Optimized Convolutional Neural Network-Based Adaptive Controller for 6-Phase DFIG-Based Wind Energy Systems-Reference-Cited by-同舟云学术

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Optimized Convolutional Neural Network-Based Adaptive Controller for 6-Phase DFIG-Based Wind Energy Systems

Published:2023-05-30 Issue:19 Volume:51 Page:2262-2283
ISSN:1532-5008
Container-title:Electric Power Components and Systems
language:en
Short-container-title:Electric Power Components and Systems

Author:

Azhakappan Arunkumar¹^ORCID,Chellappan Agees Kumar¹^ORCID,Sethuramalingam Murugan²^ORCID

Affiliation:

1. Department of Electrical and Electronics Engineering, Arunachala College of Engineering for Women, Nagercoil, India

2. Department of Electronics and Communication Engineering, Thamirabharani Engineering College, Tirunelveli, India

Publisher

Informa UK Limited

Subject

Electrical and Electronic Engineering,Mechanical Engineering,Energy Engineering and Power Technology

Link

https://www.tandfonline.com/doi/pdf/10.1080/15325008.2023.2209081

Reference47 articles.

1. Fault-Tolerant Operation of Six-Phase Energy Conversion Systems With Parallel Machine-Side Converters

2. Operation of a Six-Phase Induction Machine Using Series-Connected Machine-Side Converters

3. Grid Synchronization of Equivalent Wind Farm Equipped with DFIG Model for Transient Stability by Using Nonlinear Integral Backstepping Control

4. Wind-DFIG wireless controlled using EGPRS standard applied to the ancillary services in a smart grid environment

5. Efficient Direct Model Predictive Control for Doubly-Fed Induction Generators

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