In this paper a new aggregated model for electric vehicle (EV) fleets is presented that considers their daily and weekly usage patterns. A frequency-constrained stochastic unit commitment model is employed to optimally schedule EV charging and discharging as well as the provision of frequency response (FR) in an electricity system, while respecting the vehicles' energy requirements and driving schedules. Through case studies we demonstrate that an EV with vehicle to grid (V2G) capability can reduce system costs in a future GB electricity grid by up to £12,000 per year, and reduce CO2 emissions by 60 tonnes per year, mainly due to reduced curtailment of wind power. The paper also quantifies the changes in the benefits of fleet V2G resulting from variations in FR delivery time, the penetration of wind or uptake of alternative flexibility providers. Finally , a battery degradation model dependent on an EV's state of charge is proposed and implemented in the stochastic scheduling problem. It enables significant degradation cost reductions of 16% with only a 0.4% reduction of an EV's system value.
The problem of autonomous parking of vehicle fleets is addressed in this paper. We present a system-level modeling and control framework which allows investigating different vehicle parking strategies while taking into account path planning and collision avoidance. The proposed approach decouples the problem into a centralized parking spot allocation and path generation, and a decentralized collision avoidance control. This paper presents the hierarchical framework and algorithmic details. Extensive simulations are used to assess several allocation strategies in terms of total fleet parking ti…
Road vehicles play an important role in the UK's energy systems and are a critical component in reducing the reliance on fossil fuels and mitigating emissions. A dynamic model of vehicle fleet, based on predator-prey concepts, is presented. It allows to predict the evolution of the hydrogen based vehicle's role in the UK's vehicle fleet and the sensitivity of this growth to the supply chain. In addition to this, this model is used to predict the demand of hydrogen for the passenger vehicle fleet for various scenarios. A key result is that the amount of hydrogen required to support a huge netwo…
We study the feasibility of using electric vehicles in online, high-capacity ridepooling systems. Prior work has shown that online algorithms perform well for centrally-controlled, high-capacity ridepool systems. First, we propose a mixed integer linear program to expand past algorithms on ridepooling to electric vehicles fleets with the objective of scheduling vehicle charging to maintain sufficient fleet sizes at various times of day. Then we show a faster, scalable algorithm with similar performance that is practical for full-scale systems. Our contributions show the importance of having kn…
This paper analyzes the potential benefit of heavy-duty vehicle (HDV) electrification and automation on fleet cost, infrastructure cost, grid, and environmental impact. In this work, we extended the vehicle electrification benefit analysis tool: Grid-Electrified Mobility (GEM) model, which had primarily been used to study light-duty passenger vehicles (LDVs), to analyze the heavy-duty vehicle electrification. The extended model is derived for freight transportation and key results and findings on the impact of freight electrification and automation are presented and discussed.
With recent developments in vehicle and battery technologies, electric vehicles (EVs) are rapidly getting established as a sustainable alternative to traditional fossil-fuel vehicles. This has made the large-scale electrification of ride-sourcing operations a practical viability, providing an opportunity for a leap toward urban sustainability goals. Despite having a similar driving range to fossil-fuel vehicles, EVs are disadvantaged by their long charging times which compromises the total fleet service time. To efficiently manage an EV fleet, the operator needs to address the charge schedulin…
The electrification of transport is seen as an important step in the global decarbonisation agenda. With such a large expected load on the power system from electric vehicles (EVs), it is important to coordinate charging in order to balance the supply and demand for electricity. Bidirectional charging, enabled through Vehicle-to-Grid (V2G) technology, will unlock significant storage capacity from stationary EVs that are plugged in. To take this concept a step further, this paper quantifies the potential revenues to be gained by a commercial EV fleet operator from simultaneously scheduling its …
Deploying real-time control on large-scale fleets of electric vehicles (EVs) is becoming pivotal as the share of EVs over internal combustion engine vehicles increases. In this paper, we present a Vehicle-to-Grid (V2G) algorithm to simultaneously schedule thousands of EVs charging and discharging operations, that can be used to provide ancillary services. To achieve scalability, the monolithic problem is decomposed using the alternating direction method of multipliers (ADMM). Furthermore, we propose a method to handle bilinear constraints of the original problem inside the ADMM iterations, whi…
Both ride-hailing services and electric vehicles are becoming increasingly popular and it is likely that charging management of the ride-hailing vehicles will be a significant part of the ride-hailing company's operation in the near future. Motivated by this, we propose a game theoretic model for charging management, where we assume that it is the fleet-operator that wants to minimize its operational cost, which among others include the price of charging. To avoid overcrowded charging stations, a central authority will design pricing policies to incentivize the vehicles to spread out among the…
