首页|面向风电功率预测的关键技术及应用综述

面向风电功率预测的关键技术及应用综述

扫码查看
分析了风电功率预测的新兴技术与发展趋势,介绍了深度学习、机器学习、经验模态分解等方法.每种技术都针对特定挑战提出解决方案,展现了风电功率预测技术在电力系统领域的最新进展,探讨了未来研究的方向,包括深入研究风电预测方式、探索混合模型对风电功率预测方法的有效性,以及机器学习、深度学习技术在风电功率预测方向的发展.
A Review of Key Technologies and Applications for Wind Power Prediction
Emerging technologies and development trends in wind power prediction are analysed,focusing on deep learning,machine learning,and empirical modal decomposition.Each technique proposes solutions to specific challenges,showing the latest progress of wind power prediction techniques in the field of power systems,and also discussing the direction of future research,including in-depth research on wind power prediction methods,exploring the effectiveness of hybrid models for wind power prediction methods,and the development of machine learning and deep learning techniques in the direction of wind power prediction.

wind power predictiondeep learningmachine learningmodal decompositiontechnology development trend

何志福、徐戈

展开 >

辽宁工程技术大学,辽宁 葫芦岛 125105

风电功率预测 深度学习 机器学习 模态分解 技术发展趋势

2024

现代工业经济和信息化

现代工业经济和信息化

影响因子:0.485
ISSN:
年,卷(期):2024.14(10)