Short-term local prediction of wind speed and wind power based on singular spectrum analysis and locality-sensitive hashing-Reference-Cited by-同舟云学术

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Short-term local prediction of wind speed and wind power based on singular spectrum analysis and locality-sensitive hashing

Published:2018-03 Issue:2 Volume:6 Page:317-329
ISSN:2196-5625
Container-title:Journal of Modern Power Systems and Clean Energy
language:en
Short-container-title:J. Mod. Power Syst. Clean Energy

Author:

LIU Ling,JI Tianyao,LI Mengshi,CHEN Ziming,WU Qinghua

Funder

Guangdong Innovative Research Team Program

State Key Program of National Natural Science

Publisher

Springer Science and Business Media LLC

Subject

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

Link

http://link.springer.com/article/10.1007/s40565-018-0398-0/fulltext.html

Reference26 articles.

1. Wang HZ, Wang GB, Li GQ et al (2016) Deep belief network based deterministic and probabilistic wind speed forecasting approach. Appl Energy 182:80–93

2. Zhang Y, Liu K, Qin L et al (2016) Deterministic and probabilistic interval prediction for short-term wind power generation based on variational mode decomposition and machine learning methods. Energy Convers Manag 112:208–219

3. GWEC. Global wind energy council (gwec)

4. Jung J, Broadwater RP (2014) Current status and future advances for wind speed and power forecasting. Renew Sustain Energy Rev 31(2):762–777

5. Zhang C, Wei H, Zhao X et al (2016) A gaussian process regression based hybrid approach for short-term wind speed prediction. Energy Convers Manag 126:1084–1092

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3. Research on Short-Term Wind Speed Prediction Based on Deep Learning;2023 2nd International Conference on Data Analytics, Computing and Artificial Intelligence (ICDACAI);2023-10-17

4. Research on wind speed behavior prediction method based on multi-feature and multi-scale integrated learning;Energy;2023-01

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