Charging Stations Distribution Optimization using Drones Fleet for Disaster Prone Areas

Zohaib Hassan (zohaib.hassan@mail.au.edu.pk), Irtiza Ali Shah and Ahsan Sarwar Rana
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Zohaib Hassan: Electrical and Computer Engineering Department, Air University, Islamabad, Pakistan
Irtiza Ali Shah: Department of Mechanical and Aerospace Engineering, AirUniversity, Islamabad, Pakistan
Ahsan Sarwar Rana: Electrical and Computer Engineering Department, Air University, Islamabad, Pakistan

International Journal of Innovations in Science & Technology, 2022, vol. 4, issue 5, 103-121

Abstract: A disaster is an unforeseen calamity that causes damage to property or brings about a loss of human life. Quick response and rapid distribution of vital relief items into the affected region could save precious lives. In this regard, disaster management comes into play, which is highly dependent on the topography of the disaster-hit area. If the disaster-hit area has little or no road connectivity, the use of drones in such areas becomes essential for the delivery of health packages. Since the battery capacity of the drone is limited, there is a need of charging stations that should be transported using road infrastructure and pre-installed in disaster-prone areas, as access to these areas may be denied once the disaster hits. In this article, a simulation model was used to optimize the number and location of drone charging stations for deployment in a disaster-prone area in the pre-disaster scenario, aiming at the distribution of relief items to disaster-hit areas in the post-disaster scenario. We consider the relative priority of locations where a preference is given to the locations that have higher priority levels. An optimal number of charging stations and optimal routes have also been determined by using our optimization model. To illustrate the use of our model, numerical examples have been simulated for different sizes of the disaster-hit area and the number of targets. In our numerical simulation, it was observed that the drone's maximum distance capacity is the key factor in determining the optimal grid size, which directly correlates to the number of charging stations.

Keywords: Drone Charging Stations; Prepadness and Response; Drone Path Planning; Energy Optimization; Drone Recharging (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:abq:ijist1:v:4:y:2022:i:5:p:103-121

DOI: 10.33411/IJIST/2022040509

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