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, including unbalanced three-phase infrastructure, non-ideal battery charging behavior, and quantized control signals. We demonstrate how the Adaptive Scheduling Algorithm handles these challenges, and compare its performance against baseline algorithms from the deadline scheduling literature using real workloads recorded from the Caltech ACN and accurate system models. We find that in these realistic settings, our scheduling algorithm can improve operator profit by 3.4 times over uncontrolled charging and consistently outperforms baseline algorithms when delivering energy in highly congested systems.
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…
We study a real-time smart charging algorithm for electric vehicles (EVs) at a workplace parking lot in order to minimize electricity cost from time-of-use electricity rates and demand charges while ensuring that the owners of the EVs receive adequate levels of charge. Notably, due to real-world constraints, our algorithm is agnostic to both the state-of-charge and the departure time of the EVs and uses scenario generation to account for each EV's unknown future departure time as well as certainty equivalent control to account for the unknown EV arrivals in the future. Real-world charging data…
With the advances in the Internet of Things technology, electric vehicles (EVs) have become easier to schedule in daily life, which is reshaping the electric load curve. It is important to design efficient charging algorithms to mitigate the negative impact of EV charging on the power grid. This paper investigates an EV charging scheduling problem to reduce the charging cost while shaving the peak charging load, under unknown future information about EVs, such as arrival time, departure time, and charging demand. First, we formulate an EV charging problem to minimize the electricity bill of th…
We present a customizable online optimization framework for real-time EV smart charging to be readily implemented at real large-scale charging facilities. Notably, due to real-world constraints, we designed our framework around 3 main requirements. First, the smart charging strategy is readily deployable and customizable for a wide-array of facilities, infrastructure, objectives, and constraints. Second, the online optimization framework can be easily modified to operate with or without user input for energy request amounts and/or departure time estimates which allows our framework to be imple…
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…
Electric vehicles are booming and with them the required public charging stations. Knowing how charging stations are used is crucial for operators of the charging stations themselves, navigation systems, electricity grids, and many more. Given that there are now 2.5 as many vehicles per charging station compared to 2017, the system needs to allocate charging points intelligently and efficiently. This paper presents representative data on energy consumption, arrival times, occupation, and profitability of charging stations in Germany by combining usage data of 27,800 installations. Charging hap…
High-powered electric vehicle (EV) charging can significantly increase charging costs due to peak-demand charges. This paper proposes a novel charging algorithm which exploits typically long plugin sessions for domestic chargers and reduces the overall charging power by boost charging the EV for a short duration, followed by low-power charging for the rest of the plugin session. The optimal parameters for boost and low-power charging phases are obtained using reinforcement learning by training on EV's past charging sessions. Compared to some prior work, the proposed algorithm does not attempt …
Modelling of the Electric Vehicle Charging Infrastructure as Cyber Physical Power Systems: A Review on Components, Standards, Vulnerabilities and Attacks
The growing deployment of electric mobility calls for power system analyses to investigate to what extent the simultaneous charging of electric vehicles leads to degraded network operation and to validate the efficiency of countermeasures. To reduce complexity and CPU time, a common approach while performing these analyses consists in replacing electric vehicles and their charging stations with constant PQ loads. However, this approach is inaccurate, as the power absorbed by these elements actually depends not only on voltage but also on the state of charge, charging method, cathode chemistry …
Planning to support widespread transportation electrification depends on detailed estimates for the electricity demand from electric vehicles in both uncontrolled and controlled or smart charging scenarios. We present a modeling approach to rapidly generate charging estimates that include control for large-scale scenarios with millions of individual drivers. We model uncontrolled charging demand using statistical representations of real charging sessions. We model the effect of load modulation control on aggregate charging profiles with a novel machine learning approach that replaces tradition…
Wireless charging technology provides a solution to the insufficient battery life of electric vehicles (EVs). However, the conflict of interests between wireless charging lanes (WCLs) and EVs is difficult to resolve. In the day-ahead electricity market, considering the revenue of WCLs caused by the deviation between actual electricity sales and pre-purchased electricity, as well as endurance and traveling experience of EVs, this paper proposes a charging scheduling algorithm based on a double-layer game model. In lower layer, the potential game is used to model the multi-vehicle game of vehicl…
In this paper, particle-hopping cellular automaton (CA) models of elastic demand are used to investigate the value added to plug-in electric vehicles (PEV) aggregators by adopting vehicle-to-grid (V2G) responsive services. CA models used earlier to study load-sifting responses are modified to capture discharge/ recharge capabilities of V2G. Results on ramping responses from CA are then analysed to discuss the small contribution to system controllability added by V2G responsive services.
