کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6860362 | 1438739 | 2014 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
An optimized mean variance estimation method for uncertainty quantification of wind power forecasts
ترجمه فارسی عنوان
روش پیش بینی میانگین واریانس بهینه برای تعیین عدم قطعیت پیش بینی های انرژی باد
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کلمات کلیدی
مزرعه باد، میانگین واریانس، فاصله پیش بینی، عدم قطعیت،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
A statistical optimized technique for rapid development of reliable prediction intervals (PIs) is presented in this study. The mean-variance estimation (MVE) technique is employed here for quantification of uncertainties related with wind power predictions. In this method, two separate neural network models are used for estimation of wind power generation and its variance. A novel PI-based training algorithm is also presented to enhance the performance of the MVE method and improve the quality of PIs. For an in-depth analysis, comprehensive experiments are conducted with seasonal datasets taken from three geographically dispersed wind farms in Australia. Five confidence levels of PIs are between 50% and 90%. Obtained results show while both traditional and optimized PIs are hypothetically valid, the optimized PIs are much more informative than the traditional MVE PIs. The informativeness of these PIs paves the way for their application in trouble-free operation and smooth integration of wind farms into energy systems.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Electrical Power & Energy Systems - Volume 61, October 2014, Pages 446-454
Journal: International Journal of Electrical Power & Energy Systems - Volume 61, October 2014, Pages 446-454
نویسندگان
Abbas Khosravi, Saeid Nahavandi,