Estimation of Small Onshore Wind Power Development for Poverty Reduction in Jubek State, South Sudan, Africa

Abstract

Energy security is one of the challenging issues hindering developmental progress in developing countries. Wind power as a renewable energy source can play a significant role in poverty reduction if adequate information is provided. In this study, multi-approach technics were applied for a better understanding of the wind energy potential in Jubek State, South Sudan. Geographic Information System (GIS), remote sensing, and mathematical equations were applied in identifying suitable locations, potential power per unit area, wind farm layout, design of appropriate turbine size, and utilization of wind energy in both agricultural and domestic sectors. Wind speed, land use land cover, and digital elevation maps of the study area were processed in ArcGIS, MATLAB (Weibull distribution), and Minitab software. The results show that 17,331.4 km 2 (94.64%) of the study area is appropriate for wind power generation, with wind density of about 3.65 W/m 2 and installation capacity about 19,757.79 MW, resulting in an annual energy production of about 7269.29 GWh. With the proposed wind turbine, one ton of various crops and animal products require 1-4 and 2-20 turbines, respectively. Therefore, the step-by-step procedures followed in this study will contribute to poverty reduction through improving agricultural productivity and food quality.Sustainability 2020, 12, 1483 2 of 22 indicated that 3% (9 EJ) of the global energy was spent on agriculture, and up to 20% of the greenhouse gas emissions worldwide. It was generally observed that agricultural yield improvements result in positive energy ratios; this can be justified by the gained in using fossil energy as an input for agricultural activities-the harvested crops contain more energy than the energy consumed in crop production [5].A study was conducted by Cranfield University in the UK in order to review energy requirements for agricultural production from the field to the farm gate. They used the life cycle analysis (LCA) approach, which is a recommended method for estimating the cradle to grave, a product or process of environmental impacts. Selected materials were field crops (maize, wheat, sugarcane, beans, oilseed rape, and potatoes) and three animal products in the form of meat (lamb, poultry, beef, and pork), eggs, and milk [6][7][8]. Besides this, [9] reported a detailed work on the transport cost from farm to plate or distance from the production area to consumption zone. Such work is essential for understanding wasted energy and efficiency at an extent which is beyond the farm boundaries.In the LCA, in order to capture all embodied energies, it is necessary to consider all inputs used in the production of a given product. Therefore, the authors included energy used in fertilizer, buildings, machinery, and pesticides together with diesel and other forms of fuel as direct energy. For estimating inputs for animal production, they included energy for producing feed crops. Breeding overhead was also included in their work. Therefore, the final values presented in Table 1...

Wind and Solar Energy for Sustainable Energy Production for Family Farms in Coastal Agricultural Regions of Libya Using Measured and Multiple Satellite Datasets

“…However, due to the lack of measurement data, utilizing data derived from satellite measurements and various reanalysis becomes paramount in advancing the assessment and forecasting of nextgeneration wind and solar resources. These alternative data sources serve as crucial tools for evaluating the potential and economic viability of wind and solar energy in specific locations [60,85,87,89,92,[122][123][124]. The reliability and suitability of these products need to be carefully evaluated before estimating wind and solar resources.…”

“…These datasets are created by combining various sources of observations, including weather station measurements, satellite data, and other relevant sources, using sophisticated mathematical models [76,77]. Many scientific researchers have utilized the satellite database for evaluating the potential of wind energy [78][79][80][81][82][83][84][85][86][87][88][89][90][91][92][93][94][95][96] as shown in Table S1 in the Supplementary Materials. In this study, five SPs were selected based on their high spatial resolution, coverage domain, and periods of availability as shown in Table 3.…”