پیش بینی سرعت و قدرت باد قطعی
ترجمه نشده

پیش بینی سرعت و قدرت باد قطعی

عنوان فارسی مقاله: چشم انداز فعلی در مورد دقت پیش بینی سرعت و قدرت باد قطعی
عنوان انگلیسی مقاله: Current Perspective on the Accuracy of Deterministic Wind Speed and Power Forecasting
مجله/کنفرانس: دسترسی – IEEE Access
رشته های تحصیلی مرتبط: جغرافیا
گرایش های تحصیلی مرتبط: آب و هوا شناسی
کلمات کلیدی فارسی: قطعی، سرعت باد، قدرت باد، دقت پیش بینی، شاخص های آماری نرمال شده
کلمات کلیدی انگلیسی: Deterministic, wind speed, wind power, forecasting accuracy, normalized statistical indicators
نوع نگارش مقاله: مقاله مروری (Review Article)
نمایه: Scopus – Master Journals List – JCR
شناسه دیجیتال (DOI): https://doi.org/10.1109/ACCESS.2019.2951153
دانشگاه: Department of Mechanical and Electrical Engineering, Massey University, Palmerston North 4442, New Zealand
ناشر: آی تریپل ای - IEEE
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2019
ایمپکت فاکتور: 4.641 در سال 2018
شاخص H_index: 56 در سال 2019
شاخص SJR: 0.609 در سال 2018
شناسه ISSN: 2169-3536
شاخص Quartile (چارک): Q2 در سال 2018
فرمت مقاله انگلیسی: PDF
تعداد صفحات مقاله انگلیسی: 18
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: خیر
آیا این مقاله مدل مفهومی دارد: ندارد
آیا این مقاله پرسشنامه دارد: ندارد
آیا این مقاله متغیر دارد: ندارد
کد محصول: E13975
رفرنس: دارای رفرنس در داخل متن و انتهای مقاله
فهرست انگلیسی مطالب

Abstract


I. Introduction


II. Deterministic Wind Speed and Power Forecasting Classification


III. Methodology


IV. Conclusion


Authors


Figures


References

نمونه متن انگلیسی مقاله

Abstract


The intermittent nature of wind energy raised multiple challenges to the power systems and is the biggest challenge to declare wind energy a reliable source. One solution to overcome this problem is wind energy forecasting. A precise forecast can help to develop appropriate incentives and wellfunctioning electric markets. The paper presents a comprehensive review of existing research and current developments in deterministic wind speed and power forecasting. Firstly, we categorize wind forecasting methods into four broader classifications: input data, time-scales, power output, and forecasting method. Secondly, the performance of wind speed and power forecasting models is evaluated based on 634 accuracy tests reported in twenty-eight published articles covering fifty locations of ten countries. From the analysis, the most significant errors were witnessed for the physical models, whereas the hybrid models showed the best performance. Although, the physical models have a large normalized root mean square error values but have small volatility. The hybrid models perform best for every time horizon. However, the errors almost doubled at the medium-term forecast from its initial value. The statistical models showed better performance than artificial intelligence models only in the very short term forecast. Overall, we observed the increase in the performance of forecasting models during the last ten years such that the normalized mean absolute error and normalized root mean square error values reduced to about half the initial values.


Introduction


In recent years, wind power is the most competitively priced technology in many markets. According to Global Wind Energy Council (GWEC) Annual Report 2018 [1], the cumulative wind power installed during 2001 to 2018 is 591 GW that is expected to reach 908 GW by the end of 2023 as shown in Fig. 1. Despite providing more than half of renewables growth [2], the intermittent nature of wind raised multiple challenges to the power systems and is the biggest challenge to declare wind energy a reliable source. The challenges that raised to the power system due to the intermittent nature of wind includes planning and operational difficulties, quality of power, and standard of inter-connections. For example, the system operator needs to allocate additional energy reserves in case any power fluctuation occurs between programmed and actual power produced. This additional reserves would increase the operational costs, which subsequently increases the final energy prices [3]. Albadi and Saadany discussed a detailed review of wind power intermittency impacts on power systems [4]. One solution to overcome this problem is wind energy forecasting. A precise forecast would help to develop appropriate incentives and well-functioning hour-a-head or dayahead electric markets [5].

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