A Sequential Optimization-Simulation Approach for Planning the Transition to the Low Carbon Freight System with Case Study in the North Island of New Zealand

Patricio Gallardo,Rua Murray,Susan Krumdieck

doi:10.3390/en14113339

Abstract

Freight movement has always been, and always will be an essential activity. Freight transport is one of the most challenging sectors to transition to net-zero carbon. Traffic assignment, mode allocation, network planning, hub location, train scheduling and terminal design problem-solving have previously been used to address cost and operation efficiencies. In this study, the interdisciplinary transition innovation, management and engineering (InTIME) methodology was used for the conceptualization, redesign and redevelopment of the existing freight systems to achieve a downshift in fossil energy consumption. The fourth step of the InTIME methodology is the conceptualization of a long-term future intermodal transport system that can serve the current freight task. The novelty of our approach stands in considering the full range of freight supply chain factors as a whole, using an optimization-simulation approach as if we were designing the low-carbon system of 2121. For the optimization, ArcGIS software was used to set up a multimodal network model. Route and mode selection were delivered through the optimization of energy use within the network. Complementarily, Anylogic software was used to build a GIS-based discrete event simulation model and set up different experiments to enhance the solution offered by the network analysis. The results outline the resources needed (i.e., number of railway tracks, train speed, size of railyards, number of cranes and forklifts at terminals) to serve the freight task. The results can be backcast to reveal the most efficient investments in the near term. In the case of New Zealand’s North Island, the implementation of strategic terminals, with corresponding handling resources and railyards, could deliver 47% emissions reduction from the sector by 2030, ahead of longer lead-time upgrades like electrification of the railway infrastructure.

Highlights

In 2017, world primary energy consumption reached 9718 Mtoe and the transportation sector was responsible for 27.9% of the total energy demand [1]
Location models involve the selection of facilities that facilitate the optimal movement of goods throughout the network; the objective function represents the sum of fixed facility costs and transportation costs, and the feasibility region is bounded by demand and capacity constraints [20]
If there are no interventions regarding infrastructure, and trucking remains the dominant mode of transportation, energy demand could increase by 86% in the worst-case scenario (FS-NC-T)

Summary

Introduction

In 2017, world primary energy consumption reached 9718 Mtoe (million tons of oil equivalent) and the transportation sector was responsible for 27.9% of the total energy demand [1]. The energy transition of the transport sector is critical since almost all means of transport are heavily dependent on fossil fuels. The strong reliance that the transport sector has on the oil market poses a threat to the future accessibility of essential activities and commodities, due to the finite nature of this resource, its environmental implications and high price volatility [3]. Transitioning the freight transport system is likely to involve a reconfiguration of the broader supply chain. Whole-system analysis of freight transportation includes multiple transport regimes (modal shift to greener modes) as well as niche innovations (vehicle technologies, substitution of energy carriers, relaxation of just-in-time deliveries and localized sourcing) [4,5]. A Comparative Analysis of Behavior-Oriented Commodity Transport Models; TRB: Liedtke, G.T.;

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Results

Conclusion