Final report: Workshop on: Integrating electric mobility systems with the grid infrastructure

EXECUTIVE SUMMARY: This document is a report on the workshop entitled “Integrating Electric Mobility Systems with the Grid Infrastructure” which was held at Boston University on November 6-7 with the sponsorship of the Sloan Foundation. Its objective was to bring together researchers and technical leaders from academia, industry, and government in order to set a short and longterm research agenda regarding the future of mobility and the ability of electric utilities to meet the needs of a highway transportation system powered primarily by electricity. The report is a summary of their insights based on workshop presentations and discussions. The list of participants and detailed Workshop program are provided in Appendices 1 and 2. Public and private decisions made in the coming decade will direct profound changes in the way people and goods are moved and the ability of clean energy sources – primarily delivered in the form of electricity – to power these new systems. Decisions need to be made quickly because of rapid advances in technology, and the growing recognition that meeting climate goals requires rapid and dramatic action. The blunt fact is, however, that the pace of innovation, and the range of business models that can be built around these innovations, has grown at a rate that has outstripped our ability to clearly understand the choices that must be made or estimate the consequences of these choices. The group of people assembled for this Workshop are uniquely qualified to understand the options that are opening both in the future of mobility and the ability of electric utilities to meet the needs of a highway transportation system powered primarily by electricity. They were asked both to explain what is known about the choices we face and to define the research issues most urgently needed to help public and private decision-makers choose wisely. This report is a summary of their insights based on workshop presentations and discussions. New communication and data analysis tools have profoundly changed the definition of what is technologically possible. Cell phones have put powerful computers, communication devices, and position locators into the pockets and purses of most Americans making it possible for Uber, Lyft and other Transportation Network Companies to deliver on-demand mobility services. But these technologies, as well as technologies for pricing access to congested roads, also open many other possibilities for shared mobility services – both public and private – that could cut costs and travel time by reducing congestion. Options would be greatly expanded if fully autonomous vehicles become available. These new business models would also affect options for charging electric vehicles. It is unclear, however, how to optimize charging (minimizing congestion on the electric grid) without increasing congestion on the roads or creating significant problems for the power system that supports such charging capacity. With so much in flux, many uncertainties cloud our vision of the future. The way new mobility services will reshape the number, length of trips, and the choice of electric vehicle charging systems and constraints on charging, and many other important behavioral issues are critical to this future but remain largely unknown. The challenge at hand is to define plausible future structures of electric grids and mobility systems, and anticipate the direct and indirect impacts of the changes involved. These insights can provide tools essential for effective private ... [TRUNCATED]Workshop funded by the Alfred P. Sloan Foundatio

The Critical Role of Public Charging Infrastructure

Editors: Peter Fox-Penner, PhD, Z. Justin Ren, PhD, David O. JermainA decade after the launch of the contemporary global electric vehicle (EV) market, most cities face a major challenge preparing for rising EV demand. Some cities, and the leaders who shape them, are meeting and even leading demand for EV infrastructure. This book aggregates deep, groundbreaking research in the areas of urban EV deployment for city managers, private developers, urban planners, and utilities who want to understand and lead change

Optimization and Integration of Electric Vehicle Charging System in Coupled Transportation and Distribution Networks

With the development of the EV market, the demand for charging facilities is growing rapidly. The rapid increase in Electric Vehicle and different market factors bring challenges to the prediction of the penetration rate of EV number. The estimates of the uptake rate of EVs for light passenger use vary widely with some scenarios gradual and others aggressive. And there have been many effects on EV penetration rate from incentives, tax breaks, and market price. Given this background, this research is devoted to addressing a stochastic joint planning framework for both EV charging system and distribution network where the EV behaviours in both transportation network and electrical system are considered. And the planning issue is formulated as a multi-objective model with both the capital investment cost and service convenience optimized. The optimal planning of EV charging system in the urban area is the target geographical planning area in this work where the service radius and driving distance is relatively limited. The mathematical modelling of EV driving and charging behaviour in the urban area is developed

Stochastic Programming Models For Electric Vehicles’ Operation: Network Design And Routing Strategies

Logistic and transportation (L&T) activities become a significant contributor to social and economic advances throughout the modern world Road L&T activities are responsible for a large percentage of CO2 emissions, with more than 24% of the total emission, which mostly caused by fossil fuel vehicles. Researchers, governments, and automotive companies put extensive effort to incorporate new solutions and innovations into the L&T system. As a result, Electric Vehicles (EVs) are introduced and universally accepted as one of the solutions to environmental issues. Subsequently, L&T companies are encouraged to adopt fleets of EVs. Integrating the EVs into the logistic and transportation systems introduces new challenges from strategic, planning, and operational perspectives. At the strategical level, one of the main challenges to be addressed to expand the EV charging infrastructures is the location of charging stations. Due to the longer charging time in EVs compared to the conventional vehicles, the parking locations can be considered as the candidate locations for installing charging stations. Another essential factor that should be considered in designing the Electric Vehicle Charging Station (EVCS) network is the size or capacity of charging stations. EV drivers\u27 arrival times in a community vary depending on various factors such as the purpose of the trip, time of the day, and day of the week. So, the capacity of stations and the number of chargers significantly affect the accessibility and utilization of charging stations. Also, the EVCSs can be equipped by distinct types of chargers, which are different in terms of installation cost, charging time, and charging price. City planners and EVCS owners can make low-risk and high-utilization investment decisions by considering EV users charging pattern and their willingness to pay for different charger types. At the operational level, managing a fleet of electric vehicles can offer several incentives to the L&T companies. EVs can be equipped with autonomous driving technologies to facilitate online decision making, on-board computation, and connectivity. Energy-efficient routing decisions for a fleet of autonomous electric vehicles (AEV) can significantly improve the asset utilization and vehicles’ battery life. However, employing AEVs also comes with new challenges. Two of the main operational challenges for AEVs in transport applications is their limited range and the availability of charging stations. Effective routing strategies for an AEV fleet require solving the vehicle routing problem (VRP) while considering additional constraints related to the limited range and number of charging stations. In this dissertation, we develop models and algorithms to address the challenges in integrating the EVs into the logistic and transportation systems

