Hybrid European MV-LV Network Models for Smart Distribution Network Modelling

Matthew Deakin, David Greenwood, Sara Walker, Phil C. Taylor

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

7 Citations (Scopus)


A pair of European-style, integrated MV-LV circuits are presented, created by combining generic MV and real LV networks. The two models have 86, 000 and 113, 000 nodes, and are made readily available for download in the OpenDSS file format. Primary substation tap change controls and MV-LV feeders are represented as three-phase unbalanced distribution network models, capturing the coupling of voltages at the MV level. The assumptions made in constructing the models are outlined, including a preconditioning step that reduces the number of nodes by more than five times without affecting the solution. Two flexibility-based case studies are presented, with TSO-DSO and peer-to-peer-based smart controls considered. The demonstration of the heterogeneous nature of these systems is corroborated by the analysis of measured LV voltage data. The models are intended to aid the development of algorithms for maximising the benefits of smart devices within the context of whole energy systems.

Original languageEnglish
Title of host publication2021 IEEE Madrid PowerTech, PowerTech 2021 - Conference Proceedings
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
ISBN (Electronic)9781665435970
Publication statusPublished - 28 Jun 2021
Event2021 IEEE Madrid PowerTech, PowerTech 2021 - Madrid, Spain
Duration: 28 Jun 20212 Jul 2021

Publication series

Name2021 IEEE Madrid PowerTech, PowerTech 2021 - Conference Proceedings


Conference2021 IEEE Madrid PowerTech, PowerTech 2021

Bibliographical note

Funding Information:
This work was funded by EPSRC through grant no. EP/S00078X/1 (Super-gen Energy Networks Hub 2018). Email: matthew.deakin@newcastle.ac.uk.

Publisher Copyright:
© 2021 IEEE.


  • distribution network analysis
  • flexibility services
  • Unbalanced distribution network modelling


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