A Photovoltaic (PV)-Wind Hybrid Energy System Using an Improved Deep Neural Network (IDNN)-Based Voltage Source Controller for a Microgrid Environment-Reference-Cited by-同舟云学术

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A Photovoltaic (PV)-Wind Hybrid Energy System Using an Improved Deep Neural Network (IDNN)-Based Voltage Source Controller for a Microgrid Environment

Published:2023-12-12 Issue: Volume: Page:
ISSN:
Container-title:RAiSE-2023
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Author:

Prakasam Manimekalai Maradi Anthonymuthu¹,Karuppaiyen Muthulakshmi²^ORCID,Siddan Gopinath³

Affiliation:

1. Department of ECE, Karunya Institute of Technology and Sciences, Coimbatore 641114, Tamil Nadu, India

2. Department of ECE, Sri Krishna College of Technology, Coimbatore 641042, Tamil Nadu, India

3. Department of ECE, Swarnandhra Institute of Engineering and Technology, Narsapur 534280, Andhra Pradesh, India

Publisher

MDPI

Link

https://www.mdpi.com/2673-4591/59/1/30/pdf

Reference18 articles.

1. Smart energy coordination of a hybrid wind/PV with battery storage connected to grid;Mbungu;J. Eng.,2019

2. Size optimization and sensitivity analysis of hybrid wind/PV micro-grids-a case study for Bangladesh;Nurunnabi;IEEE Access,2019

3. Design and analysis of a hybrid renewable energy plant with solar and wind power;Kabalci;Energy Convers. Manag.,2013

4. Application of neural network and weighted improved PSO for uncertainty modeling and optimal allocating of renewable energies along with battery energy storage;Masoumi;Appl. Soft Comput.,2020

5. Albalawi, H., El-Shimy, M.E., AbdelMeguid, H., Kassem, A.M., and Zaid, S.A. (2022). Analysis of a Hybrid Wind/Photovoltaic Energy System Controlled by Brain Emotional Learning-Based Intelligent Controller. Sustainability, 14.

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