Affiliation:
1. School of Renewable Energy and Clean Energy, North China Electric Power University, Beijing, China
Abstract
The current study presents a wind resource assessment (WRA) approach by combining existing approaches, including wind probability density estimation based on hourly wind speed frequency, wind power density (WPD) and wind energy density (WED), wind turbine (WT) power output and power curve modeling, and annual energy production (AEP). Wind probability density investigation employed various probability density functions (PDF), including parametric probability density functions such as Weibull, Normal, and Gamma, and non-parametric distribution, including Kernel Density Estimator (KDE). The present study also models the influence of humidity on air density for estimating WPD, WT power output, and AEP. The current study validated the proposed approach by conducting case studies for selected sites of remote Indonesian archipelago islands. AEP estimation proposed by this study can assist the site-turbine fitting design, especially for relatively moist locations.
Subject
Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献