Towards electric bus system: planning, operating and evaluating

The green transformation of public transportation is an indispensable way to achieve carbon neutrality. Governments and authorities are vigorously implementing electric bus procurement and charging infrastructure deployment programs. At this primary but urgent stage, how to reasonably plan the procurement of electric buses, how to arrange the operation of the heterogeneous fleet, and how to locate and scale the infrastructure are urgent issues to be solved. For a smooth transition to full electrification, this thesis aims to propose systematic guidance for the fleet and charging facilities, to ensure life-cycle efficiency and energy conservation from the planning to the operational phase.One of the most important issues in the operational phase is the charge scheduling for electric buses, a new issue that is not present in the conventional transit system. How to take into account the charging location and time duration in bus scheduling and not cause additional load peaks to the grid is the first issue being addressed. A charging schedule optimization model is constructed for opportunity charging with battery wear and charging costs as optimization objectives. Besides, the uncertainty in energy consumption poses new challenges to daily operations. This thesis further specifies the daily charging schedules with the consideration of energy consumption uncertainty while safeguarding the punctuality of bus services.In the context of e-mobility systems, battery sizing, charging station deployment, and bus scheduling emerge as crucial factors. Traditionally these elements have been approached and organized separately with battery sizing and charging facility deployment termed planning phase problems and bus scheduling belonging to operational phase issues. However, the integrated optimization of the three problems has advantages in terms of life-cycle costs and emissions. Therefore, a consolidated optimization model is proposed to collaboratively optimize the three problems and a life-cycle costs analysis framework is developed to examine the performance of the system from both economic and environmental aspects. To improve the attractiveness and utilization of electric public transportation resources, two new solutions have been proposed in terms of charging strategy (vehicle-to-vehicle charging) and operational efficiency (mixed-flow transport). Vehicle-to-vehicle charging allows energy to be continuously transmitted along the road, reducing reliance on the accessibility and deployment of charging facilities. Mixed flow transport mode balances the directional travel demands and facilities the parcel delivery while ensuring the punctuality and safety of passenger transport

Siting and sizing of charging infrastructure for shared autonomous electric fleets

Business models rooted in shared economy, electrification, and automation are transforming urban mobility. Accounting for how these transformations interact is crucial if synergies are to be exploited. In this paper, we focus on how a cost-effective charging infrastructure for e-mobility can support the emergence of shared, autonomous mobility. This study addresses the problem of siting and sizing of charging stations for a fleet of shared autonomous electric vehicles (SAEVs). We develop a hybrid simulation-optimization model to find locations and numbers of chargers needed to serve charging demands. Our agent-based model provides an enhanced representation of SAEV operations allowing for smart charging and vehicle cruising when parking/charging is not available. Also, we model charging station placement as full covering optimization and solve the location-allocation problem simultaneously. Finally, we employ real-world trip data from ShareNow in Berlin to evaluate our approach for realistic demand patterns under different charging strategies and fleet sizes. The results show that charging station locations depend mostly on the spatial distribution of installation costs and charging demands. Moreover, charging strategies and fleet size affect the charging patterns and the required number of chargers as well as fleet performance

Planning and operation objectives of public electric vehicle charging infrastructures: a review

Planning public electric vehicle (EV) charging infrastructure has gradually become a key factor in the electrification of mobility and decarbonization of the transport sector. In order to achieve a high level of electrification in mobility, in recent years, different studies have been presented, proposing novel practices and methodologies for the planning and operation of electric vehicles charging infrastructure. In this paper, the authors present an up-to-date analysis of the existing literature in this research field, organized by considering the perspectives and objectives of the principal actors/operators of the EV public charging infrastructure value chain. Among these actors, the electric vehicle, the charging operators and service providers, and the power system infrastructure (transmission and distribution system) are analyzed in depth. By classifying the reviewed literature based on this manifold viewpoints approach, this paper aims to facilitate researchers and technology developers in exploring the state-of-the-art methodologies for each actor’s perspective, and identify conflicting interests and synergies in charging infrastructure operation and planning.The authors would like to thank the Research Council of Norway and industry partners for the support in writing this paper under project 295133/E20FuChar—Grid and Charging Infrastructure of the Future https://prosjektbanken.forskningsradet.no/en/project/FORISS/295133?Kilde=F ORISS&distribution=Ar&chart=bar&calcType=funding&Sprak=no&sortBy=score&sortOrder=desc& resultCount=30&offset=0&Fritekst=fuchar&source=FORISS&projectId=295133 (accessed on 23 June 2023). The authors gratefully acknowledge Michele Garau, Bendik Nybakk Torsæter, and Daniel Mota from SINTEF Energy Research for their contribution to the conceptualization and review of the article. The work of Andreas Sumper was supported by the Catalan Institution for Research and Advanced Studies (ICREA) Academia Program.Postprint (published version

