Reducing Detrimental Communication Failure Impacts in Microgrids by Using Deep Learning Techniques

Abstract

A Microgrid (MG), like any other smart and interoperable power system, requires device-to-device (D2D) communication structures in order to function effectively. This communication system, however, is not immune to intentional or unintentional failures. This paper discusses the effects of communication link failures on MG control and management and proposes solutions based on enhancing message content to mitigate their detritus impact. In order to achieve this goal, generation and consumption forecasting using deep learning (DL) methods at the next time steps is used. The architecture of an energy management system (EMS) and an energy storage system (ESS) that are able to operate in coordination is introduced and evaluated by simulation tests, which show promising results and illustrate the efficacy of the proposed methods. It is important to mention that, in this paper, three dissimilar topics namely MG control/management, DL-based forecasting, and D2D communication architectures are employed and this combination is proven to be capable of achieving the aforesaid objective.

Defense and Attack Game Strategies of Dual-Network Coupled CPPS with Communication Edge Failures

“…In the first stage of the game, defense resources are allocated to CEs. Among them, certain defense resources are allocated to CEs (6,4), (4,6), (7,6), (6,7), (9,7), (7,9), (13,15), (15,13), (14,7), (7,14), (14,15), (15,14), (16,8), (8,16), (16,17), (17,16), (17,20), (20,17), (18,19), (19,18), (19,20), and (20,19). The failure probabilities p ij during attack are 0.769, 0.769, 0.769, 0.769, 0.769, 0.833, 0.833, 0.833, 0.833, 0.472, 0.472, 0.833, 0.833, 0.714, 0.714, 0.769, 0.769, 0.909, 0.909, 0.625, 0.625, 0.556, and 0.556, respectively.…”

“…Reference [13] proposes a risk assessment algorithm for power communication service routing, which optimizes the traffic channel of communication risk through a dynamic routing constraint algorithm to reduce the risk of power interruption, Reference [14] proposes ant colony optimization algorithms to optimize the power communication line and obtain the shortest distance and the optimal path. Reference [15] considers the impact of communication link failures in device-to-device (D2D) communication structures on the microgrid (MG), and implements MG control and management through deep learning methods.…”