Chance Constrained MDP Formulation and Bayesian Advantage Policy Optimization for Stochastic Dynamic Optimal Power Flow-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Chance Constrained MDP Formulation and Bayesian Advantage Policy Optimization for Stochastic Dynamic Optimal Power Flow

Published:2024-09 Issue:5 Volume:39 Page:6788-6791
ISSN:0885-8950
Container-title:IEEE Transactions on Power Systems
language:
Short-container-title:IEEE Trans. Power Syst.

Author:

Wu Yizhi¹^ORCID,Ye Yujian¹^ORCID,Hu Jianxiong¹^ORCID,Zhao Peilin²^ORCID,Liu Liu²,Strbac Goran³,Kang Chongqing⁴^ORCID

Affiliation:

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

2. Tencent AI Lab, Shenzhen, China

3. Department of Electrical and Electronic Engineering, Imperial College London, London, U.K.

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

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

CCF-Tencent Rhino-Bird Open Research Fund

Science and Technology Program of State Grid

State Key Laboratory of Power System Operation and Control Open Research Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/59/10640202/10602778.pdf?arnumber=10602778

Reference8 articles.

1. On the Feasibility Guarantees of Deep Reinforcement Learning Solutions for Distribution System Operation

2. Safe Off-Policy Deep Reinforcement Learning Algorithm for Volt-VAR Control in Power Distribution Systems

3. Safe Deep Reinforcement Learning for Microgrid Energy Management in Distribution Networks With Leveraged Spatial–Temporal Perception

4. Adaptive Tie-Line Power Smoothing With Renewable Generation Based on Risk-Aware Reinforcement Learning

5. Chance constrained policy optimization for process control and optimization

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3