  Electric airplanes are expected to take to the skies soon, finding first use
cases in small networks within hardly accessible areas, such as island
communities. In this context, the environmental footprint of such airplanes
will be strongly determined by the energy sources employed when charging them.
This paper presents a framework to optimize aircraft assignment, routing and
charge schedules explicitly accounting for the energy availability at the
different airports, which are assumed to be equipped with renewable energy
sources and stationary batteries. Specifically, considering the daily travel
demand and weather conditions forecast in advance, we first capture the
aircraft operations within a time-expanded directed acyclic graph, and combine
it with a dynamic energy model of the individual airports. Second, aiming at
minimizing grid-dependency, we leverage our models to frame the optimal
electric aircraft and airport operational problem as a mixed-integer linear
program that can be solved with global optimality guarantees. Finally, we
showcase our framework in a real-world case-study considering one week of
operations on the Dutch Leeward Antilles. Our results show that, depending on
weather conditions and compared to current schedules, optimizing flights and
operations in a renewable-energy-aware manner can reduce grid dependency from
18 to 100%, whilst significantly shrinking the operational window of the
airplanes.
