Microgrid Communication Network Optimization During Disaster Relief: A Connectivity Rank Index Based Approach
After disasters, power is urgently needed especially for medical facilities. However, power systems as well as communication systems could be severely damaged during disasters. Thus, power restoration with limited communication resources is a critical task during disaster relief. In this paper, a no...
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| Vydáno v: | IEEE International Conference on Industrial Technology (Online) s. 1 - 6 |
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| Jazyk: | angličtina |
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IEEE
26.03.2025
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| ISSN: | 2643-2978 |
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| Abstract | After disasters, power is urgently needed especially for medical facilities. However, power systems as well as communication systems could be severely damaged during disasters. Thus, power restoration with limited communication resources is a critical task during disaster relief. In this paper, a novel strategy is proposed for communication network optimization in microgrid energy management system (EMS). It applies connectivity rank index (CRI) to measure the importance of edges. The proposed strategy aims to achieve fast response of energy management using least communication resources in disaster relief processes. It relies on CRI to identify redundant edges and removes them from the original network one after another iteratively. Numerical simulations were performed on a 14-node system. Results show that the convergence speed is increased by 79.12% and the communication efficiency is increased by 14.98%, demonstrating the effectiveness of the proposed strategy. |
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| AbstractList | After disasters, power is urgently needed especially for medical facilities. However, power systems as well as communication systems could be severely damaged during disasters. Thus, power restoration with limited communication resources is a critical task during disaster relief. In this paper, a novel strategy is proposed for communication network optimization in microgrid energy management system (EMS). It applies connectivity rank index (CRI) to measure the importance of edges. The proposed strategy aims to achieve fast response of energy management using least communication resources in disaster relief processes. It relies on CRI to identify redundant edges and removes them from the original network one after another iteratively. Numerical simulations were performed on a 14-node system. Results show that the convergence speed is increased by 79.12% and the communication efficiency is increased by 14.98%, demonstrating the effectiveness of the proposed strategy. |
| Author | Tian, Hengrui Zhou, Jin Joshi, Aditya Chow, Mo-Yuen Chen, Guanrong |
| Author_xml | – sequence: 1 givenname: Hengrui surname: Tian fullname: Tian, Hengrui email: tianhengrui@sjtu.edu.cn organization: UM-SJTU Joint Institute, Shanghai Jiao Tong University,Shanghai,China – sequence: 2 givenname: Aditya surname: Joshi fullname: Joshi, Aditya email: asjoshi6@ncsu.edu organization: North Carolina State University,Department of Electrical and Computer Engineering,Raleigh,NC,USA – sequence: 3 givenname: Mo-Yuen surname: Chow fullname: Chow, Mo-Yuen email: moyuen.chow@sjtu.edu.cn organization: UM-SJTU Joint Institute, Shanghai Jiao Tong University,Shanghai,China – sequence: 4 givenname: Jin surname: Zhou fullname: Zhou, Jin email: jzhou@whu.edu.cn organization: School of Mathematics and Statistics, Wuhan University,Wuhan,China – sequence: 5 givenname: Guanrong surname: Chen fullname: Chen, Guanrong email: eegchen@cityu.edu.hk organization: City University of Hong Kong,Department of Electrical Engineering,Hong Kong |
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| Snippet | After disasters, power is urgently needed especially for medical facilities. However, power systems as well as communication systems could be severely damaged... |
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| SubjectTerms | Communication networks Convergence Disaster relief Disasters Energy Management System Energy management systems Indexes Microgrids Network optimization Network topology Numerical simulation Optimization Power systems |
| Title | Microgrid Communication Network Optimization During Disaster Relief: A Connectivity Rank Index Based Approach |
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