An Integrated Method for Day-ahead Photovoltaic Power Prediction Considering Error Correction Strategy-Reference-Cited by-同舟云学术

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An Integrated Method for Day-ahead Photovoltaic Power Prediction Considering Error Correction Strategy

Published:2024-04-11 Issue: Volume:39 Page:1477-1483
ISSN:
Container-title:2024 9th Asia Conference on Power and Electrical Engineering (ACPEE)
language:
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Author:

Lv Kexin¹,Miao Xinhui¹,Ye Lin¹,Lv Yan²,Sha Licheng³,Ma Xiaochen²,Yang Liping⁴

Affiliation:

1. China Agricultural University,College of Information and Electrical Engineering,Beijing,China

2. China Electric Power Research Institute Company Limited,Beijing,China

3. State Grid Beijing Electric Power Company,Beijing,China

4. State Grid Beijing Electric Power Company Electric Power Research Institute,Beijing,China

Funder

Science and Technology Project of State Grid

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10532251/10532216/10532561.pdf?arnumber=10532561

Reference14 articles.

1. An ensemble method for short-term wind power prediction considering error correction strategy

2. Applications of Frequency Domain Decomposition and Deep Learning Algorithms in Short-term Load and Photovoltaic Power Forecasting;Qian

3. Combined Approach for Short-term Wind Power Forecasting Under Cold Weather with Small Sample;Lin;Proceedings of the CSEE,2023

4. Ultra-short-term Wind Power Prediction Method Based on IDSCNNAM-LSTM Combination Neural Network;Zhuo;High Voltage Engineering,2022

5. A comparison of day-ahead photovoltaic power forecasting models based on deep learning neural network

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