An Improved Generative Adversarial Network for Extreme Scenarios Generation-Reference-Cited by-同舟云学术

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An Improved Generative Adversarial Network for Extreme Scenarios Generation

Published:2023-12-15 Issue: Volume:46 Page:1472-1477
ISSN:
Container-title:2023 IEEE 7th Conference on Energy Internet and Energy System Integration (EI2)
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Author:

Hongxia GUO¹,Yuan LI¹,Lingxuan CHEN¹,Ziqiang WANG²,Qian MA²,Yiming LIU³

Affiliation:

1. School of Electric Power Engineering, South China University of Technology,Guangzhou,CHINA

2. Power Dispatching and Control Center of China Southern Power Grid,Guangzhou,CHINA

3. Guangdong Electric Power Design Institute Co Ltd. of China Energy Engineering Group,Guangzhou,CHINA

Funder

National Key Research and Development Program of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10511272/10512350/10512990.pdf?arnumber=10512990

Reference12 articles.

1. Analysis and Enlightenme nt of Extremely Cold Weather Power Outage in Texas, US in 2021;Haiwang;Automation Electric of Power Systems,2022

2. Power Supply Challenges and Prospects in New Power System fro m Sichuan Electricity Curtailment Events Caused by High-temperat ure Drought Weather;GAO

3. Optimal allocation for multi-e nergy complementary microgrid based on scenario generation of wi nd power and photovoltaic output;Bai;Automation of Electric Power Systems,2018

4. A wind power time series modeling method based on the improved Markov chain Monte Carlo meth od;Chenxi;Transactions of China Electrotechnical Society,2020

5. Optimal config uration of soft open point for active distribution network considerin g the characteristics of distributed generation;Wang

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