Uncovering wind power forecasting uncertainty sources and their propagation through the whole modelling chain. (September 2022)

• Record Type: Journal Article
• Authors: Yan, Jie; Möhrlen, Corinna; Göçmen, Tuhfe; Kelly, Mark; Wessel, Arne; Giebel, Gregor
• Is Part Of: Renewable & sustainable energy reviews. Volume 165(2022)
• Publication Date: 2022-09
• Subjects: Wind power -- Forecast uncertainty -- Modelling chain; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.rser.2022.112519
• Languages: English
• ISSNs: 1364-0321

Abstract

Abstract: Wind power forecasting has supported operational decision-making for power system and electricity markets for 30 years. Efforts of improving the accuracy and/or certainty of deterministic or probabilistic wind power forecasts are continuously exerted by academics and industries. Forecast errors and associated uncertainties propagating through the whole forecasting chain, from weather provider to end user, cannot be eliminated completely. Therefore, understanding the uncertainty sources and how these uncertainties propagate throughout the modelling chain is significant to implement more rational and targeted uncertainty mitigation strategies and standardise the forecast and uncertainty validation. This paper presents a qualitative review on wind power forecasting uncertainty. First, the definition of uncertainty sources throughout the forecast modelling chain acts as a guiding line for checking and evaluating the uncertainty of a wind power forecast system/model. For each of the types of uncertainty sources, uncertainty mitigation strategies are provided, starting from the planning phase of wind farms, the establishment of a forecasting system through the operational phase and market phase. Our review finalises with a discussion on uncertainty validation with an example on ramp forecast validation. Highlights are a qualitative review and discussion including: (1) forecasting uncertainty exists and propagates everywhere throughout the entire modelling chain, from the planning phase to the market phase; (2) the mitigation efforts should be exerted in every modelling step; (3) standardised uncertainty validation practice, including why global data samples are required for forecasters to improve model performance and for forecast users to select and evaluate forecast model outputs. Graphical abstract: Highlights: Main source of uncertainty through modelling chain of wind power forecast is defined. Approach to evaluate and mitigate sources of uncertainty from planning, operating to market phase. Improved use, verification and validation of uncertainty are discussed on basis of use cases. Identification of recent trends and future work on uncertainty in wind energy forecasting.