Regional photovoltaic power prediction based on multi-agent federated learning and deep learning-Reference-Cited by-同舟云学术

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Regional photovoltaic power prediction based on multi-agent federated learning and deep learning

Published:2024-05-17 Issue: Volume:49 Page:16-21
ISSN:
Container-title:2024 3rd International Conference on Energy, Power and Electrical Technology (ICEPET)
language:
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Author:

Ding Li¹,Wu Donghui¹,Zhang Cheng¹,Chen Zhangfan¹,Ma Liang¹,Li Zhigang¹,Liu Da¹,Han Bitong¹,Ge Dalin¹

Affiliation:

1. State Grid Digital Technology Holdings Co., Ltd.,Beijing,China,100077

Funder

Science and Technology Project of State Grid

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10625771/10625773/10627618.pdf?arnumber=10627618

Reference10 articles.

1. Review of Ultra-short-term Forecasting Methods for Photovoltaic Power Generation;Dong;J. High Voltage Engineering,2023

2. Analysis of the “Three Norths” Region Wind and PV Power Limitation;Fan;J. North China Electric Power,2016

3. Short-term Interval Probability Prediction of Photovoltaic Power Based on Similar Daily Clustering and QR-CNN-BiLSTM Model;Wang;J. High Voltage Engineering,2022

4. Review of Photovoltaic Power Output Prediction Technology;Lai;J. Transactions of China Electrotechnical Society,2019

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