A Multi-Agent Deep Reinforcement Learning Method for Cooperative Load Frequency Control of a Multi-Area Power System-Reference-Cited by-同舟云学术

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A Multi-Agent Deep Reinforcement Learning Method for Cooperative Load Frequency Control of a Multi-Area Power System

Published:2020-11 Issue:6 Volume:35 Page:4599-4608
ISSN:0885-8950
Container-title:IEEE Transactions on Power Systems
language:
Short-container-title:IEEE Trans. Power Syst.

Author:

Yan Ziming^ORCID,Xu Yan^ORCID

Funder

Ministry of Education

Nanyang Technological University

Singtel Cognitive and Artificial Intelligence Lab for Enterprises

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology

Link

http://xplorestaging.ieee.org/ielx7/59/9239415/09108633.pdf?arnumber=9108633

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1. Alleviating imbalanced problems of reinforcement learning when applying in real-time power network dispatching and control;Expert Systems with Applications;2024-12

2. A survey on load frequency control using reinforcement learning-based data-driven controller;Applied Soft Computing;2024-11

3. Multi-agent reinforcement learning for multi-area power exchange;Electric Power Systems Research;2024-10

4. Cloud model-based intelligent controller for load frequency control of power grid with large-scale wind power integration;Frontiers in Energy Research;2024-09-13

5. Model‐free adaptive load frequency control for power systems with wind penetration under deregulation environment;Asian Journal of Control;2024-09-06

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