EV semi-dynamic routing and bidirectional dynamic wireless power transfer for service restoration in coupled traffic-power networks

With vehicle-to-grid (V2G) technology, electric vehicles (EVs) can serve as emergency power sources for post-disaster grid restoration. Compared to traditional static V2G, dynamic V2G, which relies on dynamic wireless charging roads, allows EVs to participate in service restoration more flexibly and quickly. This paper explores the application of EV bidirectional dynamic wireless power transfer (DWPT) technology in enhancing grid resilience. We propose a coordinated post-disaster service restoration model that integrates several key subtasks: EV semi-dynamic routing, DWPT-based V2G scheduling, dynamic network reconfiguration, and power dispatch. Our model considers heterogeneous vehicles in the traffic network and employs a semi-dynamic traffic assignment approach that integrates a pricing mechanism related to bidirectional DWPT to optimize EV routing and dynamic V2G dispatch for grid support. Additionally, this model accounts for damage to both lines and roads, represented as line outages and road capacity drops, respectively. To address the uncertainties associated with line and road conditions during restoration, we introduce a rolling restoration framework based on stochastic model predictive control. The optimization problem is reformulated as mixed-integer second-order cone programming after convex relaxation and linearization. We employ a heuristic sequential bound tightening algorithm to ensure a tight convex relaxation. Through case studies conducted on a coupled traffic-power network, we demonstrate the effectiveness of the proposed model in facilitating rapid grid restoration.