Imperial College London
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Professor Yujian Ye

Faculty of Engineering, Department of Electrical and Electronic Engineering

Honorary Lecturer
 
 
 
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Contact

 

yujian.ye11

 
 
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Location

 

1105Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Qiu:2024:10.1109/tpwrs.2023.3276827,
author = {Qiu, D and Wang, Y and Wang, J and Zhang, N and Strbac, G and Kang, C},
doi = {10.1109/tpwrs.2023.3276827},
journal = {IEEE Transactions on Power Systems},
pages = {3401--3416},
title = {Resilience-oriented coordination of networked microgrids: a shapley Q-value learning approach},
url = {http://dx.doi.org/10.1109/tpwrs.2023.3276827},
volume = {39},
year = {2024}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - High-impact and low-probability extreme events have occurred more frequently than before because of rapid climate change, which can seriously damage distribution systems. However, conventional distribution management can be dysfunctional after an event, destroying its centralized supervision towards resilience enhancement. In this context, networked microgrids (NMGs) with distributed energy resources provide a viable solution for the resilience enhancement of distribution systems. Existing literature tends to employ model-based optimization approaches for resilient operations of NMGs, which require complete system models and can be time-consuming. To address these challenges, this article suggests a decentralized framework for resilience-oriented coordination of NMGs and proposes a novel multi-agent reinforcement learning (MARL) method to solve it. Specifically, the proposed MARL method develops an efficient credit assignment scheme for NMGs to learn their contributions to the distribution system resilience via the Shapley Q-value technique with more efficient resilience enhancement. Case studies based on two modified IEEE 15- and 69-bus distribution networks are conducted to validate the effectiveness of the proposed MARL method in enabling effective coordination among NMGs and providing a high resilience level.
AU  - Qiu,D
AU  - Wang,Y
AU  - Wang,J
AU  - Zhang,N
AU  - Strbac,G
AU  - Kang,C
DO  - 10.1109/tpwrs.2023.3276827
EP  - 3416
PY  - 2024///
SN  - 0885-8950
SP  - 3401
TI  - Resilience-oriented coordination of networked microgrids: a shapley Q-value learning approach
T2  - IEEE Transactions on Power Systems
UR  - http://dx.doi.org/10.1109/tpwrs.2023.3276827
UR  - http://hdl.handle.net/10044/1/109852
VL  - 39
ER  -
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