TY - JOUR
T1 - Leveraging Energy Function Virtualization with Game Theory for Fault-Tolerant Smart Grid
AU - Wang, Kuan
AU - Wu, Jun
AU - Zheng, Xi
AU - Jolfaei, Alireza
AU - Li, Jianhua
AU - Yu, Dongjin
N1 - Funding Information:
Manuscript received January 5, 2020; revised January 13, 2020; accepted January 20, 2020. Date of publication February 4, 2020; date of current version October 23, 2020. This work was supported by the National Natural Science Foundation of China under Grant 61972255. Paper no. TII-20-0061. (Corresponding author: Jun Wu.) Kuan Wang is with the School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China (e-mail: wangkuanfyfy@sjtu.edu.cn).
Publisher Copyright:
© 2005-2012 IEEE.
PY - 2021/1
Y1 - 2021/1
N2 - As major infrastructures are increasingly depending on electricity, the smart grid has become an important base for industrial manufacturing and residential living. Despite the benefits of smart grids, the reliability and continuity of power services are often threatened by severe nature disasters and human errors. In smart grids, the centralized and often large-sized grid equipment hinder the rapid recovery and flexible reconfiguration in an emergency. Meanwhile, the large amount of personal equipment and their invisibility make it difficult for the grid operators to utilize assets optimally and easily. In addition, since the power service is provided by multiple energy functions, which consists voltage transformation, transmission, and storage, only considering the restoration of power generation function will restrict the service capacity and lengthen the response time. To address these problems, this article proposes an energy function virtualization for smart grid to decouple the implementation of energy functions from the underlying physical infrastructure to speed up the deployment and test of energy functions. With the help of distributed infrastructure resources, manager can redeploy energy functions and accelerate the service response in smart grid. To motivate prosumers to contribute private function resources, an optimized network calculus performance assessment scheme and a game theory-based resource orchestration scheme are proposed. Simulation results show that proposed scheme can dynamically adjust the delay factor to shorten the emergency response time.
AB - As major infrastructures are increasingly depending on electricity, the smart grid has become an important base for industrial manufacturing and residential living. Despite the benefits of smart grids, the reliability and continuity of power services are often threatened by severe nature disasters and human errors. In smart grids, the centralized and often large-sized grid equipment hinder the rapid recovery and flexible reconfiguration in an emergency. Meanwhile, the large amount of personal equipment and their invisibility make it difficult for the grid operators to utilize assets optimally and easily. In addition, since the power service is provided by multiple energy functions, which consists voltage transformation, transmission, and storage, only considering the restoration of power generation function will restrict the service capacity and lengthen the response time. To address these problems, this article proposes an energy function virtualization for smart grid to decouple the implementation of energy functions from the underlying physical infrastructure to speed up the deployment and test of energy functions. With the help of distributed infrastructure resources, manager can redeploy energy functions and accelerate the service response in smart grid. To motivate prosumers to contribute private function resources, an optimized network calculus performance assessment scheme and a game theory-based resource orchestration scheme are proposed. Simulation results show that proposed scheme can dynamically adjust the delay factor to shorten the emergency response time.
KW - Emergency response
KW - function virtualization
KW - game theory
KW - resource orchestration
KW - smart grid
UR - http://www.scopus.com/inward/record.url?scp=85096032131&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85096032131&partnerID=8YFLogxK
U2 - 10.1109/TII.2020.2971584
DO - 10.1109/TII.2020.2971584
M3 - Article
AN - SCOPUS:85096032131
SN - 1551-3203
VL - 17
SP - 678
EP - 687
JO - IEEE Transactions on Industrial Informatics
JF - IEEE Transactions on Industrial Informatics
IS - 1
M1 - 8982189
ER -