Comparative Analysis of Offshore Wind Power Prediction Models and Clustering-Based Daily Output Classification
Author:
Affiliation:
1. Zhuhai Power Supply Bureau Guangdong Power Grid Co., Ltd.,Zhuhai,China
2. University of Macau,State Key Laboratory of Internet of Things for Smart City,Macao,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10601630/10601669/10601951.pdf?arnumber=10601951
Reference19 articles.
1. 10,000,000! Guangdong offshore wind power installed capacity exceeds ten million kilowatts;Shen,2024
2. Improvement of ultra-short-term forecast for wind power;Chen;Automation of Electric Power Systems,2011
3. Improved BP neural network algorithm to wind power forecast
4. Multi-step ahead wind speed forecasting using an improved wavelet neural network combining variational mode decomposition and phase space reconstruction
5. Short-Term Wind-Power Prediction Based on Wavelet Transform–Support Vector Machine and Statistic-Characteristics Analysis
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