The increasing uptake of electrical vehicles (EVs) has increased the awareness of battery degradation costs and how they can be minimized. However, from a planning perspective it is difficult to integrate battery degradation models into existing route planning models and to assess how policies that aim at reducing battery degradation affect route planning costs and degradation across the fleet. In this paper, a simple transportation vehicle routing problem (VRP) is formulated as a mixed-integer nonlinear problem (MINLP), with a modification that allows monitoring the maximum and minimum depth-…
This paper deals with the electric vehicle fleet relocation management in a sharing system. The mobility sharing systems efficiency depends on the vehicles relocation task that strongly affect the company operating cost, and consequently the service price for users. The proposed approach aims at minimizing the cost of vehicles relocation for a sharing company by involving users through an innovative incentive scheme. The idea is to request users of the sharing service to relocate the EVs, e.g. through an IT application, incentivizing them by free-of-charge travels and rewards. The proposed inc…
Automated vehicles (AVs) are expected to be beneficial for Mobility-on-Demand (MoD), thanks to their ability of being globally coordinated. To facilitate the steady transition towards full autonomy, we consider the transition period of AV deployment, whereby an MoD system operates a mixed fleet of automated vehicles (AVs) and human-driven vehicles (HVs). In such systems, AVs are centrally coordinated by the operator, and the HVs might strategically respond to the coordination of AVs. We devise computationally tractable strategies to coordinate mixed fleets in MoD systems. Specifically, we mode…
In this paper, we propose a closed queueing network model for performance analysis of electric vehicle sharing systems with a certain number of chargers in each neighborhood. Depending on the demand distribution, we devise algorithms to compute the optimal fleet size and number of chargers required to maximize profit while maintaining a certain quality of service. We show that the profit is concave with respect to the fleet size and the number of chargers at each charging point. If more chargers are installed within the city, we show that it can not only reduce the fleet size, but it also impr…
In this paper, we study an online charge scheduling strategy for fleets of autonomous-mobility-on-demand electric vechicles (AMoD EVs). We consider the case where vehicles complete trips and then enter a between-ride state throughout the day, with their information becoming available to the fleet operator in an online fashion. In the between-ride state, the vehicles must be scheduled for charging and then routed to their next passenger pick-up locations. Additionally, due to the unknown daily sequences of ride requests, the problem cannot be solved by any offline approach. As such, we study an…
This paper considers an aggregator of Electric Vehicles (EVs) who aims to learn the aggregate power of his/her fleet while also participating in the electricity market. The proposed approach is based on a data-driven inverse optimization (IO) method, which is highly nonlinear. To overcome such a caveat, we use a two-step estimation procedure which requires solving two convex programs. Both programs depend on penalty parameters that can be adjusted by using grid search. In addition, we propose the use of kernel regression to account for the nonlinear relationship between the behaviour of the po…
Distributed energy resources (DERs) such as responsive loads and energy storage systems are valuable resources available to grid operators for balancing supply-demand mismatches via load coordination. However, consumer acceptance of load coordination schemes depends on ensuring quality of service (QoS), which embodies device-level constraints. Since each device has its own internal energy state, the effect of QoS on the fleet can be cast as fleet-wide energy limits within which the aggregate "state of charge" (SoC) must be actively maintained. This requires coordination of DERs that is cogniza…
We consider the platoon matching problem for a set of trucks with the same origin, but different destinations. It is assumed that the vehicles benefit from traveling in a platoon for instance through reduced fuel consumption. The vehicles belong to different fleet owners and their strategic interaction is modeled as a non-cooperative game where the vehicle actions are their departure times. Each truck has a preferred departure time and its utility function is defined as the difference between its benefit from platooning and the cost of deviating from its preferred departure time. We show that …
Due to their large power draws and increasing adoption rates, electric vehicles (EVs) will become a significant challenge for electric distribution grids. However, with proper charging control strategies, the challenge can be mitigated without the need for expensive grid reinforcements. This manuscript presents and analyzes new distributed charging control methods to coordinate EV charging under nonlinear transformer temperature ratings. Specifically, we assess the trade-offs between required data communications, computational efficiency, and optimality guarantees for different control strateg…
Profit-sharing is needed within platoons in order for competing transportation companies to collaborate in forming platoons. In this paper, we propose distribution models of the profit designed for vehicles that are located at the same origin and are operated by competing transportation companies. The vehicles have default departure times, but can decide to depart at other times in order to benefit from platooning. We model the strategic interaction among vehicles with game theory and consider pure Nash equilibria as the solution concept. In a numerical evaluation we compare the outcomes of th…
