Data‐driven approach for real‐time distribution network reconfiguration-Reference-Cited by-同舟云学术

Data‐driven approach for real‐time distribution network reconfiguration

Published:2020-05-12 Issue:13 Volume:14 Page:2450-2463
ISSN:1751-8695
Container-title:IET Generation, Transmission & Distribution
language:en
Short-container-title:IET Generation, Transmission & Distribution

Author:

Yin Ziyang¹,Ji Xingquan¹,Zhang Yumin¹,Liu Qi²,Bai Xingzhen¹

Affiliation:

1. College of Electrical Engineering and Automation, Shandong University of Science and TechnologyQingdao266590People's Republic of China

2. Key Laboratory of Smart Grid of Ministry of Education, Tianjin UniversityTianjin300072People's Republic of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology,Control and Systems Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-gtd.2019.1733

Reference43 articles.

1. Merlin A. Back H.: ‘Search for a minimal‐loss operating spanning tree configuration in an urban power distribution system’.Proc. Fifth Power System Computation Conf. Cambridge UK September1975 pp.1–18

2. A new algorithm for the reconfiguration of distribution feeders for loss minimization

3. Feeder reconfiguration in distribution networks based on convex relaxation of OPF;Peng Q.;IEEE Trans. Power Deliv.,2015

4. Distribution system reconfiguration for annual energy loss reduction considering variable distributed generation profiles;Tahboub A.M.;IEEE Trans. Power Deliv.,2015

5. A Fast Nondominated Sorting Guided Genetic Algorithm for Multi-Objective Power Distribution System Reconfiguration Problem

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