirements for the forecasting tool as well as a demonstration of a limited area of LV network on a prototype tool.Net Benefits for consumersBy reducing unplanned outages on LV networks, consumers will benefit from fewer disruptions, minimising financial losses and inconvenience to daily routines, work and leisure activities. Knowing that outages are less likely reduces stress and anxiety associated with the uncertainty of potential disruptions.Financial benefits to networkHaving a better understanding of the load and condition of LV cables, maintenance and replacement efforts can be implemented more effectively, maximising the lifespan of assets and optimising investment decisions. Unplanned outages require emergency repairs which are more expensive than planned work. By reducing these unplanned outages, it is anticipated the project will save410,000 per annum. The objectives are:Establish a methodology to ingest analyse LV monitoring and smart meter data.Combine above analysis with trend data for Low Carbon Technologies to produce power flow and LV feeder load allocation for a 5 year horizon.Build a prototype tool to demonstrate the outputs of the forecasting for a limited area of LV network. | |
| Abstract | The energy system transition will have the greatest impact on LV demand and capacity due to the mass adoption of LCTs. Understanding this impact on demand, available capacity and investment required requires granular long term forecasting for LV feeders.LV Futures will analyse data from recently deployed LV monitoring and smart meters along with trends on LCT uptake to produce power flow and feeder load allocation for LV feeders. The outputs of this analysis will provide relevant information to inform interventions such as reinforcement or flexible services requirements. | |
| Data | No related datasets |
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| Projects | No related projects |
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| Publications | No related publications |
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| Added to Database | 02/04/25 | |
