Dec 2009
Electricity Distribution
Smart Urban Low Voltage Network
NIA_UKPN0003
Complete
Dec 2009
Mar 2017
UK Power Networks, Eastern Power Networks, London Power Networks and South Eastern Power Networks
UKPN Innovation Team
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Network Innovation Allowance
None
£5,383,409.00
The scope covers:

1) Industrialisation of hardware (based on learning from the prototype deployment undertaken in the LV Remote Control & Automation IFI project), and development of a link box load monitoring device (non-switching) to retrofit into older cast iron link boxes. This activity has been completed under the original Tier 1 LCNF project.

2) Integration of LV hardware with a SCADA based control system utilising LV connectivity models. This activity has been completed under the original Tier 1 LCNF project.

3) Roll out of the technology and evaluation of the potential benefits which are expected to include reduced losses, increased capacity headroom, early visibility of emerging loading or power quality issues. A potential improvement in quality of supply of up to 75% has been identified in the trial area. This activity will be completed under NIA funding.

This project will demonstrate the business benefits of a large scale roll out of a technology that facilitates remote smart management of the LV network.

The following will be considered when assessing whether the project has been successful:

1) Connectivity models for the LV network areas chosen for the trial installations have been created.

2) Successful implementation of automated switching of the LV network is achieved (for fault scenarios and during load related supply interruptions e.g. non-fault fuse operations).

3) Reduction in load related CIs/CMLs is achieved in the trial areas, and the impact of faults on the LV network is reduced.

4) More effective management of the LV network can be demonstrated, by using the additional load monitoring data available to address, amongst other things, any over-loading of plant, phase imbalance, harmonic levels and enable planners to optimise network reinforcement designs.