Modelling the effect of electric aircraft on airport operations and infrastructure

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Doctor, F., Budd, T., Williams, P. D. orcid id iconORCID: https://orcid.org/0000-0002-9713-9820, Prescott, M. and Iqbal, R. (2022) Modelling the effect of electric aircraft on airport operations and infrastructure. Technological Forecasting and Social Change, 177. 121553. ISSN 00401625 doi: 10.1016/j.techfore.2022.121553

Abstract/Summary

Electric aircraft offer the potential for emissions savings towards decarbonising air transport and reducing its contribution to climate change. However, the characteristics of these novel technologies pose questions about how they can be integrated with existing airport infrastructure. Key considerations relate to the time needed to recharge electric aircraft whilst on the ground without adversely affecting operational capacities, and the requirement for airport operators to install electric charging capabilities. The paper applies queuing theory and simulation modelling techniques to help identify potential battery charging regimes for electric aircraft based on potential forecasts of the future electric aircraft fleet. An initial prototype discrete event simulation model was developed to simulate impacts of short-haul electric aircraft on airport capacity to help determine future infrastructural requirements. Computational optimisation techniques were used to determine optimal configurations of single purpose and converted dual purpose aircraft parking stands under different scenarios and charging regimes. The model demonstrated that a future increase in electric aircraft equating to 25% of the global aircraft fleet required the conversion of only 13% of existing parking stands, while maintaining airside capacity and operational efficiency. The findings have important implications for air transport planners and decision makers in the transition to zero emissions and flight.

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Item Type Article
URI https://reading-clone.eprints-hosting.org/id/eprint/103108
Identification Number/DOI 10.1016/j.techfore.2022.121553
Refereed Yes
Divisions Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher Elsevier
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