Stability-Oriented Multiobjective Control Design for Power Converters Assisted by Deep Reinforcement Learning
Author:
Affiliation:
1. School of Electrical Engineering and Telecommunications, UNSW Sydney, Sydney, NSW, Australia
2. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/63/10242191/10197504.pdf?arnumber=10197504
Reference12 articles.
1. Multiagent Deep Reinforcement Learning-Aided Output Current Sharing Control for Input-Series Output-Parallel Dual Active Bridge Converter
2. A Future With Inverter-Based Resources: Finding Strength From Traditional Weakness
3. Twin Delayed Deep Deterministic Policy Gradient (TD3) Based Virtual Inertia Control for Inverter-Interfacing DGs in Microgrids
4. Autonomous Input Voltage Sharing Control and Triple Phase Shift Modulation Method for ISOP-DAB Converter in DC Microgrid: A Multiagent Deep Reinforcement Learning-Based Method
5. Small-Signal Modeling and Parameters Design for Virtual Synchronous Generators
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1. Modeling and Deep Reinforcement Learning Based Control Parameter Tuning for Voltage Source Converter in a Renewable Energy Generation System;Journal of Electrical Engineering & Technology;2024-02
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3. Direct Current Control of Grid Connected Two Level Inverter With LCL-Filter Using Deep Reinforcement Learning Algorithm;IEEE Access;2024
4. Impedance-Based Stability of Grid-Connected DC Distribution Power Systems: AC- and DC-Side Stability Criteria, Equivalence, and Difference;IEEE Journal of Emerging and Selected Topics in Power Electronics;2023-12
5. A Physics-Informed Pattern Recognition Method for Open-Circuit Fault Detection of Inverters Under Unexpected Conditions;IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society;2023-10-16
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