An Improved Two-Stage Deep Reinforcement Learning Approach for Regulation Service Disaggregation in a Virtual Power Plant-Reference-Cited by-同舟云学术

An Improved Two-Stage Deep Reinforcement Learning Approach for Regulation Service Disaggregation in a Virtual Power Plant

Author:

Yi Zhongkai¹^ORCID,Xu Yinliang¹^ORCID,Wang Xue²,Gu Wei³^ORCID,Sun Hongbin⁴^ORCID,Wu Qiuwei¹^ORCID,Wu Chenyu³^ORCID

Affiliation:

1. Tsinghua–Berkeley Shenzhen Institute, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China

2. Alibaba DAMO Academy, Alibaba Group, Beijing, China

3. School of Electrical Engineering, Southeast University, Nanjing, China

4. Department of Electrical Engineering, State Key Laboratory of Power Systems, Tsinghua University, Beijing, China

Funder

Shenzhen Science and Technology Program

Basic and Applied Basic Research Foundation of Guangdong Province

Tsinghua Shenzhen International Graduate School Interdisciplinary Research and Innovation Fund

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Computer Science

Link

Reference41 articles.

3. Reinforcement learning for decision-making and control in power systems: Tutorial, review, and vision;chen;arXiv 2102 01168,2021

Cited by 34 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献