Motion Hub, the implementation of an integrated end-to-end journey planner

© AET 2018 and contributorsThe term “eMobility” and been brought into use partly to encourage use of electric vehicles but more especially to focus on the transformation from electric vehicles as products to electrified personal transport as a service. Under the wider umbrella of Mobility-as-a-Service (MaaS) this has accompanied the growth of car clubs in general. The Motion Hub project has taken this concept a step further to include not just the car journey but the end-to-end journey. The booking of multifaceted journeys is well established in the leisure and business travel industries, where flights, car hire and hotels are regularly booked with a single transaction on a website. To complete an end-to-end scenario Motion Hub provides integration of public transport with electric vehicle and electric bike use. Building on a previous InnovateUK funded project that reviewed the feasibility of an integrated journey management system, the Motion Hub project has brought together a Car Club, a University, and EV infrastructure company, a bicycle hire company with electric bicycle capabilities and a municipality to implement a scheme and test it on the ground. At the heart of the project has been the development of a website that integrates the public transport booking with the hire of electric vehicles or bicycles. Taking the implementation to a fully working system accessible to members of the public presents a number of significant challenges. This paper identifies those challenges, details the progress and success of the Motion Hub and sets out the lessons learnt about end-to-end travel. The project was fortunate to have as its municipal partner the Council of a sizeable South East England town, Southend-on-Sea. With a population of 174,800 residents with good road, rail and air links there is considerable traffic in and out of the town. The Council has already shown its commitment to sustainable transport. In the previous six years it had installed a number of electric vehicle charging points for use by the public and latterly had trialled car club activity. An early challenge in the project was the location of physical infrastructure in an already crowded municipal space in order to provide the local ‘spokes’ of the system. In addition to its existing charging points, Southend now has four locations where electric cars can be hired, five where electric bikes are available and the local resources to maintain these assets. Combining a number of web-based services and amalgamating their financial transactions is relatively straightforward. However, introducing the potential for public transport ticketing as well raises additional security, scale and financial constraints. The project has engaged with major players and regulators across the public transport industry.Peer reviewe

Optimal electric bus fleet scheduling considering battery degradation and non-linear charging profile

This study aims to determine the battery electric bus service and charging strategy to minimize the total operational cost of transit system, where the cost incurred by battery degradation and non-linear charging profile is taken into account. We formulate a set partitioning model for this problem, subject to predefined trip schedule and limited charging facilities. A tailored branch-and-price approach is then proposed to find the global optimal solution. In particular, we develop an effective multi-label correcting method to deal with the pricing problem (i.e., generating columns) in column generation procedure within the branch-and-price framework, coupled with a dual stabilization technique with an aim to accelerate the convergence rate. Meanwhile, a branch-and-bound solution approach is adopted to guarantee optimal integer solutions. Numerical experiments and a case study arising from real transit network are conducted to further assess the efficiency and applicability of the proposed method. Our experiments confirm that, despite the complexity of the considered problem, optimal solution can still be generated within reasonable computational time using the proposed algorithm. The results also show considerable cost saving (about 10.1–27.3% less) if this optimization model is implemented, mainly contributed by the substantial extension of battery life. A number of managerial insights stemmed from the numerical case study are outlined, which can help transit operators formulate more cost-efficient electric bus fleet scheduling plans

Towards a Multimodal Charging Network: Joint Planning of Charging Stations and Battery Swapping Stations for Electrified Ride-Hailing Fleets

This paper considers a multimodal charging network in which charging stations and battery swapping stations are built in tandem to support the electrified ride-hailing fleet in a synergistic manner. Our central thesis is predicated on the observation that charging stations are cost-effective, making them ideal for scaling up electric vehicles in ride-hailing fleets in the beginning, while battery swapping stations offer quick turnaround and can be deployed in tandem with charging stations to improve fleet utilization and reduce operational costs for the ride-hailing platform. To fulfill this vision, we consider a ride-hailing platform that expands the multimodal charging network with a multi-stage investment budget and operates a ride-hailing fleet to maximize its profit. A multi-stage network expansion model is proposed to characterize the coupled planning and operational decisions, which captures demand elasticity, passenger waiting time, charging and swapping waiting times, as well as their dependence on fleet status and charging infrastructure. The overall problem is formulated as a nonconvex program. Instead of pursuing the globally optimal solution, we establish a theoretical upper bound through relaxation, reformulation, and decomposition so that the global optimality of the derived solution to the nonconvex problem is verifiable. In the case study for Manhattan, we find that the two facilities complement each other and play different roles during the expansion of charging infrastructure: at the early stage, the platform always prioritizes building charging stations to electrify the fleet, after which it initiates the deployment of swapping stations to enhance fleet utilization. Compared to the charging-only case, ..