  Unmanned Aerial Vehicle (UAV) swarms are often required in off-grid
scenarios, such as disaster-struck, war-torn or rural areas, where the UAVs
have no access to the power grid and instead rely on renewable energy.
Considering a main battery fed from two renewable sources, wind and solar, we
scale such a system based on the financial budget, environmental
characteristics, and seasonal variations. Interestingly, the source of energy
is correlated with the energy expenditure of the UAVs, since strong winds cause
UAV hovering to become increasingly energy-hungry. The aim is to maximize the
cost efficiency of coverage at a particular location, which is a combinatorial
optimization problem for dimensioning of the multivariate energy generation
system under non-convex criteria. We have devised a customized algorithm by
lowering the processing complexity and reducing the solution space through
sampling. Evaluation is done with condensed real-world data on wind, solar
energy, and traffic load per unit area, driven by vendor-provided prices. The
implementation was tested in four locations, with varying wind or solar
intensity. The best results were achieved in locations with mild wind presence
and strong solar irradiation, while locations with strong winds and low solar
intensity require higher Capital Expenditure (CAPEX) allocation.
