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This project ended in May 2019 and is now closed.Dismiss
Losses Investigation
Funding mechanism
Network Innovation Allowance (NIA)
Duration
Apr 2015 - May 2019
Project expenditure
£2,580,000
Research area
Safety, Health
Region
East Midlands
May 2019
The Losses Investigation project is now completed. A comprehensive Closedown Report will shortly be available on the WPD Innovation website. Initial dissemination of learning and outcomes from the project took place at the WPD Balancing Act (London, June 2019). Further technical dissemination is being planned and will be advertised.
The Losses Investigation project is now completed. A comprehensive Closedown Report will shortly be available on the WPD Innovation website. Initial dissem…
Objectives
1) Understand technical losses on the LV and HV network
2) Determine the minimum information to accurately predict network losses.
Problem(s)
Distribution Network Operators have an obligation to operate efficient and economic networks. As such the effective management of distribution losses is paramount. Current estimates put the technical losses at between 5.8% and 6.6% of electricity delivered (“Management of Electricity Distribution Network Losses” IFI report) worth approximately £900 million across the UK. Approximately £640 million of these losses occur after transformation down to 11kV.
Some improvements with clear cost benefits across the network are being rolled out, as outlined in WPDs losses strategy, however these are restricted to broad brush techniques due to a lack of detailed understanding of the distribution of losses across our network. As such reductions in losses cannot be targeted and the network cannot be optimised.
Method(s)
This project will fully monitor several LV and HV feeders to measure all the in-feeds and out-feeds to the networks. This will enable us to gain a much fuller understanding of flows on the feeders as well as determining network losses. We will also investigate the causes and effects of certain loss influencing parameters such as imbalance and power factor.
The monitored feeders will enable us to build a reference for different loss estimation models which will be developed using restricted data sets. These models will predict the losses using data such as customer types and circuit length and will be compared against the reference allowing us to understand the importance and value of the data. The comparisons will allow us to determine the minimum information needed to assess network losses accurately.
This project aims to further our understanding of technical losses on the distribution network and help us target them in a cost effective manner. As 72% of technical losses occur on the HV and LV networks, these will be the focus of the project. Losses before the feeder circuit breaker, beyond the meter as well as non-technical losses will not be investigated. The initial investigations will cover the effects of different loading types and patterns on the various networks, determining their effects on losses and where they are most prevalent. This will be incorporated into an initial losses model to test our understanding against the measured values. The second stage of the project will move to predicting losses with reduced data sets. The accuracy of these predictions will be tested against the measured values. This will allow us to determine the minimum information required to target losses and help create the template for a losses register.
1) Construction of fully monitored HV and LV networks
2) Measurement of network losses on monitored feeders
3) Accurate modelling of losses with full information
4) Several models with limited data sets created and tested
5) Conclusion on level of information needed to accurately predict losses
The installation of fully monitored LV or HV networks hasn’t been done on this scale in the UK. It will allow us to better understand the flows in our network as well as the losses. It should also help us fully understand the effects of different parameters such as imbalance and power factor on losses. The high granularity of the monitoring equipment will also allow us to investigate previous miss-understanding of losses due to averaging effects. The development of the prediction models will allow us to transfer this improved knowledge onto our unmonitored network and enable a targeted reduction in losses.