Electric vehicles (EVs) have enjoyed increasing adoption because of the global concerns about the petroleum dependence and greenhouse gas emissions. However, their limited driving range fosters the occurrence of charging requests deriving from EV drivers in urban road networks, which have significant uncertain characteristic from time dimension in the real-world situation. To tackle the challenge brought by the dynamic charging requests, this study is devoted to proposing optimal strategies to provide guidance for EV charging. The time-varying characteristic of road network is further involved…
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…
This paper studies optimal thermal management and charging of a battery electric vehicle driving over long distance trips. The focus is on the potential benefits of including a heat pump in the thermal management system for waste heat recovery, and charging point planning, in a way to achieve optimality in time, energy, or their trade-off. An optimal control problem is formulated, in which the objective function includes the energy delivered by the charger(s), and the total charging time including the actual charging time and the detour time to and from the charging stop. To reduce the computa…
As an important supporting facility for electric vehicles, the reasonable planning and layout of charging stations are of great significance to the development of electric vehicles. However, the planning and layout of charging stations is affected by various complex factors such as policy economy, charging demand, user charging comfort, and road traffic conditions. How to weigh various factors to construct a reasonable model of charging station location and capacity has become a major difficulty in the field of electric vehicle charging facility planning. Firstly, this paper constructs the loc…
This paper presents a consolidated grid impact analysis design and corresponding mitigation strategies for heavy-duty electric vehicle (EV) charging stations. The charging load of heavy-duty charging station can reach several megawatts, which could induce adverse impacts on the distribution grid if not effectively mitigated. To analyze the impacts and provide corresponding solutions, we select four representative distribution systems - including both single-feeder cases and a multi-feeder case - and design thorough test metrics for the impact analysis. The charging load profiles used in the an…
The optimal operation problem of electric vehicle aggregator (EVA) is considered. An EVA can participate in energy and regulation markets with its current and upcoming EVs, thus reducing its total cost of purchasing energy to fulfill EVs' charging requirements. An MPC based optimization model is developed to consider future arrival of EVs as well as energy and regulation prices. The index of CVaR is used to model risk-averseness of an EVA. Simulations on the 1000-EV test system validate the effectiveness of our work in achieving a lucrative revenue while satisfying the charging requests from E…
In this paper we propose a stochastic decentralized algorithm to recommend the most convenient Charging Station (CS) to Plug-in Electric Vehicles (PEVs) that need charging. In particular, we use different cost functions to describe the possibly different priorities of PEV drivers, such as the preference to minimize charging costs, charging times, or the distance between them and the CS. For this purpose, we leverage on an IoT architecture based on a permissioned Distributed Ledger Technology (DLT) to enforce compliance of drivers and reduces the occurrence of detrimental misbehaviours of drive…
We study the joint route assignment and charge scheduling problem of a transit system dispatcher operating a fleet of electric buses in order to maximize solar energy integration and reduce energy costs. Specifically, we consider a complex bus transit system with preexisting routes, limited charging infrastructure, limited number of electric buses, and time-varying electricity rates. We present a mixed integer linear program (MILP) that yields the minimal cost daily operation strategy for the fleet (i.e., route assignments and charging schedules using daily solar forecasts). We present numeric…
