Prediction of ultra-short-term wind power based on BBO-KELM method
Author:
Affiliation:
1. School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
Funder
National Natural Science Foundation of China
Publisher
AIP Publishing
Subject
Renewable Energy, Sustainability and the Environment
Link
http://aip.scitation.org/doi/pdf/10.1063/1.5113555
Reference34 articles.
1. Analysis and application of forecasting models in wind power integration: A review of multi-step-ahead wind speed forecasting models
2. Novel Multi-Step Short-Term Wind Power Prediction Framework Based on Chaotic Time Series Analysis and Singular Spectrum Analysis
3. Quantifying the Economic and Grid Reliability Impacts of Improved Wind Power Forecasting
4. A review of combined approaches for prediction of short-term wind speed and power
5. Short-term wind power forecasts by a synthetical similar time series data mining method
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