Multi-Agent Graph Convolutional Reinforcement Learning for Dynamic Electric Vehicle Charging Pricing-Reference-Cited by-同舟云学术

Multi-Agent Graph Convolutional Reinforcement Learning for Dynamic Electric Vehicle Charging Pricing

Published:2022-08-14 Issue: Volume: Page:
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Container-title:Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Zhang Weijia¹,Liu Hao²,Han Jindong³,Ge Yong⁴,Xiong Hui⁵

Affiliation:

1. AIT, HKUST (GZ), Guangzhou, China

2. AIT, HKUST (GZ) & CSE, HKUST, Hong Kong, Hong Kong

3. AIT, HKUST (GZ), Hong Kong, Hong Kong

4. The University of Arizona, Tucson, AZ, USA

5. HKUST SHCIRI & AIT, HKUST (GZ) & CSE, HKUST, Hong Kong, Hong Kong

Funder

National Natural Science Foundation of China

Project of Hetao Shenzhen-Hong Kong Science and Technology Innovation Cooperation Zone

Foshan HKUST Projects

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3534678.3539416

Reference45 articles.

1. Ahmed Abdalrahman and Weihua Zhuang . 2020. Dynamic Pricing for Differentiated PEV Charging Services Using Deep Reinforcement Learning . IEEE Transactions on Intelligent Transportation Systems ( 2020 ). Ahmed Abdalrahman and Weihua Zhuang. 2020. Dynamic Pricing for Differentiated PEV Charging Services Using Deep Reinforcement Learning. IEEE Transactions on Intelligent Transportation Systems (2020).

2. Gagangeet Singh Aujla Neeraj Kumar Mukesh Singh and Albert Y Zomaya. 2019. Energy trading with dynamic pricing for electric vehicles in a smart city environment. J. Parallel and Distrib. Comput. (2019) 169--183. Gagangeet Singh Aujla Neeraj Kumar Mukesh Singh and Albert Y Zomaya. 2019. Energy trading with dynamic pricing for electric vehicles in a smart city environment. J. Parallel and Distrib. Comput. (2019) 169--183.

3. CĂtălina Cangea , Petar VeliČković , Nikola Jovanović , Thomas Kipf , and Pietro Liò . 2018 . Towards sparse hierarchical graph classifiers . In NIPS Workshop. CĂtălina Cangea, Petar VeliČković, Nikola Jovanović, Thomas Kipf, and Pietro Liò. 2018. Towards sparse hierarchical graph classifiers. In NIPS Workshop.

4. Qifang Chen , FeiWang, Bri-Mathias Hodge , Jianhua Zhang , Zhigang Li , Miadreza Shafie-Khah , and João PS Catalão . 2017. Dynamic price vector formation modelbased automatic demand response strategy for PV-assisted EV charging stations . IEEE Transactions on Smart Grid ( 2017 ), 2903--2915. Qifang Chen, FeiWang, Bri-Mathias Hodge, Jianhua Zhang, Zhigang Li,Miadreza Shafie-Khah, and João PS Catalão. 2017. Dynamic price vector formation modelbased automatic demand response strategy for PV-assisted EV charging stations. IEEE Transactions on Smart Grid (2017), 2903--2915.

5. Junyoung Chung , Caglar Gulcehre , KyungHyun Cho , and Yoshua Bengio . 2014. Empirical evaluation of gated recurrent neural networks on sequence modeling. arXiv preprint arXiv:1412.3555 ( 2014 ). Junyoung Chung, Caglar Gulcehre, KyungHyun Cho, and Yoshua Bengio. 2014. Empirical evaluation of gated recurrent neural networks on sequence modeling. arXiv preprint arXiv:1412.3555 (2014).

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