Economic assessment of WECS for water pumping systems in the North Region of Cameroon

Abstract

This paper analyses the potential utilization of wind electric pumping for water distribution in off-grid locations of the North Region of Cameroon (NRoC), using ground measured data as well as long-term satellite-derived data. Furthermore, this paper puts emphasis on statistical indexes of accuracy for the comparison of measured (2007–2012) and long-term satellite-derived (2005–2020) data. The outcome of this study clearly indicates that long-term satellite-derived data, obtained through the Prediction of Worldwide Renewable Energy Resources, can be considered as a viable alternative to missing site-specific data from ground stations, mainly in developing countries. The accuracy of satellite-based wind resource is deemed sufficient to provide a reasonable assessment in the initial phase of wind project planning, before in situ measurements with high accuracy are available. To model wind speeds characteristics, the energy pattern factor method (EPF) has been utilized as one of the reliable Weibull distribution methods for the assessment of wind energy potential at desired turbines heights in the selected locations. Five 20-kW pitch-controlled wind turbines (WT) with a hub height of 30 m, are considered to evaluate the power output and energy produced. Volumetric flow rates and costs of water produced are estimated. The results showed that, out of the eight chosen locations, Figuil shows the best combination of capacity factors (CF) and costs of energy (COE), while the site of Poli displays the worst values of CF and COE, no matter which of the five WT is employed. Thus, selecting WT for low wind speeds regimes, should require to combine location wind resource and WT characteristics such as lower cut-in wind speed (1.5 m/s) as well as lower rated wind speed (8.0 m/s) in order to successfully and affordably implement the wind technology in the NRoC.

Assessment of wind potential for electricity production: case of the rural community of Logone Birni

“…This characterization involves the determination of the mean and variance of the wind data. They are determined by equations ( 1) and (2) [7]:…”

“…In the literature, the Weibull probability distribution is the most widely used model for wind speed distribution characterization, wind potential studies, and wind prediction. This distribution has two parameters: scale parameter c (m.s-1) and shape parameter k (unitless) [5,7,9,10]. Its probability density function f (v) is given by:…”

“…The capacity factor (CF) is defined as the ratio of the average power output (Pe,ave) to the rated electrical power (PeR) of the wind turbine. It is stated as [1,7]: Using different types of wind turbines, the cost of energy generated from wind resources is assessed. The technical specifications of these turbines are given in Table 2.…”

rspatialdata: a collection of data sources and tutorials on downloading and visualising spatial data using R

“…Data retrieved from the NASA POWER Project have been used in a few different applications. For example, POWER data have been used in the study of the potential utilization of wind electric pumping systems for water distribution in Cameroon, 49 in the analysis of photovoltaic systems usage in China 50 and in the study of Dunaliella salina (a type of green micro-algae) cultivation. 51 nasapower 52 aims to make it quick and easy to automate downloading NASA-POWER data in R. In rspatialdata, we show how to use this package to download rainfall and humidity.…”

Technoeconomic Analysis of a Wind Power Generation System and Wind Resource Mapping Using GIS Tools: The Case of Twelve Locations in the Commune of Evodoula, Cameroon

“…Seen through this lens, the energy challenges in terms of the cost of electricity production are important in several countries in the world, including Saudi Arabia, Turkey, Ethiopia, Pakistan, Kuwait, Egypt, and Cameroon, in particular. According to some recent studies presented by [1][2][3], it is clear that Cameroon also has vast renewable resource potential, including the prevalence of wind energy, for electricity generation. Therefore, it is useful to do an assessment of wind energy prospects for the country.…”