محاسبۀ دقیق وابستگی توان آیرودینامیک توربین بادی به خطای ناهماهنگی یاو و پیچ با استفاده از روش پاسخ درجۀ 2 و معرفی میکروحسگر مناسب برای کاهش این خطا

نوع مقاله : مقاله پژوهشی

نویسندگان

1 آزمایشگاه ساخت ادوات پیشرفتۀ میکرونانو، گروه ریزفناوری و فتونیک، دانشکدۀ سامانه‌های هوشمند، دانشگاه تهران، تهران، ایران

2 گروه ریزفناوری و فتونیک، دانشکدۀ سامانه‌های هوشمند، دانشگاه تهران، تهران، ایران

چکیده

در این مقاله، اثر دو خطای عملیاتی پرتکرار در توربین‌های بادی شامل ناهماهنگی یاو و افست پیچ پره بر پاسخ‌های آیرودینامیکی توربین در دو ناحیۀ عملکردی ناحیۀ ۲ (زیرنامی) و ناحیۀ ۳ (نامی/بالانامی) کمّی‌سازی و مدل‌سازی شد. برای دستیابی به نتایج قابل تعمیم و مقایسه‌پذیر در مقیاس‌های مختلف، سه توربین مرجع ۳٫۴، ۵ و ۱۰ مگاوات انتخاب و شبیه‌سازی‌های زمان‌دامنه باOpenFAST/AeroDyn  مدل BEM در شرایط باد پایا انجام شد؛ سپس کمیت‌های شبه‌ایستا شامل ضریب توان و توان آیرودینامیکی  (و در مراحل میانی گشتاور) از پنجرۀ پایدار استخراج شد. برای پوشش نظام‌مند فضای پارامترها ، از طراحی آزمایش (DOE) استفاده شد و مدل‌های جانشین شبه‌ایستا مبتنی بر سطح پاسخ درجۀ 2 (RSM/QS) به ‌صورت تفکیک‌شده برای ناحیۀ ۲ و ناحیۀ ۳ برازش شدند. اعتبارسنجی با مقایسۀ مستقیم پیش‌بینی‌های مدل جانشین و نتایج OpenFAST (از جمله با نمودار هم‌ارزی) انجام شد و علاوه بر منحنی‌های دوبعدی حساسیت نسبت به یاو/پیچ، نقشه‌ها و سطوح سه‌بعدی پاسخ برای نمایش پیوسته تغییرات و  ارائه شد. در نهایت، با استفاده از معادلات درجۀ 2 نهایی و ضرایب متناظر به‌ عنوان روابط کم‌هزینه، اثر خطای انواع حسگرها بر توان خروجی توربین بادی با روش مونت‌کارلو محاسبه شد و نتایج نشان داد حسگرهای لیدار و میکروالکترومکانیکی کمترین تلفات توان را ایجاد می‌کنند. به‌ طور مشخص، حسگر میکروالکترومکانیکی در سناریوی «فقط یاو» برای هر سه توربین تلفات بدترین ‌حالت را در بازۀ حدود 18/0 تا 1/2  و در سناریوی «خطای سرعت + فرمان پیچ ناشی از آن» در بازۀ حدود 6 تا 10 نشان می‌دهد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Accurate Analysis of Wind Turbine Aerodynamic Power Sensitivity to Yaw and Pitch Errors Using a Second-Order Response Surface Method with a Microsensor for Error Reduction

نویسندگان [English]

  • Kian Rafiei 1
  • Javad Koohsorkhi 2
1 Advanced Micro and Nano devices Lab., Department of MEMS and NEMS, School of Intelligent Systems, University of Tehran, Tehran, Iran
2 Associate Professor at Department of MEMS and NEMS, School of Intelligent Systems, University of Tehran, Tehran, Iran
چکیده [English]

In this study, the effects of two frequent operational errors in wind turbines yaw misalignment and blade pitch offset were quantified and modeled for the turbine aerodynamic response in two operating regions: Region 2 (below-rated) and Region 3 (rated/above-rated). To obtain results that are generalizable and comparable across different scales, three reference turbines (3.4 MW, 5 MW, and 10 MW) were selected and time-domain simulations were performed using OpenFAST/AeroDyn (BEM) under steady wind conditions. Quasi-steady quantities, including the power coefficient and aerodynamic power (and, in intermediate steps, aerodynamic torque), were extracted from the steady-state window. To systematically cover the parameter space , a design of experiments (DOE) approach was applied, and quasi-steady quadratic response-surface surrogate models (RSM/QS) were fitted separately for Regions 2 and 3. Validation was carried out by direct comparison between surrogate predictions and OpenFAST results (including parity plots). In addition to 2D sensitivity curves with respect to yaw and pitch, response maps and 3D surfaces were provided to visualize continuous variations of and across the operating space. Finally, using the final quadratic equations and their coefficients as low-cost relations, the impact of different sensor uncertainties on turbine power output was evaluated via a Monte Carlo method, showing that LiDAR and MEMS sensors yield the smallest power losses. Specifically, for the MEMS sensor, the worst-case (P95) power loss is approximately –  for yaw-only misalignment across all three turbines, and approximately –  for the combined “wind-speed error + induced pitch miscommand” scenario.

کلیدواژه‌ها [English]

  • Yaw Misalignment
  • Pitch misalignment. Blade Element Momentum
  • Response Surface Methodology
  • Sensor Effect
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