High adoption of electric vehicles (EVs) can overload distribution transformers when charging requests with heterogeneous departure deadlines compete for limited capacity. Most existing coordination schemes enforce hard deadlines and strict transformer limits, implicitly assuming feasibility and failing under severe congestion. We propose a deadline-aware EV charging framework that explicitly trades off transformer thermal aging and charging service quality under capacity-constrained operation. We model transformer stress using a convex aging proxy and soften charging deadlines via penalty-weighted unmet energy at departure. We further develop a low-complexity online charging policy that prioritizes EVs based on a marginal-cost-aware urgency index. We demonstrate through case studies under increasing EV penetration that the proposed approach reduces transformer aging while preferentially allocating limited capacity to time-critical EVs, closely approximating offline benchmark performance using only real-time information.
Supported by the technical development of electric battery and charging facilities, plug-in electric vehicle (PEV) has the potential to be mobile energy storage (MES) for energy delivery from resourceful charging stations (RCSs) to limited-capacity charging stations (LCSs). In this paper, we study the problem of using on-road PEVs as MESs for energy compensation service to compensate charging station (CS) overload. A price-incentive scheme is proposed for power system operator (PSO) to stimulate on-road MESs fulfilling energy compensation tasks. The price-service interaction between the PSO an…
Wide-scale electrification of the transportation sector will require careful planning and coordination with the power grid. Left unmanaged, uncoordinated charging of electric vehicles (EVs) at increased levels of penetration will amplify existing peak loads, potentially outstripping the grid's capacity to reliably meet demand. In this paper, we report findings from the OptimizEV Project - a real-world pilot study in Upstate New York exploring a novel approach to coordinated residential EV charging. The proposed coordination mechanism seeks to harness the latent flexibility in EV charging by of…
We describe the architecture and algorithms of the Adaptive Charging Network (ACN), which was first deployed on the Caltech campus in early 2016 and is currently operating at over 100 other sites in the United States. The architecture enables real-time monitoring and control and supports electric vehicle (EV) charging at scale. The ACN adopts a flexible Adaptive Scheduling Algorithm based on convex optimization and model predictive control and allows for significant over-subscription of electrical infrastructure. We describe some of the practical challenges in real-world charging systems, incl…
Electric vehicle charging facilities offer electric charge and parking to users for a fee. Both parking availability and electric charge capacity are constrained resources, and as the demand for charging facilities grows with increasing electric vehicle adoption, so too does the potential for exceeding these resource limitations. In this paper, we study how prices set by the charging facility impact the likelihood that resource constraints are exceeded. Specifically, we present probabilistic bounds on the number of charging spots and the total power supply needed at a facility based on the cha…
Smoothed Least-Laxity-First Algorithm for EV Charging
Singapore University of Technology and Design（新加坡科技设计大学）；Institute for High Performance Computing, Agency for Science, Technology, and Research（新加坡科技研究局高性能计算研究所）；Carnegie Mellon University（卡内基梅隆大学）；University of Colorado Boulder（科罗拉多大学博尔德分校）；California Institute of Technology（加州理工学院）
The rapid escalation in plug-in electric vehicles (PEVs) and their uncoordinated charging patterns pose several challenges in distribution system operation. Some of the undesirable effects include overloading of transformers, rapid voltage fluctuations, and over/under voltages. While this compromises the consumer power quality, it also puts on extra stress on the local voltage control devices. These challenges demand for a well-coordinated and power network-aware charging approach for PEVs in a community. This paper formulates a real-time electric vehicle charging scheduling problem as an mixe…
Emission-Aware Reinforcement Learning for Sustainable Electric Vehicle Charging and Carbon Dioxide Reduction Under Varying Renewable Penetration
organization= nasc Research, School of Computer Science \& IT, University College Cork , country = IE；organization= School of Computing, Engineering；Digital Technologies, Teesside University , country= UK；organization= International Energy Research Centre, Tyndall National Institute, Cork , country = IE；Radiation Technologies Group, CCDCU, Faculty of Engineering；Technology, Sunway University , country = Malaysia；organization= Department of Physics, College of Science, Korea University , country = Republic of Korea
Marain Inc.（Marain公司）；Stanford University（斯坦福大学）；eIQ Mobility（eIQ Mobility公司）；SLAC National Accelerator Laboratory（SLAC国家加速器实验室）
In future transportation systems, the charging behavior of electric Autonomous Mobility on Demand (AMoD) fleets, i.e., fleets of electric self-driving cars that service on-demand trip requests, will likely challenge power distribution networks (PDNs), causing overloads or voltage drops. In this paper, we show that these challenges can be significantly attenuated if the PDNs' operational constraints and exogenous loads (e.g., from homes or businesses) are accounted for when operating an electric AMoD fleet. We focus on a system-level perspective, assuming full coordination between the AMoD and …
The connected vehicle paradigm empowers vehicles with the capability to communicate with neighboring vehicles and infrastructure, shifting the role of vehicles from a transportation tool to an intelligent service platform. Meanwhile, the transportation electrification pushes forward the electric vehicle (EV) commercialization to reduce the greenhouse gas emission by petroleum combustion. The unstoppable trends of connected vehicle and EVs transform the traditional vehicular system to an electric vehicular network (EVN), a clean, mobile, and safe system. However, due to the mobility and heterog…
