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Emergency Load Shedding Strategy for Microgrids Based on Dueling Deep Q-Learning

Can Wang, Hongliang Yu, Lin Chai, Huikang Liu, Binxin Zhu
2021 IEEE Access  
MG EMERGENCY LOAD SHEDDING STRATEGY BASED ON A DUELING DEEP Q-LEARNING This section introduces an islanded MG load shedding strategy based on the dueling deep Q-learning in detail.  ...  To solve the above two problems faced by dueling deep Q learning in the load shedding strategy of an MG [28] , this paper proposes an MG emergency load shedding strategy based on dueling deep Q learning  ... 
doi:10.1109/access.2021.3055401 fatcat:3vinwizfprglpcn7ifgn6dev64

Reinforcement Learning and Its Applications in Modern Power and Energy Systems: A Review

Di Cao, Weihao Hu, Junbo Zhao, Guozhou Zhang, Bin Zhang, Zhou Liu, Zhe Chen, Frede Blaabjerg
2020 Journal of Modern Power Systems and Clean Energy  
Among them, reinforcement learning (RL) is one of the most widely promoted methods for control and optimization problems.  ...  With the growing integration of distributed energy resources (DERs), flexible loads, and other emerging technologies, there are increasing complexities and uncertainties for modern power and energy systems  ...  Reference [97] proposes a DQN-based power system emergency control algorithm via under-voltage load shedding and generator dynamic braking.  ... 
doi:10.35833/mpce.2020.000552 fatcat:42bllvvymfhfxbh42t6a46q4tq

Adaptive Power System Emergency Control using Deep Reinforcement Learning [article]

Qiuhua Huang, Renke Huang, Weituo Hao, Jie Tan, Rui Fan, Zhenyu Huang
2019 arXiv   pre-print
Details of the platform and DRL-based emergency control schemes for generator dynamic braking and under-voltage load shedding are presented.  ...  To address these challenges, for the first time, this paper developed novel adaptive emergency control schemes using deep reinforcement learning (DRL), by leveraging the high-dimensional feature extraction  ...  Guanji Hou for his valuable suggestions and assistance in developing the MPC-based emergency control method in this paper.  ... 
arXiv:1903.03712v2 fatcat:tlnl7if7uvb25ir3oijhihysti

Reinforcement Learning for Decision-Making and Control in Power Systems: Tutorial, Review, and Vision [article]

Xin Chen, Guannan Qu, Yujie Tang, Steven Low, Na Li
2021 arXiv   pre-print
In this paper, we provide a tutorial on various RL techniques and how they can be applied to decision-making in power systems.  ...  As a result, data-driven control techniques, especially reinforcement learning (RL), have attracted surging attention in recent years.  ...  Fundamentals of Deep Learning This subsection presents the fundamentals of deep learning to set the stage for the introduction of DRL.  ... 
arXiv:2102.01168v4 fatcat:ibjelwrjffg5bm7eg3dlw6u3ne

Federated Reinforcement Learning: Techniques, Applications, and Open Challenges [article]

Jiaju Qi, Qihao Zhou, Lei Lei, Kan Zheng
2021 arXiv   pre-print
This paper presents a comprehensive survey of Federated Reinforcement Learning (FRL), an emerging and promising field in Reinforcement Learning (RL).  ...  Starting with a tutorial of Federated Learning (FL) and RL, we then focus on the introduction of FRL as a new method with great potential by leveraging the basic idea of FL to improve the performance of  ...  A dueling deep Q-network based cooperative edge caching method is proposed to overcome the dimensionality curse of RL problem and improve caching performance.  ... 
arXiv:2108.11887v2 fatcat:xtn4dryylngsxfobzypedw2b4q

Deep Reinforcement Learning for Autonomous Internet of Things: Model, Applications and Challenges [article]

Lei Lei, Yue Tan, Kan Zheng, Shiwen Liu, Kuan Zhang, Xuemin Shen
2020 arXiv   pre-print
learning (DRL) for decision making.  ...  The sensors collect information on the system status, based on which the intelligent agents in the IoT devices as well as the Edge/Fog/Cloud servers make control decisions for the actuators to react.  ...  on/off change load shedding cost basic fitted Q-iteration device controller (centralized) [147] time state, DR device on/off state DR devices on/off change load shedding cost basic fitted  ... 
arXiv:1907.09059v3 fatcat:z7yksnu4wve7norrjijnu43kvi

Search Improvement Process-Chaotic Optimization-Particle Swarm Optimization-Elite Retention Strategy and Improved Combined Cooling-Heating-Power Strategy Based Two-Time Scale Multi-Objective Optimization Model for Stand-Alone Microgrid Operation

Fei Wang, Lidong Zhou, Hui Ren, Xiaoli Liu
2017 Energies  
The optimal dispatching model for a stand-alone microgrid (MG) is of great importance to its operation reliability and economy.  ...  A new two-time scale multi-objective optimization model, including day-ahead cursory scheduling and real-time scheduling for finer adjustments, is proposed to optimize the operational cost, load shedding  ...  storage system (ESS) based on the coordinated operation among sources-load-ESS and an improved dispatch strategy of the MT's CCHP operation mode.  ... 
doi:10.3390/en10121936 fatcat:vfk662dhtvg6ncgt5ossw3x4ku

Federated reinforcement learning: techniques, applications, and open challenges

Jiaju Qi, Qihao Zhou, Lei Lei, Kan Zheng
2021 Intelligence & Robotics  
This paper presents a comprehensive survey of Federated Reinforcement Learning (FRL), an emerging and promising field in Reinforcement Learning (RL).  ...  Starting with a tutorial of Federated Learning (FL) and RL, we then focus on the introduction of FRL as a new method with great potential by leveraging the basic idea of FL to improve the performance of  ...  A dueling deep Q-network based cooperative edge caching method is proposed to overcome the dimensionality curse of RL problem and improve caching performance.  ... 
doi:10.20517/ir.2021.02 fatcat:qnnomfmvujcofbiselcf337o2a

2020 Index IEEE Transactions on Vehicular Technology Vol. 69

2020 IEEE Transactions on Vehicular Technology  
+ Check author entry for coauthors ami-mFading Channels With Integer and Non-Integerm; TVT March 2020 2785-2801 Hoang, T.M., Tran, X.N., Nguyen, B.C., and Dung, L.T., On the Performance of MIMO Full-Duplex  ...  . 2020 9938-9950 Hoki, K., see Kawakami, T., TVT Dec. 2020 16168-16172 Hong, C., Shan, H., Song, M., Zhuang, W., Xiang, Z., Wu, Y., and Yu, X., A Joint Design of Platoon Communication and Control Based  ...  ., +, TVT May 2020 5598-5609 A Decision-Making Strategy for Vehicle Autonomous Braking in Emergency via Deep Reinforcement Learning.  ... 
doi:10.1109/tvt.2021.3055470 fatcat:536l4pgnufhixneoa3a3dibdma

CCC 2020 Contents

2020 2020 39th Chinese Control Conference (CCC)   unpublished
LIN Zhaochen, LIU Xiyang, NIU Yinbao, HAO Ning, HE Fenghua 3648 Improved Current-based Droop Control Strategy for Microgrids Inverter . . . . . .  ...  LIU Jun 2113 Molecular Design Based on Q-learning and Maximum Likelihood Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ... 
doi:10.23919/ccc50068.2020.9188973 fatcat:7t2dwrbc3zdcjnyijypuga7yhe