نوع مقاله : مقاله پژوهشی
نویسندگان
1 دانشجوی کارشناسی ارشد، مهندسی مکاترونیک، واحد علوم و تحقیقات، دانشگاه ازاد اسلامی؛ آزمایشگاه ساخت ادوات پیشرفتۀ میکرو نانو، گروه مهندسی سیستم‌های میکرو و نانوالکترومکانیک، دانشکدۀ سامانه‌های هوشمند، دانشگاه تهران
2 گروه ریزفناوری، دانشکدۀ سامانه‌های هوشمند، دانشگاه تهران؛ آزمایشگاه ساخت ادوات پیشرفتۀ میکرو نانو، گروه مهندسی سیستم‌های میکرو و نانوالکترومکانیک، دانشکدۀ سامانه‌های هوشمند، دانشگاه تهران
چکیده
کلیدواژه‌ها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
Wind turbines play a crucial role in renewable energy systems and, with the global shift towards sustainable energy sources, the use of this technology is expanding. This study examines the effect of yaw misalignment on the power coefficient (Cp) of a 5 MW reference wind turbine. Computational Fluid Dynamics (CFD) simulations were carried out for this purpose. Yaw misalignment, defined as the deviation of the rotor axis from the prevailing wind direction, impacts turbine performance by reducing power output and increasing mechanical stresses. The simulation results indicate that even a 2-degree yaw misalignment can result in a 1% reduction in the power coefficient. Furthermore, the performance of various sensors, including traditional anemometers and wind vanes, hot-wire sensors, acoustic sensors, LiDAR, and micro-electromechanical system (MEMS) sensors, were evaluated in terms of accuracy, working range, operational temperature, and response time. The findings reveal that hot-wire, acoustic, and MEMS sensors are superior in detecting yaw angle and wind speed due to their high accuracy, rapid response, and stability in varying environmental conditions. Additionally, MEMS sensors, with their compact design, low energy consumption, and reasonable cost, offer an ideal solution for improving wind turbine performance and reducing maintenance costs. This study highlights the significance of advanced sensors in optimizing wind turbine performance and enhancing wind energy efficiency.
کلیدواژه‌ها [English]
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