Suppr超能文献

基于经验模态分解的灰色组合预测模型——在风力发电长期预测中的应用

EMD-based gray combined forecasting model - Application to long-term forecasting of wind power generation.

作者信息

Ran Minghao, Huang Jindi, Qian Wuyong, Zou Tingting, Ji Chunyi

机构信息

School of Business, Jiangnan University, Wuxi, Jiangsu, 214122, China.

出版信息

Heliyon. 2023 Jul 7;9(7):e18053. doi: 10.1016/j.heliyon.2023.e18053. eCollection 2023 Jul.

Abstract

Wind power is the most promising renewable energy source after hydropower because of its mature technology and low price, and has great potential for carbon emission reduction. Long-term forecasts of its power generation can help power companies to develop operational plans, grid configuration and power dispatch, and can also provide a basis for the government to formulate energy and environmental policies. However, due to the characteristics of China's monsoon climate and wind power industry development, wind power generation data are characterized by nonlinear cycles and small data volume, which makes accurate prediction more difficult. To this end, this paper develops a new prediction model and applies it to the long-term prediction of wind power generation in China, and proposes some targeted policy recommendations based on the prediction results to promote the development of China's wind power industry.

摘要

由于技术成熟且价格低廉,风力发电是仅次于水力发电的最具前景的可再生能源,具有巨大的碳排放减排潜力。对其发电量进行长期预测有助于电力公司制定运营计划、电网配置和电力调度,也可为政府制定能源和环境政策提供依据。然而,由于中国季风气候和风电行业发展的特点,风力发电数据具有非线性周期和小数据量的特征,这使得准确预测更加困难。为此,本文开发了一种新的预测模型并将其应用于中国风力发电的长期预测,并根据预测结果提出了一些针对性的政策建议,以促进中国风电行业的发展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/817a/10366421/1ddbc5e4abb0/gr1.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验