基于EMD的灰色组合预测模型 - - 应用于风力发电的长期预测
Minghao Ran1, Jindi Huang1, Wuyong Qian1
1School of Business, Jiangnan University, Wuxi, Jiangsu, 214122, China.
Heliyon
|July 27, 2023
概括
这项研究引入了一个新的模型,用于中国的长期风力发电预测. 该模型解决了季风气候和数据限制所带来的挑战,以改善可再生能源规划.
科学领域:
- 可再生能源系统可再生能源系统
- 气候科学 气候科学
- 数据分析数据分析数据分析.
背景情况:
- 风力发电是重要的可再生能源,具有显著的碳减排潜力.
- 准确的长期风力发电预测对于能源政策和电网管理至关重要.
- 中国的风力发电数据存在挑战,原因是季风气候影响,非线性循环和小体积.
研究的目的:
- 开发和应用一种新的预测模型,用于中国的长期风力发电.
- 为推进中国风力发电行业提供数据驱动的政策建议.
主要方法:
- 开发一个新的,专门的预测模型.
- 该模型应用于来自中国的长期风力发电数据.
- 分析预测结果以告知政策.
主要成果:
- 开发的模型在预测长期风能发电方面表现出有效性.
- 该研究根据预测结果确定了具体的政策建议.
- 这些发现旨在支持中国风力发电部门的增长.
结论:
- 新的预测模型有效地解决了预测中国风力发电的复杂性.
- 有针对性的政策建议可以促进风能可持续发展.
- 准确的预测对于优化可再生能源的整合和政策制定至关重要.
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