Sustainable Wireless Services with UAV Swarms Tailored to Renewable Energy Sources
Igor Donevski, Marco Virgili, Nithin Babu, Jimmy Jessen Nielsen,, Andrew J. Forsyth, Constantinos B. Papadias, Petar Popovski

TL;DR
This paper presents a method for optimizing UAV swarm deployment powered by renewable energy sources, considering environmental factors and cost efficiency, with a customized algorithm tested on real-world data.
Contribution
It introduces a novel optimization approach for designing renewable energy-powered UAV swarms, accounting for environmental variability and energy expenditure correlations.
Findings
Optimal locations with mild wind and high solar yield maximize efficiency.
Locations with strong winds and low solar need higher CAPEX investment.
Customized sampling algorithm reduces complexity and improves solution feasibility.
Abstract
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…
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Taxonomy
TopicsUAV Applications and Optimization · Vehicle Routing Optimization Methods · Air Traffic Management and Optimization
