# Advances, Progress, and Future Directions of Renewable Wind Energy in Brazil (2000-2025-2050)
## 2 Potential of Wind Energy Resources in Brazil  
### Onshore Wind Energy Potential  
Brazil has a vast territory and great geographical diversity, giving it significant wind power potential for electricity generation. Wind speeds in Brazil vary considerably by region and altitude, which is a crucial factor for wind turbine efficiency. Furthermore, other factors such as capacity factor and wind direction are crucial for optimizing wind energy production [24]. In general, the northeastern and southern regions of Brazil have the highest wind speeds, with the northeast being the most promising area for wind energy. In this region, especially in the states of Rio Grande do Norte, Bahia, and Ceara, winds are more constant and stronger, with average annual speeds that can exceed 8 m/s at an altitude of 80 m, the typical hub height of modern wind turbines. These conditions allow wind farms in these areas to achieve exceptionally high-capacity factors, sometimes exceeding 50%. The capacity factor, which represents the ratio of the energy generated to the maximum possible energy generated if the wind turbine were continuously operated at full capacity, is a key indicator of a wind farm's efficiency. In Brazil, the average capacity factors of onshore and offshore wind farms typically range between 0.35 and 0.50, figures that are among the highest in the world, thanks to the consistency and quality of the winds [24]. The wind's behavior concerning altitude follows a vertical profile known as the exponential law of wind speed, which indicates that wind speed increases with altitude. This is due to the reduction in friction with the Earth's surface. In Brazil, it has been observed that at an altitude of 50 m, wind speeds can be around 6 m/s, while at 100 m, these speeds can increase to 7.5 m/s or more, depending on the region. This characteristic has led to the installation of wind turbines with taller towers and longer blades, capable of capturing stronger and more consistent winds at higher altitudes [24]. In addition to speed and height, wind direction is another critical factor in the planning and operation of wind farms. In Brazil, the prevailing winds in the most favorable regions,such as the northeast, tend to be consistent in direction, making it easier to orient wind turbines to maximize energy capture. The trade winds, which blow from the Atlantic Ocean toward the continent, are particularly important in the northeast, as they provide stable and predictable airflow. This consistency in wind direction reduces wear and tear on wind turbine yaw mechanisms and improves overall system efficiency [24]. The ability to generate electricity with wind turbines is directly related to wind speed, as wind power is proportional to the cube of the wind speed. This means that a small increase in wind speed can result in a significant increase in energy production. Therefore, areas with higher wind speeds at higher altitudes are best suited for installing wind farms. Furthermore, the combination of high-capacity factors and consistent wind direction makes Brazil one of the countries with the greatest potential for wind energy expansion [24]. Based on the 100 m wind speed map the Global Wind Atlas (GWA) provided, Brazil possesses significant wind energy potential. The most favorable wind resource conditions are concentrated mainly in the Northeast and South regions (Figure 3). Wind speeds were analyzed using the Weibull probability distribution, taking into account different altitudes and studying seasonal behavior [25]. Figure 3: Map of the wind potential at an average wind turbine height of 100 m and the location of the 10 largest wind farms under operation in Brazil. Figure 3 also shows the 10 largest onshore wind farms in Brazil by 2025, all connected to the national interconnected electricity system (SIN). The wind energy potential was evaluated using the following steps [26]:  
1. Data Sources * Wind Speed Data: Obtained from (e.g., meteorological stations, reanalysis datasets (ERA5, MERRA-2), and SCADA records).