赤道位置双参数威布尔分布和基于最大熵的分布函数的风特征和势

T. Otunla, A. Umoren
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引用次数: 0

摘要

深入了解风的特性和变化对任何地方的风能资源开发都是非常重要的。本研究考察了西非低风赤道地区的风特征,并评估了两种分布函数的潜力。高分辨率的风速和风向数据是从研究区域选择的Nsukka站点获得的。研究了风速和风向的日变化、季节变化和年变化。利用R2和均方根误差(RMSE)对两参数威布尔分布和另一种基于最大熵原理的分布函数的潜力进行评估。结果表明,白天比夜间风大。2月、3月和4月的过渡月份风速最高。旱季比雨季具有更大的能源潜力。主要风向为西南偏南和东部。2月、3月和4月的主要风区是东南部。基于mep和威布尔分布的日、分季节白天和夜间、月和年r2范围在0.90和0.99之间。基于mep和Weibull分布的日RMSE、分季节昼夜RMSE、月RMSE和年RMSE也分别在0.011 ~ 0.075之间。因此,基于mep和Weibull的双参数分布函数均可用于研究地点的风数据建模。
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Wind Characteristics and Potentials of Two-Parameter Weibull Distribution and Maximum Entropy-Based Distribution Functions at an Equatorial Location
Thorough knowledge of the wind characteristics and variations are of great importance in the development of wind energy resource in any location. This study examines the wind characteristics and assess the potential of two distribution functions in a low wind equatorial region of West Africa. High resolution wind speed and direction data were obtained from a site in Nsukka, a location chosen in the region of study. Diurnal, seasonal and annual variations of both the wind speed and directions were examined. The potentials of two-parameter Weibull distribution and another distribution function based on Maximum Entropy principle (MEP) were assessed using R2 and root mean squared error (RMSE). The results indicated that day-time is windier than night-time. The transitions months of February, March and April have the highest wind speed. The dry season has greater energy potential than rainy season. The predominant wind direction lay within the sectors: South-South-West and East. The predominant wind sector for February, March and April is South-East. The R2for daily, sub-seasonal day-time and night-time, monthly, and annual ranged between 0.90 and 0.99 for both MEP-based and Weibull distributions. The daily, sub-seasonal day-time and night-time, monthly, and annual RMSE also ranged between 0.011 to 0.075 for MEP-based and Weibull distribution respectively. Thus, both MEP-based and Weibull two-parameter distribution functions can be used to model wind data at the location of study.
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来源期刊
Songklanakarin Journal of Science and Technology
Songklanakarin Journal of Science and Technology Multidisciplinary-Multidisciplinary
CiteScore
1.10
自引率
0.00%
发文量
0
审稿时长
25 weeks
期刊介绍: Songklanakarin Journal of Science and Technology (SJST) aims to provide an interdisciplinary platform for the dissemination of current knowledge and advances in science and technology. Areas covered include Agricultural and Biological Sciences, Biotechnology and Agro-Industry, Chemistry and Pharmaceutical Sciences, Engineering and Industrial Research, Environmental and Natural Resources, and Physical Sciences and Mathematics. Songklanakarin Journal of Science and Technology publishes original research work, either as full length articles or as short communications, technical articles, and review articles.
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