Ultra-Short Term Photovoltaic Generation Forecasting Based on Data Decomposition and Customized Hybrid Model Architecture-Reference-Cited by-同舟云学术

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Ultra-Short Term Photovoltaic Generation Forecasting Based on Data Decomposition and Customized Hybrid Model Architecture

Published:2024 Issue: Volume:12 Page:20840-20853
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Lee Jooseung¹^ORCID,Kang Jimyung¹^ORCID,Lee Soonwoo¹^ORCID,Oh Hui-Myoung¹^ORCID

Affiliation:

1. Power Grid Research Division, Korea Electrotechnology Research Institute, Ansan, South Korea

Funder

Korea Electrotechnology Research Institute (KERI) Primary Research Program through the National Research Council of Science and Technology

Ministry of Science and Information and Communication Technology

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10419336.pdf?arnumber=10419336

Reference34 articles.

1. Technologies and perspectives for achieving carbon neutrality

2. A Comprehensive Review on Renewable Energy Development, Challenges, and Policies of Leading Indian States With an International Perspective

3. A review of the deployment programs, impact, and barriers of renewable energy policies in Korea

4. Environmental Fault Diagnosis of Solar Panels Using Solar Thermal Images in Multiple Convolutional Neural Networks

5. Review of photovoltaic power forecasting

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Forecasting a Short-Term Photovoltaic Power Model Based on Improved Snake Optimization, Convolutional Neural Network, and Bidirectional Long Short-Term Memory Network;Sensors;2024-06-16

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