Development of Short-Term Wind Power Forecasting Methods-Reference-Cited by-同舟云学术

Development of Short-Term Wind Power Forecasting Methods

Published:2022-12-05 Issue: Volume: Page:
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Container-title:2022 IEEE 7th Southern Power Electronics Conference (SPEC)
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Author:

Cao Bo¹,Chang Liuchen¹

Affiliation:

1. University of New Brunswick,Dept. of Elec. & Comp. Eng.,Fredericton,Canada

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10058186/10058061/10058414.pdf?arnumber=10058414

Reference21 articles.

1. Rough Deep Neural Architecture for Short-Term Wind Speed Forecasting

2. A novel hybrid model for short-term wind power forecasting

3. Short-Term Load Forecasting With Deep Residual Networks

4. Short-term forecasting using advanced physical modelling: the results of the anemos project;giebel;Proceedings of the European Wind Energy Conference,2006

5. Wind speed prediction using a hybrid model of the multi-layer perceptron and whale optimization algorithm

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