This study focuses on analysing the impact of seasonal variations in heat on different parts of a "wind energy system," serving as a representative mechanical system. The proposed methodology utilizes wind rose analysis, offering a straightforward means to assess heat transfer effects, applicable to any mechanical system comprising numerous small heat-dissipating components. Furthermore, this work elucidates the correlation between mechanical component performance and heat dissipation impact, providing breakdown alerts for various wind turbine components. Additionally, it analyses the influence of mechanical part temperatures on energy generation, highlighting how high temperatures can indicate component deterioration, such as bearing damage. Notably, the study focuses on wind speeds ranging from 10 to 15 m/s, a typical operational range for wind turbines. By employing wind rose charts and real-time readings, the graded heat dissipating potential of mechanical parts under various wind velocities and weather conditions is determined. Moreover, the study emphasizes the significance of heat transfer analysis in optimizing wind turbine performance, demonstrating how temperature differentials between mechanical components and the environment, along with increased surface area, affect heat transfer. The proposed analysis underscores the importance of considering heat's impact on each mechanical component in tandem with seasonal environmental temperature fluctuations. The wind rose methodology, integrated with sensor implantation, emerges as a cost-effective tool for studying -level heat variances in mechanical systems, enabling the development of heat profiles for future turbine designs and computational fluid dynamics (CFD) analyses. As heat transfer coefficient increases the wind turbine performance decrease. The heat transfer coefficient decreases 14.28% from rainy to winter season and 42.85% from winter to summer season. The wind rose analysis provides valuable insights into wind patterns and characteristics at a specific location, which can inform decision-making in various fields such as energy, construction, environmental management, and safety planning. As the turbine temperature increases the wind velocity decreases. Here it decreases 28 % from rainy to winter season.
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