Wind energy resource assessment and wind turbine selection analysis for sustainable energy production

• Published in: Scientific reports Vol. 14; no. 1; p. 10708
• Main Authors: Spiru, Paraschiv, Simona, Paraschiv Lizica
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 10.05.2024; Nature Publishing Group; Nature Portfolio
• Subjects: 639/4077; 704/106; 704/158; 704/172; Carbon dioxide; Carbon dioxide emissions; CO2 emission avoided; Electricity; Energy resources; Energy sources; Farm buildings; Gas turbines; Greenhouse gases; Humanities and Social Sciences; Meteorological parameters; Monthly variations; multidisciplinary; Renewable energy analysis; Science; Science (multidisciplinary); Sustainable energy; Sustainable energy production; Turbine engines; Turbines; Wind energy; Wind farms; Wind measurement; Wind power; Wind power density; Wind resource assessment; Wind turbines; Wind energy; Renewable energy analysis; Carbon dioxide; emission avoided; Wind power density; CO; Wind resource assessment; Sustainable energy production; CO2 emission avoided
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-024-61350-6

The objective of this study is to perform an analysis to determine the most suitable type of wind turbine that can be installed at a specific location for electricity generation, using annual measurements of wind characteristics and meteorological parameters. Wind potential analysis has shown that the analyzed location is suitable for the development of a wind farm. The analysis was carried out for six different types of wind turbines, with a power ranging from 1.5 to 3.0 MW and a hub height set at 80 m. Wind power potential was assessed using the Weibull analysis. The values of the scale coefficient c were determined, and a large monthly variation was observed, with values ranging from 1.92 to 8.36 m/s and an annual value of 4.95 m/s. Monthly values for the shape coefficient k varied between 0.86 and 1.53, with an annual value of 1.07. Additionally, the capacity factor of the turbines was determined, ranging from 17.75 to 22.22%. The Vestas turbine, with a nominal power of 2 MW and a capacity factor of 22.22%, proved to be the most efficient wind turbine for the specific conditions of the location. The quantity of greenhouse gas emissions that will be reduced if this type of turbine is implemented was also calculated, considering the average CO 2 emission intensity factor (kg CO 2 /kWh) of the national electricity system.