Ultra‐short‐term PV power prediction model based on HP‐OVMD and enhanced emotional neural network-Reference-Cited by-同舟云学术

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Ultra‐short‐term PV power prediction model based on HP‐OVMD and enhanced emotional neural network

Published:2022-06-09 Issue:11 Volume:16 Page:2233-2247
ISSN:1752-1416
Container-title:IET Renewable Power Generation
language:en
Short-container-title:IET Renewable Power Gen

Author:

Wang* Yufei¹^ORCID,Yang Qixing¹,Xue Hua¹,Mi Yang¹,Tu Yijun¹

Affiliation:

1. College of Electrical Engineering Shanghai University of Electric Power Yangpu Shanghai China

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Renewable Energy, Sustainability and the Environment

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/rpg2.12514

Reference31 articles.

1. ‘Installed capacity trends IRENA’ https://www.irena.org/solar accessed 19 April2021.

2. Standards and Guidelines for Grid-Connected Photovoltaic Generation Systems: A Review and Comparison

3. Mid-to-long term wind and photovoltaic power generation prediction based on copula function and long short term memory network

4. Review on forecasting of photovoltaic power generation based on machine learning and metaheuristic techniques

5. RBFNN Based Photovoltaic Power Prediction Method with Hiding of Main Influencing Factor

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4. Day-Ahead Photovoltaic Power Forecasting Using Empirical Mode Decomposition Based on Similarity-Day Extension Without Information Leakage;Arabian Journal for Science and Engineering;2023-12-22

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