System resilience enhancement: Smart grid and beyond

doi:10.15302/J-FEM-2017030

Front. Eng

2017, Vol. 4

Issue (3) : 271-282 https://doi.org/10.15302/J-FEM-2017030

REVIEW ARTICLE

System resilience enhancement: Smart grid and beyond

Gang HUANG¹(

), Jianhui WANG², Chen CHEN³, Chuangxin GUO¹, Bingquan ZHU⁴

¹. College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
². Department of Electrical Engineering, Southern Methodist University, Dallas, TX 75205, USA; Energy Systems Division, Argonne National Laboratory, Argonne, IL 60439, USA
³. Energy Systems Division, Argonne National Laboratory, Argonne, IL 60439, USA
⁴. State Grid Zhejiang Electric Power Company, Hangzhou 310027, China

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Abstract

Boosting the resilience of power systems is a core requirement of smart grids. In fact, resilience enhancement is crucial to all critical infrastructure systems. In this study, we review the current research on system resilience enhancement within and beyond smart grids. In addition, we elaborate on resilience definition and resilience quantification and discuss several challenges and opportunities for system resilience enhancement. This study aims to deepen our understanding of the concept of resilience and develop a wide perspective on enhancing the system resilience for critical infrastructures.

Keywords critical infrastructure cyber-physical systems energy systems resilience smart grid

Corresponding Author(s): Gang HUANG

Just Accepted Date: 08 September 2017 Online First Date: 28 September 2017 Issue Date: 30 October 2017

Cite this article:

Gang HUANG,Jianhui WANG,Chen CHEN, et al. System resilience enhancement: Smart grid and beyond[J]. Front. Eng, 2017, 4(3): 271-282.

URL:

https://academic.hep.com.cn/fem/EN/10.15302/J-FEM-2017030
https://academic.hep.com.cn/fem/EN/Y2017/V4/I3/271

Fig.1 Illustration of the relationships among power grids, energy systems, and cyber-physical systems

Fig.2 Milestones of resilience enhancement strategies. The blue storm image indicates disaster scenarios

Fig.3 IRR framework (adopted from Huang et al. (2017))

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