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Issue title: Special Section: Applied Machine Learning and Management of Volatility, Uncertainty, Complexity & Ambiguity (V.U.C.A)
Guest editors: Srikanta Patnaik
Article type: Research Article
Authors: Liu, Yanb; * | Gu, Ya-lib | Wang, Jing-mina
Affiliations: [a] School of Economics and Mangement, North China Electric Power University, China | [b] Key Laboratory of Electric Power Big Data of Guizhou Province, Guizhou Insitute of Technology, China
Correspondence: [*] Corresponding author. Dr. Yan Liu, School of Economics and Mangement, North China Electric Power University, China. E-mail: 20140341@git.edu.cn.
Abstract: With the increasing global energy crisis, wind power is gradually favored by people for its sustainability and cleanliness. When the wind power is connected with the power system, the problem of grid connection must be overcome. In order to better meet the demand load interactive response in smart grid environment, a multi-layer scheduling two-dimensional operation model was proposed. The mechanism of wind power uncertainty was analyzed. Thus, wind power prediction algorithm was established, and the concept of probability based multi-level scheduling was introduced to improve the adaptability of the model as a whole. In order to verify the reliability and effectiveness of the method, case experiments were carried out. The results show that the method can effectively help wind power consumption when ensuring economic and reliable conditions.
Keywords: Smart grid, consumption, load response, power system
DOI: 10.3233/JIFS-179922
Journal: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 2, pp. 1481-1488, 2020
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