Short-Medium-Term Solar Irradiance Forecasting with a CEEMDAN-CNN-ATT-LSTM Hybrid Model Using Meteorological Data

Short-Medium-Term Solar Irradiance Forecasting with a CEEMDAN-CNN-ATT-LSTM Hybrid Model Using Meteorological Data

In recent years, the adverse effects of climate change have increased rapidly worldwide, driving countries to transition to clean energy sources such as solar and wind. However, these energies face challenges such as cloud cover, precipitation, wind speed, and temperature, which introduce variabilit...

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Bibliographic Details
Main Authors: Max Camacho, Jorge Maldonado-Correa, Joel Torres-Cabrera, Sergio Martín-Martínez, Emilio Gómez-Lázaro
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Applied Sciences
Subjects:
solar irradiance forecasting
long short-term memory
convolution neural network
CEEMDAN
multi-head attention
complex terrain
Online Access:https://www.mdpi.com/2076-3417/15/3/1275

Internet

https://www.mdpi.com/2076-3417/15/3/1275

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