Artificial intelligence based succored power prediction in stand alone PV system-Reference-Cited by-同舟云学术

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Artificial intelligence based succored power prediction in stand alone PV system

Published:2024-04-30 Issue: Volume: Page:1-14
ISSN:1448-837X
Container-title:Australian Journal of Electrical and Electronics Engineering
language:en
Short-container-title:Australian Journal of Electrical and Electronics Engineering

Author:

Sayeed Farrukh¹,Ahmed K. Rafeeq²,Swamy S. M.³

Affiliation:

1. Department of Electrical and Electronics Engineering, ACE College of Engineering, Thiruvananthapuram, India

2. Department of Electronics and Communication Engineering, School of Engineering Presidency University, Bangalore, India

3. Department of AI&ML, RT, Chennai, India

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/1448837X.2024.2345992

Reference26 articles.

1. A review on renewable energy and electricity requirement forecasting models for smart grid and buildings

2. Locational marginal price based optimal placement of DG using stochastic radial basis function

3. Nodal Electricity Price Forecasting using Exponential Smoothing and Holt’s Exponential Smoothing

4. A Distributed Generation Framework using SWOT Analysis

5. Wind Generation Forecasting Using Python

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