基于机器学习模型的风电预测：以浙江沿海风电场为例

IF 3.1 4区工程技术 Q3 ENERGY & FUELS

International Journal of Green Energy Pub Date : 2024-02-26 DOI:10.1080/15435075.2024.2319228

Guangcheng Gu, Ningbo Li, Yaying Pan, Chonghui Jin, Yabin Li, Rongjie Fang, Kaibo Chen, Qi Wang

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引用次数: 0

摘要

风的不可预测性和不稳定性阻碍了风能的开发和利用。为了利用风能，确保风电并网后电网的安全和稳定，风电场的建设和运营必须考虑风能的可预测性和不稳定性...

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Wind power forecasting based on a machine learning model: considering a coastal wind farm in Zhejiang as an example

The unpredictability and instability of wind have hindered the development and utilization of wind power. To harness wind energy and ensure a secure and stable power grid after wind power integrat...

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来源期刊

International Journal of Green Energy 工程技术-能源与燃料

CiteScore

6.60

自引率

9.10%

发文量

112

审稿时长

3.7 months

期刊介绍： International Journal of Green Energy shares multidisciplinary research results in the fields of energy research, energy conversion, energy management, and energy conservation, with a particular interest in advanced, environmentally friendly energy technologies. We publish research that focuses on the forms and utilizations of energy that have no, minimal, or reduced impact on environment, economy and society.