In recent years, the market for frequency containment reserve (FCR) has become a relevant source of revenue for stationary battery storage systems in Germany. During this period, prices for FCR have decreased, while the market has become increasingly flexible with shorter service periods and lower minimum power requirements. This flexibility makes the market attractive for pools of electric vehicles (EVs). Their idle times are now often longer than FCR service periods, providing the opportunity to earn additional revenue. In this paper, multi-year measurement data from 22 commercial EVs are us…
The surging adoption of electric vehicles (EV) calls for accurate and efficient approaches to coordinate with the power grid operation. By being responsive to distribution grid limits and time-varying electricity prices, EV charging stations can minimize their charging costs while aiding grid operation simultaneously. In this study, we investigate the economic benefit of vehicle-to-grid (V2G) using real-time price data from New York State and a real-world charging network dataset. We incorporate nonlinear battery models and price uncertainty into the V2G management design to provide a realisti…
The advent of vehicle autonomy, connectivity and electric powertrains is expected to enable the deployment of Autonomous Mobility-on-Demand systems. Crucially, the routing and charging activities of these fleets are impacted by the design of the individual vehicles and the surrounding charging infrastructure which, in turn, should be designed to account for the intended fleet operation. This paper presents a modeling and optimization framework where we optimize the activities of the fleet jointly with the placement of the charging infrastructure. We adopt a mesoscopic planning perspective and …
Fixed pickup and delivery times can strongly limit the performance of freight transportation. Against this backdrop, fleet operators can use compensation mechanisms such as monetary incentives to buy delay time from their customers, in order to improve the fleet efficiency and ultimately minimize the costs of operation. To make the most of such an operational model, the fleet activities and the incentives should be jointly optimized accounting for the customers' reactions. Against this backdrop, this paper presents an incentive-aware electric vehicle routing scheme in which the fleet operator …
The era of fully autonomous, electrified taxi fleets is rapidly approaching, and with it the opportunity to innovate myriad on-demand services that extend beyond the realm of human mobility. This project envisions a future where autonomous plug-in electric vehicle (PEV) fleets can be dispatched as both a taxi service and a source of on-demand power serving customers during power outages. We develop a PDE-based scheme to manage the optimal dispatch of an autonomous fleet to serve passengers and electric power demand during outages as an additional stream of revenue. We use real world power outa…
Connected and automated vehicles (CAVs) can plan and actuate control that explicitly considers performance, system safety, and actuation constraints in a manner more efficient than their human-driven counterparts. In particular, eco-driving is enabled through connected exchange of information from signalized corridors that share their upcoming signal phase and timing (SPaT). This is accomplished in the proposed control approach, which follows first principles to plan a free-flow acceleration-optimal trajectory through green traffic light intervals by Pontryagin's Minimum Principle in a feedbac…
In this paper, we study the potential benefits from smart charging for a fleet of electric vehicles (EVs) providing autonomous mobility-on-demand (AMoD) services. We first consider a profit-maximizing platform operator who makes decisions for routing, charging, rebalancing, and pricing for rides based on a network flow model. Clearly, each of these decisions directly influence the fleet's smart charging potential; however, it is not possible to directly characterize the effects of various system parameters on smart charging under a classical network flow model. As such, we propose a modeling v…
The integration of energy systems such as electricity and gas grids and power and thermal grids can bring significant benefits in terms of system security, reliability, and reduced emissions. Another alternative coupling of sectors with large potential benefits is the power and transportation networks. This is primarily due to the increasing use of electric vehicles (EV) and their demand on the power grid. Besides, the production and operating costs of EVs and battery technologies are steadily decreasing, while tax credits for EV purchase and usage are being offered to users in developed count…
San Diego State University（圣地亚哥州立大学）；GEIRI North America（全球能源互联网研究院北美分院）
A total 19% of generation capacity in California is offered by PV units and over some months, more than 10% of this energy is curtailed. In this research, a novel approach to reduce renewable generation curtailments and increasing system flexibility by means of electric vehicles' charging coordination is represented. The presented problem is a sequential decision making process, and is solved by fitted Q-iteration algorithm which unlike other reinforcement learning methods, needs fewer episodes of learning. Three case studies are presented to validate the effectiveness of the proposed approach…
The ubiquitous growth of mobility-on-demand services for passenger and goods delivery has brought various challenges and opportunities within the realm of transportation systems. As a result, intelligent transportation systems are being developed to maximize operational profitability, user convenience, and environmental sustainability. The growth of last mile deliveries alongside ridesharing calls for an efficient and cohesive system that transports both passengers and goods. Existing methods address this using static routing methods considering neither the demands of requests nor the transfer…
Distributed Control Barrier Functions for Safe Multi-Vehicle Navigation in Heterogeneous USV Fleets
Massachusetts Institute of Technology（麻省理工学院）；MIT Lincoln Laboratory（MIT林肯实验室）；Woods Hole Oceanographic Institution（伍兹霍尔海洋研究所）；Charles Stark Draper Laboratory（查尔斯·斯塔克·德拉珀实验室）；Brigham Young University
