Short-Term Wind Power Probabilistic Prediction for Newly Built Wind Farms Scenarios Based on W-GAN and CNN-LSTM-Reference-Cited by-同舟云学术

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Short-Term Wind Power Probabilistic Prediction for Newly Built Wind Farms Scenarios Based on W-GAN and CNN-LSTM

Published:2022-11-11 Issue: Volume: Page:
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Container-title:2022 IEEE 6th Conference on Energy Internet and Energy System Integration (EI2)
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Author:

Peijie Wei¹,Xiaohai Wang²,Yuhan Xiong³,Xiaosheng Peng¹,Zimin Yang¹,Shuxiang Guo²,Feng Hao²

Affiliation:

1. Huazhong University of Science and Technology,School of Electrical and Electronic Engineering,Wuhan,China

2. Inner Mongolia Power (Group) Co., Ltd,Hohhot,China

3. Huazhong University of Science and Technology,China–EU Institute for Clean and Renewable Energy,Wuhan,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10115460/10115466/10116968.pdf?arnumber=10116968

Reference11 articles.

1. Adjustable Robust Real-Time Power Dispatch With Large-Scale Wind Power Integration

2. A Short-Term Wind Power Forecasting Approach With Adjustment of Numerical Weather Prediction Input by Data Mining

3. A Data-Driven Methodology for Probabilistic Wind Power Ramp Forecasting

4. Additional Capacity Value From Synergy of Variable Renewable Energy and Energy Storage

5. Probabilistic Prediction of Regional Wind Power Based on Spatiotemporal Quantile Regression

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