Artificial Neural Network Based Improving Inertia Control With Grid-Connected Renewable Energy Sources-Reference-Cited by-同舟云学术

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Artificial Neural Network Based Improving Inertia Control With Grid-Connected Renewable Energy Sources

Published:2023-08-23 Issue: Volume: Page:
ISSN:
Container-title:2023 Second International Conference on Trends in Electrical, Electronics, and Computer Engineering (TEECCON)
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Author:

Jonnalagadda Vimala Kumari¹,Reddy Aduru Veera¹,Reddy Damodhar²,Vamsi Kumar Segu Yaswanth¹

Affiliation:

1. V. R. Siddhartha Engineering College,Electrical and Electronics Engineering,Vijayawada,India

2. Sasi Institute of Technology & Engineering,Electrical and Electronics Engineering,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10335696/10335697/10335830.pdf?arnumber=10335830

Reference11 articles.

1. A practical model for single-step power prediction of grid-connected PV plant using artificial neural network;fei;2011 IEEE PES Innovative Smart Grid Technologies,2011

2. An Artificial Neural Network based MPPT Algorithm For Solar PV System

3. A Fuzzy Logic-Based Emulated Inertia Control to a Supercapacitor System to Improve Inertia in a Low Inertia Grid with Renewables

4. Design and Implementation of Variable Inertia and Droop Controls on Tidal Power Generator

5. Development and Validation of Artificial Neural Network-Based Tools for Forecasting of Power System Inertia With Wind Farms Penetration

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