A cyber-physical restoration method of distribution system considering the impact of restoration sequence for cyber system
Yufan Lu, Nian Liu
Abstract
• The restoration process of cyber system is formulated as a vehicle routing problem with time-window. • Restoration approaches including network reconfiguration, dispatchment of distributed energy resources and mobile resources are exploited. • The time-window modification method is proposed to handle the cyber-physical interaction during the restoration process. • A double-layer optimization problem has been applied to represent the restoration of cyber-physical system. Efficient restoration strategies of distributed cyber-physical system (CPS) are critical for enhancing its resilience under extreme disasters. Moreover, with the wide use of intelligent electronic equipment, there is an increasing coupling between CPS during the restoration process. Therefore, a double-layer optimization problem has been applied to represent the restoration of CPS. A vehicle routing problem with time-window (VRPTW) is proposed to formulate the cyber restoration process in the upper layer, where the time-window constraints are used for general restriction of restoration priority. Physical failures are restored through the application of network reconfiguration, distributed energy resources (DERs), and mobile emergency resources (MERs) for different areas in the lower layer. Furthermore, the time-window modification (TWM) method is proposed to coordinate the restoration between two layers. By adjusting the restoration time-windows flexibly in a flexible manner based on the scale of physical failure, the cyber-physical cooperation is effectively realised, and the restoration costs for both systems reduce efficiently within limited computational time. Case studies with modified IEEE 33-node and 118-node systems are conducted to validate the effectiveness of the proposed approach. The reduction of calculation time by applying the TWM method is demonstrated by comparison. Moreover, the restoration costs are reduced by 16.3 % and 20.4 % for small-scale and large-scale failures respectively by applying the proposed method. © 2017 Elsevier Inc. All rights reserved.