White Rose University Consortium logo
University of Leeds logo University of Sheffield logo York University logo

Investigating the Ability of Smart Electricity Meters to Provide Accurate Low Voltage Network Information to the UK Distribution Network Operators

Poursharif, Goudarz (2018) Investigating the Ability of Smart Electricity Meters to Provide Accurate Low Voltage Network Information to the UK Distribution Network Operators. PhD thesis, University of Sheffield.

[img]
Preview
Text
Investigating the Ability of Smart Electricity Meters.pdf
Available under License Creative Commons Attribution-Noncommercial-No Derivative Works 2.0 UK: England & Wales.

Download (4Mb) | Preview

Abstract

This research presents a picture of the current status and the future developments of the LV electricity grid and the capabilities of the smart metering programme in the UK as well as investigating the major research trends and priorities in the field of Smart Grid. This work also extensively examines the literature on the crucial LV network performance indicators such as losses, voltage levels, and cable capacity percentages and the ways in which DNOs have been acquiring this knowledge as well the ways in which various LV network applications are carried out and rely on various sources of data. This work combines 2 new smart meter data sets with 5 established methods to predict a proportion of consumer’s data is not available using historical smart meter data from neighbouring smart meters. Our work shows that half-hourly smart meter data can successfully predict the missing general load shapes, but the prediction of peak demands proves to be a more challenging task. This work then investigates the impact of smart meter time resolution intervals and data aggregation levels in balanced and unbalanced three phase LV network models on the accuracy of critical LV network performance indicators and the way in which these inaccuracies affect major smart LV network application of the DNOs in the UK. This is a novel work that has not been carried out before and shows that using low time resolution and aggregated smart meter data in load flow analysis models can negatively affect the accuracy of critical low voltage network estimates.

Item Type: Thesis (PhD)
Keywords: Smart Grid, Smart Meters, Smart Meter Data, Low Voltage Network, Losses, Voltage Levels, Time Resolution, Data Aggregation.
Academic Units: The University of Sheffield > Faculty of Social Sciences (Sheffield) > Management School (Sheffield)
Identification Number/EthosID: uk.bl.ethos.745667
Depositing User: Mr Goudarz Poursharif
Date Deposited: 18 Jun 2018 09:00
Last Modified: 12 Oct 2018 09:54
URI: http://etheses.whiterose.ac.uk/id/eprint/20614

You do not need to contact us to get a copy of this thesis. Please use the 'Download' link(s) above to get a copy.
You can contact us about this thesis. If you need to make a general enquiry, please see the Contact us page.

Actions (repository staff only: login required)