Innovative Prepositioning and Dispatching Schemes of Electric Vehicles for Smart Distribution Network Resiliency and Restoration

Mobile power sources (MPS), such as electric vehicles (EVs), potentially improve distribution network (DN) restoration under extreme event conditions. However, employing EVs as a major power source is under researched, as is the prepositioning, routing, and dispatch of large numbers of EVs. This study proposes a three-stage optimization approach to achieve proactive prepositioning, dynamic routing, and dynamic power scheduling for effective assessment of resilience and needy restoration. First, EVs are prepositioned in the DN to enable swift pre-restoration and improve the survival of loads. Second, following an extreme event, EVs are dynamically routed in the DN and transportation system (TS) to improve system recovery. This stage also proposes a novel EV travelling model, bridging consumption rate and distance to study the efficacy of EV's state of charge (SOC) and the participation decision of the EV's user. Third, dynamic power scheduling of EVs is addressed, based on decisions made in the previous two stages. A mixed-integer programming model that addresses matters such as various timeframes of EV dispatch and DS operation, and the connection of road and power networks, is tested via case studies of a three-phase AC IEEE 123-node test system to demonstrate the effectiveness of the proposal.