Strategic Bidding and Trading in Joint Electricity-Carbon Market with Deep Reinforcement Learning-Reference-Cited by-同舟云学术

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Strategic Bidding and Trading in Joint Electricity-Carbon Market with Deep Reinforcement Learning

Published:2023-12-15 Issue: Volume: Page:5183-5189
ISSN:
Container-title:2023 IEEE 7th Conference on Energy Internet and Energy System Integration (EI2)
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Author:

Li Yingjie¹,Leng Di¹,Cao Yuji²,Zhao Huan³,Zhou Xiyuan⁴,Zhao Junhua⁴

Affiliation:

1. Information Center Shenzhen Power Supply Co., Ltd.,Shenzhen,China

2. Center for Crowd Intelligence Shenzhen Institute of Artificial Intelligence and Robotics for Society (AIRS),Shenzhen,China

3. School of Electrical and Electronic Engineering, Nanyang Technological University,Singapore

4. School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen,Shenzhen,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10511272/10512350/10512704.pdf?arnumber=10512704

Reference18 articles.

1. The impact of Renewable Portfolio Standards on carbon emission trading under the background of China’s electricity marketization reform

2. Linear-layer-enhanced quantum long short-term memory for carbon price forecasting

3. Modeling Strategic Behaviors for GenCo with joint Consideration on Electricity and Carbon Markets

4. Strategic Bidding for a Large Consumer

5. Pool equilibria including strategic storage

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