Multi-step ahead wind speed forecasting using a hybrid model based on two-stage decomposition technique and AdaBoost-extreme learning machine-Reference-Cited by-同舟云学术

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Multi-step ahead wind speed forecasting using a hybrid model based on two-stage decomposition technique and AdaBoost-extreme learning machine

Published:2017-12 Issue: Volume:153 Page:589-602
ISSN:0196-8904
Container-title:Energy Conversion and Management
language:en
Short-container-title:Energy Conversion and Management

Author:

Peng Tian,Zhou Jianzhong,Zhang Chu,Zheng Yang

Funder

National Key R&D Program of China

National Natural Science Foundation of China

National Natural Science of China

Publisher

Elsevier BV

Subject

Energy Engineering and Power Technology,Fuel Technology,Nuclear Energy and Engineering,Renewable Energy, Sustainability and the Environment

Reference33 articles.

1. A novel empirical mode decomposition with support vector regression for wind speed forecasting;Ren;IEEE Trans Neural Networks Learn Syst,2016

2. Soman S S, Zareipour H, Malik O, et al. A review of wind power and wind speed forecasting methods with different time horizons. North American Power Symposium (NAPS), IEEE; 2010. p. 1–8.

3. Comparison of numerical weather prediction based deterministic and probabilistic wind resource assessment methods;Zhang;Appl Energy,2015

4. Review of the use of Numerical Weather Prediction (NWP) Models for wind energy assessment;Al-Yahyai;Renew Sustain Energy Rev,2010

5. Non-parametric hybrid models for wind speed forecasting;Han;Energy Convers Manage,2017

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