A Novel Hybrid Strategy Using Three-Phase Feature Extraction and a Weighted Regularized Extreme Learning Machine for Multi-Step Ahead Wind Speed Prediction

Jujie Wang, Yanfeng Wang and Yaning Li
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Jujie Wang: Climate and Weather Disasters Collaborative Innovation Center, School of Management Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
Yanfeng Wang: Gansu Weather Modification Office, Lanzhou 730020, China
Yaning Li: College of Mathematics and Statistics, Nanjing University of Information Science and Technology, Nanjing 210044, China

Energies, 2018, vol. 11, issue 2, 1-33

Abstract: With the growing penetration of wind power into electric grids, improving wind speed prediction accuracy has become particularly valuable for the exploitation of wind power. In this paper, a novel hybrid strategy based on a three-phase signal decomposition (TPSD) technique, feature extraction (FE) and weighted regularized extreme learning machine (WRELM) is developed for multi-step ahead wind speed prediction. The TPSD including seasonal separation algorithm (SSA), fast ensemble empirical mode decomposition (FEEMD) and variational mode decomposition (VMD) is proposed for the first time to handle the complex and irregular natures of wind speed comprehensively. The FE process is used to capture the useful features of wind speed fluctuations and determine the optimal inputs for a prediction model. The WRELM is employed as a basic predictor for building the prediction model by these selected features. Four real wind speed prediction cases are utilized to evaluate the proposed model, and experimental results verify the effectiveness of the proposed model compared with the benchmark models.

Keywords: multi-step ahead prediction; three-phase signal decomposition; feature selection; weighted regularized extreme learning machine (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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