Infrastructure planning for electrified transportation

Abstract

Due to the climate crisis, the importance of reducing greenhouse gas (GHG) has been recognized by governments, private companies and the general public alike. Yet carbon capturing-based approaches are difficult to integrate with transportation, which is one of the largest GHG producing sectors, Therefore, electrification is the only viable approach to reduce emissions from transportation, by greatly increasing the market share of electric vehicles (EVs). However, the mass adoption of either (or both) of battery EVs (BEVs) and fuel cell EVs (FCEVs) require a large amount of supporting infrastructures, particularly the construction of EV charging stations (EVCSs) for BEVs and hydrogen refuelling stations (HRSs) for FCEVs. The goal of this study is to provide effective approaches for the sizing and sitting of EVCSs and HRSs to facilitate the deployment of BEVs and FCEVs. The background and an overview of the thesis are provided in Chapter 1, where the gaps in the current research are pointed out and the objectives of the thesis are formulated. Chapter 2 reviewed the current state of technologies regarding the hydrogen life cycle as well as the popular planning models for EVCSs and HRSs. In Chapter 3, to achieve a competitive strategy from the perspective of private companies, a market-based framework is proposed for the problem of EVCS planning by leveraging Graph Convolutional Network (GCN) and game theory. In Chapter 4, a multi-objective planning model is developed for EVCSs and the expansion of distribution network with significant renewable components while considering uncertainties in EV charging behaviour. Additionally, in Chapter 5, a planning model of HRS maximises the long-term profit while considering different practical constraints. The HRS planning model also addresses short-term demand uncertainty via redistribution. The models that are developed in this study are validated using either synthetic or real-world case studies, and the simulation results showed the effectiveness of the proposed models. Finally Chapter 6 summarises the major achievements of the thesis and provides directions for further research