Deep learning model for solar and wind energy forecasting considering

This study presents an attention-based spatial-temporal graph neural network–long short-term memory (ASTGNN-LSTM) model designed to predict wind speed and solar radiation using 20

Enhanced wind power forecasting using machine learning, deep

Based on the research gap identified, the main objective of this study is to present significant advancements in renewable energy forecasting, with an emphasis on wind power generation.

The latest announcement of Zhongmin Energy: All units of the second

The latest announcement of Zhongmin Energy: All units of the second phase of the Putian Pinghai Bay Offshore Wind Farm Project are connected to the grid for power generation

WindDragon: Enhancing Wind Power Forecasting with Automated

This paper presents an innovative approach to short-term (1 to 6 hour horizon) wind power forecasting at a national level. The method leverages Automated Deep Learning combined

Regional Short‐Term Wind Power Prediction

Regional-scale holistic wind power prediction (WPP) is pivotal to securing the safety, stability, and economic efficiency of power systems.

Regression analysis and prediction of monthly wind and solar power

On the basis of monthly historical data and focusing on key issues in clean energy development, this study aims to analyze wind power and solar power generation quantitatively.

Zhongmin Energy announced that in 2025, the total power generation

Among them, wind power generation capacity in Fujian Province was 2,621 billion kilowatt-hours, a year-on-year decrease of 3.45%, and feed-in power, a year-on-year decrease of 3.40%; Heilongjiang

Zhongmin Energy predicts wind power generation

To harness wind energy and ensure a secure and stable power grid after wind power integration, precise predictions of wind power generation are imperative. Here, we apply one-year data from a coastal

A Comprehensive Review of Wind Power Prediction Based on

This paper presents a comprehensive review of machine learning techniques applied to wind power prediction, emphasizing their advantages over traditional physical and statistical models.

Solar and wind power data from the Chinese State Grid

In this paper, an open dataset consisting of data collected from on-site renewable energy stations, including six wind farms and eight solar stations in China, is provided.