A novel integrated method for short-term wind power forecasting based on fluctuation clustering and history matching-Reference-Cited by-同舟云学术

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A novel integrated method for short-term wind power forecasting based on fluctuation clustering and history matching

Published:2022-12 Issue: Volume:327 Page:120131
ISSN:0306-2619
Container-title:Applied Energy
language:en
Short-container-title:Applied Energy

Author:

Ye Lin,Li Yilin,Pei Ming,Zhao Yongning,Li Zhuo,Lu Peng

Funder

National Natural Science Foundation of China

State Grid Corporation of China

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Mechanical Engineering,General Energy,Building and Construction

Reference45 articles.

1. Short-term nodal voltage forecasting for power distribution grids: An ensemble learning approach;Wang;Appl Energy,2021

2. Global Wind Energy Council. Global wind statistics (2021), p. 2021.

3. Review of meta-heuristic algorithms for wind power forecasting: Methodologies, applications and challenges;Lu;Appl Energy,2021

4. A novel bidirectional mechanism based on time series model for wind power forecasting;Zhao;Appl Energy,2016

5. Numerical weather prediction enhanced wind power forecasting: Rank ensemble and probabilistic fluctuation awareness;Liu;Appl Energy,2022

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