Tomas Vacek
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Optimizing electric vehicles charging for enhancing environmental sustainability and reducing carbon emissions of freight transport: case of Czech Republic
Michal Husinec , Wadim Strielkowski , Tomas Vacek , Martin Vondracek doi: http://dx.doi.org/10.21511/ee.15(1).2024.02Environmental Economics Volume 15, 2024 Issue #1 pp. 16-31
Views: 349 Downloads: 96 TO CITE АНОТАЦІЯThe limited infrastructure of charging stations, which is crucial in route planning and total journey time and creates uncertainty in efficiency and operating costs, calls for new economic and statistical methods in sustainability development and environmental economics. This paper aims to examine the challenges of integrating electric vehicles into freight transport to improve distribution logistics’ environmental sustainability, which represents one of the pathways for reducing environmental risk.
The analysis results underscore the inadequacy of the truck charging station network in the Czech Republic. This insufficiency presents an opportunity to enhance environmental sustainability and reduce carbon emissions through strategic analysis and optimizing charging station locations. The difficulty of identifying optimal locations for these stations, given truck availability, requires using multi-criteria decision-making techniques such as the Analytical Network Process (ANP).
Municipalities with limited access to existing logistics facilities were considered during the simulation. This way, 15 new locations were identified for municipalities with insufficient distance to a charging station.
By implementing the ANP method, the study contributes to a more environmentally sustainable transportation infrastructure, highlighting the potential for significant reductions in carbon emissions through improved charging station networks. These results apply to other countries and can provide novel insights on optimizing charging station locations for sustainable economic development and reducing freight transport’s carbon emissions and environmental risks.
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