Centralized Scheduling Approach to Manage Smart Charging of Electric Vehicles in Smart Cities

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Distributed cooperative control for economic operation of multiple plug‐in electric vehicle parking decks

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138231/1/etep2348.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/138231/2/etep2348_am.pd

An Optimal Charging Strategy for PV-Based Battery Swapping Stations in a DC Distribution System

Photovoltaic-(PV-) based battery swapping stations (BSSs) utilize a typical integration of consumable renewable resources to supply power for electric vehicles (EVs). The charging strategy of PV-based BSSs directly influences the availability, cost, and carbon emissions of the swapping service. This paper proposes an optimal charging strategy to improve the self-consumption of PV-generated power and service availability while considering forecast errors. First, we introduce the typical structure and operation model of PV-based BSSs. Second, three indexes are presented to evaluate operational performance. Then, a particle swarm optimization (PSO) algorithm is developed to calculate the optimal charging power and to minimize the charging cost for each time slot. The proposed charging strategy helps decrease the impact of forecast uncertainties on the availability of the battery swapping service. Finally, a day-ahead operation schedule, a real-time decision-making strategy, and the proposed PSO charging strategy for PV-based BSSs are simulated in a case study. The simulation results show that the proposed strategy can effectively improve the self-consumption of PV-generated power and reduce charging cost

Planning of Regional Urban Bus Charging Facility:A Case Study of Fengxian, Shanghai

The electrification of public transport is of great significance to alleviating environmental pollution and energy problems. The construction of charging stations for electric buses (EBs) is the key step for the electrification of public transport and receives more and more attention. This paper proposes a new urban electric bus charging station planning algorithm which consists of two parts, park-maintaining (PM) charging station planning and midway supply (MS) charging station planning. Firstly, bus routes are classified based on charging demands. Accordingly, the PM charging station planning model is divided into full slow charging (FSC) model, Bus Rapid Transit (BRT) model and Hybrid model. Secondly, the improved grid AP algorithm is applied to plan MS charging stations to enhance the EB operation reliability. Then by multi-terminal charging pile optimization model, the economics of charging facilities construction is enhanced. Finally, via an ordered control charging algorithm, the economic profits of overall planning schemes are enhanced. The bus system in Fengxian, Shanghai is taken as an example to demonstrate the proposed method. Results prove that the proposed method can effectively meet the charging demands of EBs and improve the operating reliability of the EB system. </p

Online Station Assignment for Electric Vehicle Battery Swapping

This paper investigates the online station assignment for (commercial) electric vehicles (EVs) that request battery swapping from a central operator, i.e., in the absence of future information a battery swapping service station has to be assigned instantly to each EV upon its request. Based on EVs' locations, the availability of fully-charged batteries at service stations in the system, as well as traffic conditions, the assignment aims to minimize cost to EVs and congestion at service stations. Inspired by a polynomial-time offline solution via a bipartite matching approach, we develop an efficient and implementable online station assignment algorithm that provably achieves the tight (optimal) competitive ratio under mild conditions. Monte Carlo experiments on a real transportation network by Baidu Maps show that our algorithm performs reasonably well on realistic inputs, even with a certain amount of estimation error in parameters

Online Station Assignment for Electric Vehicle Battery Swapping

This paper investigates the online station assignment for (commercial) electric vehicles (EVs) that request battery swapping from a central operator, i.e., in the absence of future information a battery swapping service station has to be assigned instantly to each EV upon its request. Based on EVs' locations, the availability of fully-charged batteries at service stations in the system, as well as traffic conditions, the assignment aims to minimize cost to EVs and congestion at service stations. Inspired by a polynomial-time offline solution via a bipartite matching approach, we develop an efficient and implementable online station assignment algorithm that provably achieves the tight (optimal) competitive ratio under mild conditions. Monte Carlo experiments on a real transportation network by Baidu Maps show that our algorithm performs reasonably well on realistic inputs, even with a certain amount of estimation error in parameters