A Power Data Generation Method Based on CNN-LSTM-GAN for Cable Transmission Line Assessment-Reference-Cited by-同舟云学术

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A Power Data Generation Method Based on CNN-LSTM-GAN for Cable Transmission Line Assessment

Published:2023-12-15 Issue: Volume: Page:2067-2072
ISSN:
Container-title:2023 IEEE 7th Conference on Energy Internet and Energy System Integration (EI2)
language:
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Author:

Zhu ZiXuan¹,Wang Mengwei¹,Wang Zikai²,Liu Runlong³,Zhou Zhenghao⁴,Guo Zelin³,Li Yiyan³

Affiliation:

1. State Grid Shanghai Economics and Technology Research Institute,Shanghai,China

2. Shanghai Artificial Intelligence Research Institute Co., ltd,Shanghai,China

3. College of Smart Energy, Shanghai Jiao Tong University,Shanghai,China

4. College of Electrical and Information Engineering, Hunan University,Changsha,China

Funder

State Grid Corporation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10511272/10512350/10512897.pdf?arnumber=10512897

Reference16 articles.

1. Big Data Analysis-Based Security Situational Awareness for Smart Grid

2. Short-Term Residential Load Forecasting Based on LSTM Recurrent Neural Network

3. Optimal Storage Planning in Active Distribution Network Considering Uncertainty of Wind Power Distributed Generation

4. Load Profile Inpainting for Missing Load Data Restoration and Baseline Estimation

5. Optimal Power Scheduling Using Data-Driven Carbon Emission Flow Modelling for Carbon Intensity Control

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