A comprehensive review of machine learning applications in forecasting solar PV and wind turbine power output

A comprehensive review of machine learning applications in forecasting solar PV and wind turbine power output

Abstract With climate change driving the global push toward sustainable energy, the reliability of power systems increasingly depends on accurate forecasting methods. This study examined the role of machine learning (ML) in forecasting solar PV power output (SPVPO) and wind turbine power output (WTP...

Full description

Saved in:
Bibliographic Details
Main Authors: Ian B. Benitez, Jai Govind Singh
Format: Article
Language:English
Published: SpringerOpen 2025-07-01
Series:Journal of Electrical Systems and Information Technology
Subjects:
Solar PV power output forecasting
Wind turbine power output forecasting
Forecasting
Core principles and forecasting accuracy
Machine learning-based forecasting techniques
Solar and energy forecasting models
Online Access:https://doi.org/10.1186/s43067-025-00239-4
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1186/s43067-025-00239-4

Similar Items