Charging infrastructure planning and resource allocation for electric vehicles

With the increasing uptake of electric vehicles (EVs) and relative lag in the development of charging facilities, how to plan charging infrastructure and effectively use existing charging resources have become the top priority for governments, related industry and research communities. This study aims to address two key issues related to EV charging - charging station planning and charging resource allocation. The major contributions of the study are: (1) Introduced a model for charging infrastructure planning based on origin-destination data of EV traffic flows. I first showed how to use the gravity model to calculate point-to-point traffic flows from traffic data at each intersection and further induce the origin-to-destination flow data. Then, I introduced an optimization model for charging allocation based on origin-destination traffic flow data and extended it into a formal model for charging station planning by minimizing the total waiting time of EVs. (2) Applied the charging infrastructure planning model to Sydney Metropolitan charging station planning. I selected a set of representative areas from Sydney metropolitan and collected traffic data for these areas. I then used the gravity model to calculate the EV flow for each route based on possible portions of EVs among all traffic. The optimisation constraints under consideration include charging station locations, total budget and feasibility of charging allocations. Optimisation for chargers at each intersection for different scenarios is solved using the least squares method. (3) Designed an algorithm for charging facility allocation to balance the load of charging stations. By considering the maximum driving range, the number of chargers at charging stations, and waiting time and queue length at each charging station, a queue balancing algorithm is proposed. Numerical experiments were conducted to validate the algorithm based on a linear road scenario. I believe that the outcomes of this research have a great potential to be used for government/industry planning of charging stations and improvement of utilization of charging stations resources

Control and Optimization of Energy Storage in AC and DC Power Grids

Energy storage attracts attention nowadays due to the critical role it will play in the power generation and transportation sectors. Electric vehicles, as moving energy storage, are going to play a key role in the terrestrial transportation sector and help reduce greenhouse emissions. Bulk hybrid energy storage will play another critical role for feeding the new types of pulsed loads on ship power systems. However, to ensure the successful adoption of energy storage, there is a need to control and optimize the charging/discharging process, taking into consideration the customer preferences and the technical aspects. In this dissertation, novel control and optimization algorithms are developed and presented to address the various challenges that arise with the adoption of energy storage in the electricity and transportation sectors. Different decentralized control algorithms are proposed to manage the charging of a mass number of electric vehicles connected to different points of charging in the power distribution system. The different algorithms successfully satisfy the preferences of the customers without negatively impacting the technical constraints of the power grid. The developed algorithms were experimentally verified at the Energy Systems Research Laboratory at FIU. In addition to the charge control of electric vehicles, the optimal allocation and sizing of commercial parking lots are considered. A bi-layer Pareto multi-objective optimization problem is formulated to optimally allocate and size a commercial parking lot. The optimization formulation tries to maximize the profits of the parking lot investor, as well as minimize the losses and voltage deviations for the distribution system operator. Sensitivity analysis to show the effect of the different objectives on the selection of the optimal size and location is also performed. Furthermore, in this dissertation, energy management strategies of the onboard hybrid energy storage for a medium voltage direct current (MVDC) ship power system are developed. The objectives of the management strategies were to maintain the voltage of the MVDC bus, ensure proper power sharing, and ensure proper use of resources, where supercapacitors are used during the transient periods and batteries are used during the steady state periods. The management strategies were successfully validated through hardware in the loop simulation

Human versus automated agents: how user preferences affect future mobility systems

Along with rapid advancements in digital, and physical technologies, shared autonomous electric vehicles are forecasted to gradually complement and replace traditional human-based mobility systems. Information systems play a key role in such a deep socio-technical system to pave the path toward a more sustainable future. This study investigates a hybrid ride-hailing platform of automated and human-driven vehicles. Our focus lies on the demand side where we evaluate the influence of user behaviors on economic and environmental system performance. For this, we employ a data-driven agent-based simulation modeling heterogeneous vehicle and user agents calibrated by rental data of a leading vehicle-sharing company. Our findings declare that diverse customer responses to the introduction of shared autonomous electric vehicles yield significantly different fleet performance and ecological costs. We also observe that the status quo customer communication design of ride-hailing platforms need adjustments to maximize the potentials of future hybrid shared mobility systems

Novel Design and Energy Management Approaches for Seamless Integration and Adoption of Plug-In Electric Vehicles

Electric vehicles (EVs) are witnessing increased utilization throughout the world as an alternative to fossil-fueled vehicles. However, the adoption of EVs and their integration into the power grid is yet to be fully materialized due to several issues, of which two are the most salient. First, the extensive deployment of EVs can bring challenges to the grid if not properly managed. Second, access to a variety of EV supply equipment (EVSE) in different areas is still lacking. To that end, the research in this thesis aims to address these issues through the development of adaptive approaches that enhance the management of EV energy and the development of a charging strategy and a design approach that help to expand the proliferation of EV charging infrastructure. Three approaches that are adaptive to their operator/user preferences are developed to enhance energy management in EVs. The first approach allows adaptive utilization of EV batteries' distributed energy resources in an EV fleet system for concurrent services to the transportation sector and ancillary services market. The second approach is a decentralized quality of service (QoS)-based scheme for peer-peer (P2P) energy trading among EV energy providers and consumers. The proposed mechanism is designed to match energy traders based on consumers' and providers' QoS requirements and offers, respectively. The third approach is a bidirectional smart charging algorithm for EVs considering P2P energy trade, provision of ancillary services to the grid, and utilization of low electricity prices for battery charging. The algorithm incorporates user preferences into the scheduling process enabling it to adapt to various conditions. Further, to expand the proliferation of EV charging infrastructure, this thesis introduces (i) a charging control strategy that does not require a communication network, which in turn reduces additional grid upgrades, and (ii) a design approach for EV parking lots that helps private investors to participate in the growth of charging facilities. The findings of this thesis highlight the efficacy of the proposed approaches in achieving their objectives. This would provide implementable and cost-effective solutions to facilitate EVs deployment and address imminent and timely concerns that limit the wide adoption of EVs into electric distribution infrastructure