Optimal Scheduling Of Ev-uav System For Providing Multiple Post-event Relief And Recovery Responses

Recently,natural disasters have been occurring frequently worldwide,posing a threat to the stability of critical infrastructure such as transportation networks and power grids.To ensure the safety of affected individuals and enhance the resilience of the distribution network,it is essential to provide timely disaster relief and recovery efforts.The rapid development of electric vehicles(EVs)and unmanned aerial vehicles(UAVs)has offered new technological solutions for emergency grid restorations and humanitarian logistics.This study investigates the joint EVUAV two-echelon relief and recovery system,especially its coordinated scheduling issues.Firstly,the structure of the EV-UAV system and its operation mode are analyzed.The UAV serves as an emergency delivery unit and leverages its high mobility advantages to overcome adverse conditions such as damaged transportation networks after the disaster.The EV acts as a mobile base station for bulk material transportation and provides power support for UAV maintenance.It also serves as mobile emergency energy storage(MEES)to assist in the restoration of critical loads(CLs).In addition,EV can also obtain emergency power support through Distributed Generators(DG),thereby further enhancing the post-disaster adaptability of the EV-UAV system.Secondly,based on post-disaster rescue conditions and factors such as distributed generator charging and critical loads restoration,a corresponding mixed-integer linear programming(MILP)model for the EV-UAV system is established,taking into account constraints such as energy consumption,energy replenishment,loading capacity,delivery path,and time window.The effectiveness of the model is verified through numerical simulations,and the technical characteristics and application potential of the EV-UAV system in the emergency rescue are explained.Finally,solving the EV-UAV model belongs to an NP-hard problem.The strong coupling of variables in the constraints of each layer leads to a high model complexity,so using commercial solvers alone cannot solve large-scale problems in an acceptable time.Therefore,based on the characteristics of the EV-UAV system,a decoupling parameter calculation method is designed.On this basis,the ALNS-MILP algorithm is developed by combining the adaptive large neighborhood search(ALNS)algorithm with MILP to solve large-scale problems.Through case studies and simulations,the algorithm’s accuracy and stability are demonstrated to be satisfactory,and the maximum error between the results and the exact results is less than 2%.