使用韦布尔,雷利和钱珀诺恩分布对季节性风力发电进行比较分析
Bienvenu Sumaili Ndeba1,2, Omaima El Alani3, Abdellatif Ghennioui3
1Geology and Sustainable Mining Institute (GSMI), Mohammed VI Polytechnic University, Ben Guerir, Morocco. sumaili.bienvenu@um6p.ma.
Scientific reports
|January 20, 2025
概括
珀诺恩分布准确地模拟了风速变化,在风速低的地区超过了风能评估的传统模型. 这种新的方法改善了功率密度估计,并指导了现场适用性分析.
科学领域:
- 可再生能源可再生能源是可再生能源.
- 统计建模 统计建模
- 气象学 天气学
背景情况:
- 精确的风速建模对于评估风能潜力至关重要,尤其是在风速低,平静时期频繁的地区.
- 像韦布尔和雷利-赖斯这样的传统模型可能无法完全捕捉风速间歇性.
- 了解风力模式是确定风能项目的可行性的关键.
研究的目的:
- 评估Champernowne分布作为风速分析的新型统计模型.
- 使用各种统计指标,将其表现与已建立的分布 (Weibull,Rayleigh-Rice) 进行比较.
- 为了评估风能的潜力和适合性,摩洛哥的Ben Guerir.
主要方法:
- 收集了三年的风速数据 (2021-2023年) 在摩洛哥本格里尔的10米枢纽高度.
- 应用统计指标包括根平均平方误差 (RMSE),平均绝对误差 (MAE),Akaike信息标准 (AIC) 和贝叶斯信息标准 (BIC).
- 将Champernowne分布的拟合精度和预测能力与两参数韦布尔分布,三参数韦布尔分布和雷利-赖斯分布进行比较.
主要成果:
- 香珀诺恩分布在所有指标上表现出卓越的表现,实现了最低的RMSE (0.00036) 和MAE (0.00022).
- 与韦布尔 (33%) 和雷利-赖斯 (42%) 分布相比,它提供了更准确的风力发电密度估计 (23%的误差).
- 尽管平均风速低 (2.7 m/s),但该站点的功率密度在18到54 W/m2之间,这表明它不适合大型项目.
结论:
- 珀诺恩分布是建模风速的强大而准确的工具,特别是在风速间歇的地区.
- 传统的大规模风能项目不推用于Ben Guerir;应该考虑小型垂直轴风力轮机 (VAWTs) 或其他替代策略.
- 这项研究为改善风能评估和在具有挑战性的地点进行规划提供了基础.
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