Photovoltaic power prediction based on sky images and tokens-to-token vision transformer.

Q Dai, X Hou, D Su, Z Cui - International Journal of …, 2023 - search.ebscohost.com
Photovoltaic (PV) power generation has high uncertainties due to the randomness and
imbalance nature of solar energy and meteorological parameters. Hence, accurate PV …

Multifeature-Based Variational Mode Decomposition–Temporal Convolutional Network–Long Short-Term Memory for Short-Term Forecasting of the Load of Port …

G Chen, X Ma, L Wei - Sustainability, 2024 - mdpi.com
Accurate short-term forecasting of power load is essential for the reliable operation of the
comprehensive energy systems of ports and for effectively reducing energy consumption …

An adaptive method for real‐time photovoltaic power forecasting utilizing mathematics and statistics: Case studies in Australia and Vietnam

T Nguyen‐Duc, H Vu‐Xuan‐Son… - IET Renewable …, 2024 - Wiley Online Library
The advancement of Photovoltaic technology has undergone rapid acceleration in recent
years. Nonetheless, the most significant drawback of Photovoltaic is its intermittence, making …

Short-term multi-step forecasting of rooftop solar power generation using a combined data decomposition and deep learning model of EEMD-GRU

NNV Nhat, DN Huu, TTH Nguyen - Journal of Renewable and …, 2024 - pubs.aip.org
In this study, an integrated forecasting model was developed by combining the ensemble
empirical mode decomposition (EEMD) model and gated recurrent unit (GRU) neural …

A Comparative Study of Machine Learning–based Models for Short-Term Multi-step Forecasting of Solar Power: An Application for Nhi Ha Solar Farm

THT Nguyen, N Van Pham, XB Do - Measurement, Control, and …, 2024 - mca-journal.org
Over the past few decades, the utilization of solar power has gained immense significance in
the power grid, gradually taking over the responsibilities of fossil fuel-based power …