Transaction-Oriented Dynamic Power Flow Tracing for Distribution Networks – Definition and Implementation in GIS Environment


There is a growing interest from owners of distributed energy resources (DERs) to actively participate in the energy market through peer-to-peer (P2P) energy trading. Many strategies have been proposed to base P2P energy trading on. However, in those schemes neither the costs of assets usage nor the losses incurred are so far taken into account. This article presents a transaction-oriented dynamic power flow tracing (PFT) platform for distribution networks (DNs) implemented in a geographic information system (GIS) environment. It introduces a new transaction model that quantifies the use of the DN, apportions the losses and unlocks a flexible use of the surplus generation enabling that prosumers can adopt simultaneously different mechanisms for participation in energy trading, maximizing renewable energy usage. The platform is also helpful for future distribution system operators (DSOs) to overcome the status invisibility of low voltage (LV) DNs, determine who makes use of the assets, debit the losses on them and explore the effects from new connections. A case study is conducted over the IEEE European LV Test Feeder. The tool provides a clear, intuitive, temporal and spatial assessment of the network operation and the resulting power transactions, including losses share and efficiency of DERs.

Publication DOI:
Divisions: College of Engineering & Physical Sciences
Additional Information: This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see Funding: This work was supported by the research project “Street2Grid – an electricity blockchain platform for P2P energy trading” (Reference: EP/S001778/2), funded by the Engineering and Physical Sciences Research Council (EPSRC), UK Research and Innovation (UKRI), United Kingdom
Uncontrolled Keywords: Distribution networks,P2P energy simulation platform,dynamic power flow tracing,geographic information system,Computer Science(all)
Publication ISSN: 1949-3061
Last Modified: 14 May 2024 07:18
Date Deposited: 29 Oct 2020 08:32
Full Text Link:
Related URLs: https://ieeexpl ... cument/9239412/ (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2021-03
Published Online Date: 2020-10-26
Accepted Date: 2020-10-01
Authors: Vega-fuentes, Eduardo
Yang, Jin
Lou, Chengwei
Meena, Nand K (ORCID Profile 0000-0002-4092-3921)



Version: Accepted Version

License: Creative Commons Attribution

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