Short-Term Prediction of Photovoltaic Power Based on TCN-LSTM-Attention Model and Kmeans++-Reference-Cited by-同舟云学术

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Short-Term Prediction of Photovoltaic Power Based on TCN-LSTM-Attention Model and Kmeans++

Published:2024-06-05 Issue: Volume: Page:1-5
ISSN:
Container-title:2024 10th International Conference on Power Electronics Systems and Applications (PESA)
language:
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Author:

Yuanjun Chen¹,Jingtao Wu¹,Yuee Wang²,Bin Liang¹,Chunhui Dong²,Lian He¹,Simiao Yu³

Affiliation:

1. Heyuan Power Supply Bureau, Guangdong Power Grid Corporation Limited,Heyuan,China

2. School of Electric Power, South China University of Technology,Guangzhou,China

3. School of Automation Science and Engineering, South China University of Technology,Guangzhou,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10594801/10594781/10594964.pdf?arnumber=10594964

Reference9 articles.

1. Photovoltaic (PV) Impact Assessment for Very High Penetration Levels

2. Improved integration of medium scale PV plants on the distribution network

3. Solar forecasting methods for renewable energy integration

4. Photovoltaic Power Forecasting in Dunhuang based on Recurrent Neural Network

5. Residential Photovoltaic Power Forecasting Considering Division of Weather Type Index Interval

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