Agent based modelling and energy planning – Utilization of MATSim for transport energy demand modelling. (1st December 2015)

• Record Type: Journal Article
• Authors: Novosel, T.; Perković, L.; Ban, M.; Keko, H.; Pukšec, T.; Krajačić, G.; Duić, N.
• Is Part Of: Energy. Volume 92:Part 3(2015)
• Page Start: 466
• Page End: 475
• Publication Date: 2015-12-01
• Subjects: Electric vehicles -- Demand side modelling -- Agent-based modelling -- Electrification of transport -- EnergyPLAN -- MATSim; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2015.05.091
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: The transportation sector is one of the major energy consumers in most energy systems and a large portion of the energy demand is linked to road transport and personal vehicles. It accounted for 32.8% of the final energy consumption of Croatia in 2011 making it the second most energy demanding sector. Because of their higher efficiency, a modal switch from conventional ICE (internal combustion engines) to EVs(electric vehicles ) has the potential to greatly reduce the overall energy demand of the transport sector. Our previous work has shown that a transition to EVs in a combination with a modal split from air and road to rail transport can reduce the energy consumption in Croatia by 99 PJ, which is approximately 59%, by the year 2050 when compared to the business as usual scenario. The goal of this paper is to model the hourly distribution of the energy consumption of EVs and use the calculated load curves to test their impact on the Croatian energy system. The hourly demand for the transport sector has been calculated using the agent-based modelling tool MATSim on a simplified geographic layout. The impact EVs have on the energy system has been modelled using EnergyPLAN. Highlights: Agent based modelling of transport demand in Croatia. Agent based modelling can develop hourly distributions of transport demand. Utilization of obtained demand curves for energy planning. The quality of the distribution curve can highly influence the quality of the results. High penetrations of electric vehicles have a positive effect on energy systems.