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Frontiers in Energy Research
Article . 2024 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Frontiers in Energy Research
Article . 2024
Data sources: DOAJ
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Fast power flow calculation for distribution networks based on graph models and hierarchical forward-backward sweep parallel algorithm

Authors: Xinrui Wang; Wengang Chen; Ruimin Tian; Yuze Ji; Jianfei Zhu;

Fast power flow calculation for distribution networks based on graph models and hierarchical forward-backward sweep parallel algorithm

Abstract

IntroductionIn response to the issues of complexity and low efficiency in line loss calculations for actual distribution networks, this paper proposes a fast power flow calculation method for distribution networks based on Neo4j graph models and a hierarchical forward-backward sweep parallel algorithm.MethodsFirstly, Neo4j is used to describe the distribution network structure as a simple graph model composed of nodes and edges. Secondly, a hierarchical forward-backward sweep method is adopted to perform power flow calculations on the graph model network. Finally, during the computation of distribution network subgraphs, the method is combined with the Bulk Synchronous Parallel (BSP) computing model to quickly complete the line loss analysis.Results and DiscussionResults from the IEEE 33-node test system demonstrate that the proposed method can calculate network losses quickly and accurately, with a computation time of only 0.175s, which is lower than the MySQL and Neo4j graph methods that do not consider hierarchical parallel computing.

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Keywords

bulk synchronous parallel computing model, A, line loss calculation, graph model, hierarchical forward-backward sweep, distribution network, General Works

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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