Research Output
An Efficient Optimization of Battery-Drone-Based Transportation Systems for Monitoring Solar Power Plant
  Nowadays, developing environmental solutions to ensure the preservation and sustainability of natural resources is one of the core research topics for providing a better life quality. Using renewable energy sources, such as solar energy, is one of the solutions that can reduce the overuse of natural resources. This research aims to boost the efficiency of solar energy plants by proposing a novel approach to optimize the total flying time of battery-based drone systems to enhance the performance of solar plant systems. The contribution of the proposed approach is to solve scheduling problems based on timing constraints to monitor the solar plant. The main objective of the proposed approach is to maximize the drone’s minimum total flying time, which will increase the availability and reliability of the solar plant monitoring system. Time to empty values is calculated based on battery degradation rates. This problem is proven to be NP-hard. Four categories of enhanced algorithms were developed to solve drones’ scheduling problems in handling various tasks within multiple errands in the extent of solar parks in the monitored power plant to achieve the desired objective. Experimental results of the presented algorithms showed that the M2S algorithm has a stable performance behavior in all conducted experiments.

  • Type:


  • Date:

    21 November 2022

  • Publication Status:


  • Publisher

    Institute of Electrical and Electronics Engineers (IEEE)

  • DOI:


  • ISSN:


  • Funders:

    Deanship of Scientific Research at Majmaah University


Jemmali, M., Bashir, A. K., Boulila, W., Melhim, L. K. B., Jhaveri, R. H., & Ahmad, J. (2023). An Efficient Optimization of Battery-Drone-Based Transportation Systems for Monitoring Solar Power Plant. IEEE Transactions on Intelligent Transportation Systems, 24(12), 15633 - 15641.



Sustainable transport, decision-making, drone, information processing, solar power surveillance, zero-carbon, energy management

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