The SanoStrategy Wind Turbine (SSWT) represents a significant advancement in wind energy conversion, overcoming many of the limitations of existing turbine designs. Traditional horizontal axis wind turbines (HAWTs) and vertical axis wind turbines (VAWTs), such as Darrieus and Savonius turbines, have several inherent inefficiencies that limit their overall performance. In contrast, the SSWT’s innovative design, with around 80% solidity and a hybrid operating principle, addresses these shortcomings effectively.
Efficiency and Performance Comparison
Traditional HAWTs:
Low Solidity: Traditional HAWTs have narrow blades with low solidity. As a result, most of the air mass passing through the rotor sweep area does not interact with the blades, leading to wasted potential energy.
Optimal Performance Range: HAWTs typically achieve optimal performance within a narrow band of wind speeds, around 10-12 m/s, which is not commonly encountered in many regions.
Low Wind Speed Efficiency: At common wind speeds around 4.5 – 5 m/s, large HAWTs operate with low Tip Speed Ratios (TSRs), leading to suboptimal power coefficients (Cp) and reduced efficiency.
Darrieus and Savonius Turbines:
Darrieus Turbines: These turbines, despite being lift-based, exhibit efficiency that peaks at lower values than HAWTs but are still higher than Savonius turbines. They struggle with performance at low and high wind speeds, similar to HAWTs.
Savonius Turbines: Due to high drag, Savonius turbines achieve significantly lower maximum efficiencies. They are suitable for low-speed applications but not for high-efficiency energy conversion.
SanoStrategy Wind Turbine (SSWT) Advantages
The SSWT’s design addresses the inefficiencies of traditional turbines, offering several key benefits:
High Solidity: With around 80% solidity, the SSWT ensures a larger interaction surface between the wind and the blades. This design maximizes energy conversion efficiency by capturing more wind energy, unlike HAWTs, where a large portion of the wind passes through the rotor without interacting with the blades.
Hybrid Operational Principle: The SSWT operates half the time like a sail and half the time using aerodynamic lift. This hybrid principle ensures high performance even in low wind conditions, maintaining efficiency close to the Betz limit.
Enhanced Low-Speed Performance: The SSWT maintains high efficiency in low wind conditions where HAWTs and Darrieus turbines typically underperform. This characteristic ensures more consistent energy production, making it suitable for a variety of environments.
Overcoming Drag Issues: The SSWT design eliminates the significant drag issues faced by Savonius turbines, thus enhancing overall efficiency and energy conversion capabilities.
Torque in Stall Conditions: Unlike Darrieus turbines, which lose efficiency in stall conditions, the SSWT achieves its highest torque when stalled. This feature ensures consistent performance regardless of wind direction and speed fluctuations.
To illustrate these points, consider the following data and the diagram.
Weibull Distribution of average Wind Speed Probability in North America.
The Weibull distribution provides a probabilistic view of wind speed occurrences over a year. It is characterized by the scale factor (A) and shape factor (k), which determine the likelihood of different wind speeds.
Weibull Distribution Parameters:
Scale factor = 6.8
A=6.8
Shape factor = 1.91
k=1.91
The distribution indicates that moderate wind speeds around 4.5 – 5 m/s are common, while higher wind speeds (10 – 11 m/s) are less frequent. This data is crucial for understanding the real-world performance of wind turbines, as it shows the actual wind conditions they typically encounter.
Efficiency of Large HAWTs at Low Wind Speeds
The efficiency of large HAWTs decreases significantly at lower wind speeds due to several factors:
Low Tip Speed Ratio (TSR): At lower wind speeds, the blade rotational speed is reduced, resulting in a lower TSR. The optimal TSR for large HAWTs is around 7 – 8, which is difficult to maintain at lower wind speeds around 5 – 6 m/s, leading to reduced efficiency.
Power Coefficient (Cp): The power coefficient, which measures the efficiency of converting wind energy into mechanical energy, drops as the wind speed decreases. This is evident from the lower Cp values at reduced TSRs and lower wind speeds.
Weibull Distribution of Wind Speed Probability and HAWT Efficiency
The following diagram combines the Weibull distribution of wind speed probability with the efficiency curve of a large HAWT, NOT directly dependent on Tip Speed Ratio, which can be almost constant in certan conditions for broad wind speed range. It is highlighting the PRACTICAL performance drop at common wind speeds.
Diagram Explanation:
Red Line (Left Axis): Represents the Weibull probability density function, showing the likelihood of various wind speeds. The peak around 4.5 – 5 m/s indicates these speeds are most common.
Blue Line (Right Axis): Shows practical efficiency of a large HAWT at different wind speeds. The efficiency is highest at wind speeds around 10 m/s but drops significantly at lower wind speeds, typical in many regions.
Key Insights from the Diagram:
Common Wind Speeds: Wind speeds around 4.5 – 5 m/s are frequent, as shown by the peak of the Weibull distribution.
Efficiency Drop: The efficiency of large HAWTs drops at these common wind speeds, reinforcing the challenge of maintaining high performance under typical conditions.
Conclusion
The Weibull distribution and efficiency data provide a comprehensive view of the limitations faced by large HAWTs at low wind speeds. This analysis supports the need for turbine designs, like the SanoStrategy Wind Turbine (SSWT), which can maintain high efficiency across a broader range of wind speeds, including those most commonly encountered. The SSWT’s innovative design principles, including high solidity and a hybrid operational mechanism, address these challenges effectively, ensuring better performance in real-world conditions.