Reviews on uncertainty analysis of wind power forecasting

Jie Yan, Yongqian Liu, Shuang Han, Yimei Wang and Shuanglei Feng

Renewable and Sustainable Energy Reviews, 2015, vol. 52, issue C, 1322-1330

Abstract: Wind power forecasting (WPF) brings about decision risk to power system operation, because of its certain deviations. The uncertainty analysis of wind power forecasting (WPFUA) or wind power probabilistic forecasting (WPPF) provides probabilistic and confidence levels for decision makers to increase the forecasting certainty. In order to deeply and comprehensively understand WPFUA or WPPF model and then to optimize the forecasting model, the uncertain factors are firstly introduced in this paper. Secondly, the current WPFUA and WPPF methods are classified in terms of model input, modeling principle, express way and forecasting horizons. It summarizes the characteristics, merits and demerits, and application conditions of different methods. Thirdly, two advanced optimization strategies are discussed respectively from temporal and spatial perspectives. Finally, the development direction of uncertainty analysis technology in future is summarized. The objective of this review is, on one hand, to help WPPF users understand the model characteristics from different perspectives and select the most suitable one for various applications. On the other hand, it helps WPPF providers learn and optimize WPPF according to different characteristics.

Keywords: Wind power forecasting; Probabilistic forecasting; Interval forecasting; Uncertainty analysis; Impact factors; Classification; Optimization strategy (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (52)

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DOI: 10.1016/j.rser.2015.07.197

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