Three‐phase feeder parameter estimation using radial basis function neural networks and multi‐run optimisation method with bad data preparation-Reference-Cited by-同舟云学术

Three‐phase feeder parameter estimation using radial basis function neural networks and multi‐run optimisation method with bad data preparation

Published:2021-10-03 Issue:2 Volume:16 Page:351-363
ISSN:1751-8687
Container-title:IET Generation, Transmission & Distribution
language:en
Short-container-title:IET Generation Trans & Dist

Author:

Yang Nien‐Che¹^ORCID,Huang Rui²³,Guo Mou‐Fa⁴³

Affiliation:

1. Department of Electrical Engineering National Taiwan University of Science and Technology Taipei Taiwan

2. State Grid Quanzhou Electric Power Supply Company Fujian Electric Company Quanzhou China

3. Department of Electrical Engineering 135 Yuan‐Tung Road Chung‐Li Yuan Ze University Taoyuan Taiwan

4. College of Electrical Engineering and Automation Fuzhou University Fuzhou 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/gtd2.12310

Reference28 articles.

1. Power System State Estimation

2. Distribution System Modeling and Analysis

3. An Investigation of the Fundamental-Frequency Impedance of a Single-Phase Distribution Lateral

4. Temporary Overvoltage and GPR Characteristics of Distribution Feeders With Multigrounded Neutral

5. Pandian S.S. Various considerations for estimating steady‐state voltage drop in low voltage ac power distribution systems. In:2006 IEEE Industrial and Commercial Power Systems Technical Conference Detroit(2006)

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