Abstract
Natural disasters such as earthquakes have consecutive impacts on the smart grid because of aftershock activities. To guarantee service requirements and smart grid stable operations, it is a challenge to design a fast and survivable rerouting mechanism. There are few studies that consider concurrent rerouting aiming at multiple services in smart grid communication network, however. Firstly, we formulate the node survivability, link survivability, and path survivability model in terms of the distance from the epicenter to the node and the link of the network. Meanwhile, we introduce the indicator of site difference level which is unique in the smart grid to further restrict the service path. Secondly, to improve the algorithm efficiency and reduce rerouting time, the deep first search algorithm is utilized to obtain the available rerouting set, and then the I-DQN based on the framework of reinforcement learning is proposed to achieve concurrent rerouting for multiple services. The experimental results show that our approach has a better convergence performance and higher survivability as well as the approximate latency in comparison with other approaches.
Highlights
IntroductionSmart grid (SG) is a new bulk power system-integrated automation technology and information technology (e.g., the advanced remote sensing technology, communication technology, information technology, and control technology) with the physical network
Smart grid (SG) is a new bulk power system-integrated automation technology and information technology with the physical network
Inspired by [10], we propose a concurrent rerouting approach for multiple services of smart grid communication network (SGCN) in case of large-scale failures, which is solved under the framework of deep reinforcement learning (DRL)
Summary
Smart grid (SG) is a new bulk power system-integrated automation technology and information technology (e.g., the advanced remote sensing technology, communication technology, information technology, and control technology) with the physical network It offers consumers a reliable, economical, clean, and interactive power supply and various additional services by leveraging powerful demand side management and real-time pricing mechanism, which plays a significant role in the construction of smart cities [1]. SG is a typical cyber-physical system, which consists of two distinguishable and complex networks: the physical power system and the communication network The former is in charge of the energy transmission, and the latter provides the necessary scheduling and control functions in terms of the carried services with the purpose of smooth operations in SG. The combination of 5G, SDN, and SG to achieve faster service deployment has become a serious concern for SGCN reliability [5,6,7]
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