{"title":"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","authors":"T. Otunla, A. Umoren","doi":"10.30880/jst.2022.14.02.005","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":21913,"journal":{"name":"Songklanakarin Journal of Science and Technology","volume":"16 1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Wind Characteristics and Potentials of Two-Parameter Weibull Distribution and Maximum Entropy-Based Distribution Functions at an Equatorial Location\",\"authors\":\"T. Otunla, A. Umoren\",\"doi\":\"10.30880/jst.2022.14.02.005\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":21913,\"journal\":{\"name\":\"Songklanakarin Journal of Science and Technology\",\"volume\":\"16 1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Songklanakarin Journal of Science and Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.30880/jst.2022.14.02.005\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Multidisciplinary\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Songklanakarin Journal of Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30880/jst.2022.14.02.005","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Multidisciplinary","Score":null,"Total":0}
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.
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.