Establishing Lightweight and Robust Prediction Models for Solar Power Forecasting Using Numerical–Categorical Radial Basis Function Deep Neural Networks

Establishing Lightweight and Robust Prediction Models for Solar Power Forecasting Using Numerical–Categorical Radial Basis Function Deep Neural Networks

As green energy technology develops, so too grows research interest in topics such as solar power forecasting. The output of solar power generation is uncontrollable, which makes accurate prediction of output an important task in the management of power grids. Despite a plethora of theoretical model...

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Bibliographic Details
Main Authors: Chee-Hoe Loh, Yi-Chung Chen, Chwen-Tzeng Su, Heng-Yi Su
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Applied Sciences
Subjects:
solar power forecasting
robust prediction
lightweight deep learning model
Online Access:https://www.mdpi.com/2076-3417/14/22/10625
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