This paper develops a discrete-event multi-agent simulation model that may support robust and realistic well-to-wheel analysis to assess energy consumption and greenhouse gas emissions of greener technologies applied to container terminal activities. To this end, a discrete-event simulation multi-agent model was specifically developed and validated with real data for the port of Salerno (southern Italy), and a well-to-wheel analysis was carried out by comparing different scenarios with an increasing level of port electrification solutions. A comparison is proposed in terms of consumption and emissions between conventionally fueled and “green” vehicles, including cold ironing technology. The proposed modeling framework makes it possible to simulate highly complex logistics systems in which the environmental and energetic performance of the handling equipment may significantly differ and be significantly affected by human factors and external factors. Our results show that the greener scenario allows higher emissions reduction based on the energy sources used to produce electricity.
A discrete-event multi-agent simulation framework supporting well-to-wheel analysis for greening commercial maritime ports
Fiori, Chiara;Cisternas, Lucas Joel;de Luca, Stefano
2025
Abstract
This paper develops a discrete-event multi-agent simulation model that may support robust and realistic well-to-wheel analysis to assess energy consumption and greenhouse gas emissions of greener technologies applied to container terminal activities. To this end, a discrete-event simulation multi-agent model was specifically developed and validated with real data for the port of Salerno (southern Italy), and a well-to-wheel analysis was carried out by comparing different scenarios with an increasing level of port electrification solutions. A comparison is proposed in terms of consumption and emissions between conventionally fueled and “green” vehicles, including cold ironing technology. The proposed modeling framework makes it possible to simulate highly complex logistics systems in which the environmental and energetic performance of the handling equipment may significantly differ and be significantly affected by human factors and external factors. Our results show that the greener scenario allows higher emissions reduction based on the energy sources used to produce electricity.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.