Wind energy resource assessment for Vanuatu with accurate estimation of Weibull parameters

Abstract

Wind energy resource assessments for Pentecost Island and Epi Island in Vanuatu were carried out using one year of wind data. The wind data were used to calculate the daily average wind speed, diurnal variation of wind speed and monthly average wind speed. The diurnal variation of wind shear coefficient of the site was also studied and it correlated well with the temperature variation. Ten methods were used to determine the Weibull parameters and the wind power density of the site. The best method was determined using the goodness of fit test/error where the correlation coefficient, coefficient of efficiency, root mean square error, maximum absolute error and maximum absolute percentage error for the 10 methods were compared. It was found that the moments method was the best method for obtaining the shape parameter (k), the scale parameter (A) and the correct wind power density for the Pentecost Island site, whereas for the Epi site, the median and quartiles method performed the best. The mean wind speed for the Pentecost site was 5.60 m/s, while that for the Epi site was 5.86 m/s. The Weibull parameters were also estimated for the two seasons for both the islands. The wind resource maps showing the wind power density were also obtained. The annual energy production from 10 Vergnet 275 kW wind turbines, positioned at good locations on the digital wind map, was estimated. Finally, an economic analysis of the turbines was carried out, which indicated a payback period of 4.85 years.

Wind Energy Resource Assessment for Cook Islands With Accurate Estimation of Weibull Parameters Using Frequentist and Bayesian Methods

“… Barometric pressure sensor  Temperature sensor (enclosed in a circular sixplate radiation shield) [13,17].…”

“…The eleven frequentist methods used were: the median and quartiles method (MQ) [43], the moments method (MO) [44], the empirical method of Justus (EMJ) [43], the empirical method of Lysen (EML) [43], the least squares method [45], the maximum likelihood method (ML) [43], the modified maximum likelihood (MML) [43], the energy pattern factor method (EPF) [43], the WAsP method [45,46], new moments method (NMO) [47] and combined energy pattern and power density method (CEPPD) [48]. The description of the methods are presented in our previous publication [13,17]. (5)…”

“…Thus, it can be seen that most of the previous researchers used 6-8 methods for estimating the Weibull parameters and for finding the accurate wind power density. In recent wind resource assessments carried out for Suva [17], Kadavu [36], Vanuatu [13] and Tuvalu [37] in the South Pacific, the authors used 10 different methods for estimating Weibull parameters. This work uses an additional method, called combined energy pattern and power density method (CEPPD) for estimating the Weibull parameters and wind power density.…”

Towards a sustainable 2022 FIFA World Cup in Qatar: Evaluation of wind energy potential for three football stadiums

“…As a complementary method, the Weibull distribution is employed. There are several approaches to this method, like those indicated by Singh et al. (2019) and by Sumair et al.…”

“…As a complementary method, the Weibull distribution is employed. There are several approaches to this method, like those indicated by Singh et al (2019) and by Sumair et al (2020); however, all of these techniques are related and are used as a step to calculate the wind's energy potential in certain location. In the present study, the selected method determines the wind regime's characteristics, based on two parameters (shape and scale) (El Khchine et al, 2019).…”