Analysis of Artificial Intelligence based Forecasting Techniques for Renewable Wind Power Generation-Reference-Cited by-同舟云学术

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Analysis of Artificial Intelligence based Forecasting Techniques for Renewable Wind Power Generation

Published:2022-12-10 Issue: Volume: Page:
ISSN:
Container-title:2022 Smart Technologies, Communication and Robotics (STCR)
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Author:

Ranga Jarabala¹,Arun Srinivas T.²,Kumar Santosh³,Anandaram Harishchander⁴,Kulkarni Prakruti⁵,Amina Begum M.⁶

Affiliation:

1. Ramachandra College of Engineering,Department of EEE,Eluru,AP

2. JP College of Engineering,Department of EEE,Thenkasi,TN

3. School of Management Sciences,Varanasi,Uttar Pradesh

4. Amrita Vishwa Vidyapeetham,Centre for Excellence in Computational Engineering and Networking,Coimbatore,TN

5. Bharat Institute of Engineering and Technology,Department of ECE,Hyderabad

6. College of Engineering, Thiruvannamalai,Department of Oxford,Chennai,TN,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10009016/10009051/10009141.pdf?arnumber=10009141

Reference12 articles.

1. Forecasting of Wind Capacity Ramp Events Using Typical Event Clustering Identification

2. Predicting Long-Term Wind Speed in Wind Farms of Northeast Brazil: A Comparative Analysis Through Machine Learning Models

3. Short-Term Wind Power Forecasting on Multiple Scales Using VMD Decomposition, K-Means Clustering and LSTM Principal Computing

4. Short-Term Wind-Speed Forecasting Based on Multiscale Mathematical Morphological Decomposition, K-Means Clustering, and Stacked Denoising Autoencoders

5. Data Mining-Based Upscaling Approach for Regional Wind Power Forecasting: Regional Statistical Hybrid Wind Power Forecast Technique (RegionalSHWIP)

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