Hybrid data and model‐driven joint identification of distribution‐network topology and parameters-Reference-Cited by-同舟云学术

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Hybrid data and model‐driven joint identification of distribution‐network topology and parameters

Published:2022-10-18 Issue:23 Volume:16 Page:4846-4866
ISSN:1751-8687
Container-title:IET Generation, Transmission & Distribution
language:en
Short-container-title:IET Generation Trans & Dist

Author:

Yang Xiu¹,Jiang Jiafu¹^ORCID,Liu Fang¹,Tang Jinzhang¹

Affiliation:

1. College of Electrical Engineering Shanghai University of Electric Power Shanghai People'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/gtd2.12634

Reference35 articles.

1. Distributed Energy Resources Topology Identification via Graphical Modeling

2. Minimum loss operation of distribution networks with photovoltaic generation

3. Analysis of power transfer limit considering thermal balance of overhead conductor

4. A Review on Distribution System State Estimation

5. PMU-Based Estimation of Dynamic State Jacobian Matrix and Dynamic System State Matrix in Ambient Conditions

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