Rooftop Photovoltaic Power Prediction Method Considering the Characteristics of Photovoltaic Blocks-Reference-Cited by-同舟云学术

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Rooftop Photovoltaic Power Prediction Method Considering the Characteristics of Photovoltaic Blocks

Published:2024-06-21 Issue: Volume: Page:17-20
ISSN:
Container-title:2024 6th International Conference on Energy Systems and Electrical Power (ICESEP)
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Author:

Xuan Jingyan¹,Hu Lijuan²,Niu Geng²,Fu Xiaobiao³,Zheng Qiangren¹,Jin Chengri¹,Wu Ming²

Affiliation:

1. State Grid Jilin Electric Power Co., Ltd. Yanbian Power Supply Company,Yanbian,Jilin,China,133000

2. State Grid Shanghai Energy Internet Research Institute Co., LTD.,Beijing,China,100192

3. State Grid Jilin Electric Power Co., LTD.,Changchun,China,133000

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10649893/10651613/10651630.pdf?arnumber=10651630

Reference8 articles.

1. Electricity Production and Sustainable Development: The Role of Renewable Energy Sources and Specific Socioeconomic Factors

2. Data-driven analysis and machine learning for energy prediction in distributed photovoltaic generation plants: A case study in Queensland, Australia

3. Energy; Studies from North China Electric Power University Yield New Data on Energy (A Novel Photovoltaic Array Outlier Cleaning Algorithm Based on Sliding Standard Deviation Mutation) [J];Mathematics Week,2020

4. Research on Theoretical Calculation Methods of Photovoltaic Power Short-Circuit Current and Influencing Factors of Its Fault Characteristics

5. Deriving a minimum set of indicators to assess network component importance

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