Review of wind power scenario generation methods for optimal operation of renewable energy systems

Jinghua Li, Jiasheng Zhou and Bo Chen

Applied Energy, 2020, vol. 280, issue C, No S0306261920314380

Abstract: Scenario generation is an effective method for addressing uncertainties in stochastic programming for energy systems with integrated wind power. To comprehensively understand scenario generation and optimize solutions for uncertainties, the various methods and applications of scenario generation are classified and discussed in this work. First, the basic concepts are presented and scenario generation methods for addressing stochastic programming problems are discussed. Second, three categories of scenario generation methods are briefly introduced, along with their derived methods, advantages, and disadvantages. Third, an evaluation framework for these methods is established. Subsequently, applications of the scenario generation methods in power systems are discussed to identify the properties of these methods. Further, a comparative analysis and discussion are presented to show the suitability of each scenario generation method and to help choose the appropriate methods for different practical situations. Finally, the current limitations and future works with regard to scenario generation for stochastic programming in wind-power-integrated systems are highlighted and discussed. The results of this study are expected to provide references for applying scenario generation methods to the optimal operation of renewable energy systems.

Keywords: Scenario generation; Stochastic programming; Wind power; Uncertainty; Application strategy (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (36)

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DOI: 10.1016/j.apenergy.2020.115992

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