A Model Predictive Control Scheme for Flight Scheduling and Energy Management of Electric Aviation Networks

Abstract

This paper presents a Model Predictive Control (MPC) scheme for flight scheduling and energy management of electric aviation networks, where electric aircraft transport passengers between electrified airports equipped with sustainable energy sources and battery storage, with the goal of minimizing grid dependency. Specifically, we first model the aircraft flight and charge scheduling problem jointly with the airport energy management problem, explicitly accounting for local weather forecasts. Second, we frame the minimum-grid-energy operational problem as a mixed-integer linear program and solve it in a receding horizon fashion, where the route assignment and charging decisions of each aircraft can be dynamically reassigned to mitigate disruptions. We showcase the proposed MPC scheme on real-world data taken from a conventional flight network and weather conditions in the US American North East. The proposed framework saves between 10 and 37% of grid energy requirements when compared to a baseline without re-routing. Hence, results show that MPC can effectively guarantee operation of the network by efficiently re-assigning flights and rescheduling aircraft charging, while maximizing the efficiency of the on-site energy systems.