ACN-Sim is a data-driven, open-source simulation environment designed to accelerate research in the field of smart electric vehicle (EV) charging. It fills the need in this community for a widely available, realistic simulation environment in which researchers can evaluate algorithms and test assumptions. ACN-Sim provides a modular, extensible architecture, which models the complexity of real charging systems, including battery charging behavior and unbalanced three-phase infrastructure. It also integrates with a broader ecosystem of research tools. These include ACN-Data, an open dataset of E…
This paper addresses optimal battery thermal management (BTM), charging, and eco-driving of a battery electric vehicle (BEV) with the goal of improving its grid-to-meter energy efficiency. Thus, an optimisation problem is formulated, aiming at finding the optimal trade-off between trip time and charging cost. The formulated problem is then transformed into a hybrid dynamical system, where the dynamics in driving and charging modes are modeled with different functions and with different state and control vectors. Moreover, to improve computational efficiency, we propose modelling the driving dy…
Route Optimization of Electric Vehicles based on Dynamic Wireless Charging
University of Thessaly（色萨利大学）；De Montfort University（德蒙福特大学）；Nottingham Trent University（诺丁汉特伦特大学）；University of Surrey（萨里大学）；T.E.I. of Thessaly（色萨利技术教育学院）
The increasing trend of transportation electrification presents investors the opportunity to provide charging services to Electric Vehicle (EV) owners via the energy purchased from the wholesale electricity market. This will benefit EV owners with the availability of competitive rates compared to the regulated utility time-of-use (TOU) rates. The fundamental questions addressed in this paper are 1) will EV owners benefit from the additional choice of Electric Vehicle Charging Stations (EVCSs) compared to home charging? 2) is there any profitable market opportunity for charging stations while t…
As the number of electric vehicles rapidly increases, their peak demand on the grid becomes one of the major challenges. A battery-assisted charging concept has emerged recently, which allows to accumulate energy during off-peak hours and in-between charging sessions to boost-charge the vehicle at a higher rate than available from the grid. While prior research focused on the design and implementation aspects of battery-assisted charging, its impact at large geographical scales remains largely unexplored. In this paper we analyse to which extent the battery-assisted charging can replace high-s…
Coordinating the charging scheduling of electric vehicles for dynamic dial-a-ride services is challenging considering charging queuing delays and stochastic customer demand. We propose a new two-stage solution approach to handle dynamic vehicle charging scheduling to minimize the costs of daily charging operations of the fleet. The approach comprises two components: daily vehicle charging scheduling and online vehicle-charger assignment. A new battery charge scheduling model is proposed to obtain the vehicle charging schedules by minimizing the costs of vehicle daily charging operations while …
The rapid growth of electric vehicles (EVs) has promised a next-generation transportation system with reduced carbon emission. The fast development of EVs and charging facilities is driving the evolution of Internet of Vehicles (IoV) to Internet of Electric Vehicles (IoEV). IoEV benefits from both smart grid and Internet of Things (IoT) technologies which provide advanced bi-directional charging services and real-time data processing capability, respectively. The major design challenges of the IoEV charging control lie in the randomness of charging events and the mobility of EVs. In this artic…
This paper investigates the impact of the charging level of high penetration level of Electric Vehicles (EVs) on the power quality of the electricity distribution network. The EV owners tend to charge their EVs as fast as possible. The charging levels of EVs within the distribution network affect the voltage profile of buses of the network. In this paper, an exact Second-Order Cone Programming (SOCP) formulation of the full AC optimal power flow (ACOPF) problem of the distribution network is presented. The network includes solar generation units and EVs as Distributed Energy Resources (DERs). …
Electrical Vehicle Charging Station Profit Maximization: Admission, Pricing, and Online Scheduling
The Chinese University of Hong Kong（香港中文大学）；Shenzhen Research Institute, The Chinese University of Hong Kong（香港中文大学深圳研究院）；College of Information Engineering, Shenzhen University（深圳大学信息工程学院）
本文提出JoAP机制，通过联合优化电动汽车接入控制、定价和充电调度，提升充电站利润。通过 tandem 队列网络模型分析，设计最优算法并在模拟中验证其在不同等待时间惩罚率下利润提升达330%-531%。
