A Multi-Data Driven Hybrid Learning Method for Weekly Photovoltaic Power Scenario Forecast-Reference-Cited by-同舟云学术

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A Multi-Data Driven Hybrid Learning Method for Weekly Photovoltaic Power Scenario Forecast

Published:2022-01 Issue:1 Volume:13 Page:91-100
ISSN:1949-3029
Container-title:IEEE Transactions on Sustainable Energy
language:
Short-container-title:IEEE Trans. Sustain. Energy

Author:

Li Hui^ORCID,Ren Zhouyang^ORCID,Xu Yan^ORCID,Wenyuan Li^ORCID,Hu Bo^ORCID

Funder

National Key Research and Development Program of China Stem Cell and Translational Research

Complement S&T Program of State Grid Corporation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Renewable Energy, Sustainability and the Environment

Link

http://xplorestaging.ieee.org/ielx7/5165391/9655379/09513537.pdf?arnumber=9513537

Cited by 53 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. Operational day-ahead photovoltaic power forecasting based on transformer variant;Applied Energy;2024-11

2. AI for science: Covert cyberattacks on energy storage systems;Journal of Energy Storage;2024-10

3. Prediction of rainy-day photovoltaic power generation based on Generative Adversarial Networks and enhanced Sparrow Search Algorithm;Computers and Electrical Engineering;2024-10

4. Approximate power flow solutions‐based forecasting‐aided state estimation for power distribution networks;IET Generation, Transmission & Distribution;2024-09-04

5. MISAO: Ultra-Short-Term Photovoltaic Power Forecasting with Multi-Strategy Improved Snow Ablation Optimizer;Applied Sciences;2024-08-19

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