A Smart Parking Lot Management System for Scheduling the Recharging of Electric Vehicles

Kuran, Mehmet; Viana, Aline Carneiro; Iannone, Luigi; Kofman, Daniel; Mermoud, Grégory; Vasseur, Jean P.

doi:10.1109/tsg.2015.2403287

Cited by 185 publications

(100 citation statements)

References 28 publications

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“…The aggregator's profit in [7,13] is maximized by MILP and fuzzy linear programming (FLP), respectively. Two LP models were formulated in [14] to optimize EV charging in a parking station with different points of view, i.e., to maximize either the operator's revenue or the number of completely charged EVs. Two contradictory objectives-minimizing the charging cost of an EV parking station and maximizing EV users' satisfaction-were simultaneously achieved in [15] via LP and a modified convex relaxation scheme.…”

Section: Review Of Existing Literaturementioning

confidence: 99%

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Optimal Charging and Discharging Scheduling for Electric Vehicles in a Parking Station with Photovoltaic System and Energy Storage System

2017

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Abstract:The economic and environmental benefits brought by electric vehicles (EVs) cannot be fully delivered unless these vehicles are fully or partially charged by renewable energy sources (RES) such as photovoltaic system (PVS). Nevertheless, the EV charging management problem of a parking station integrated with RES is challenging due to the uncertain nature of local RES generation. This paper aims to address these difficulties by deploying an energy storage system (ESS) in parking stations and exploiting the charging and discharging scheduling of EVs to achieve better utilization of intermittent PVS for EV charging. A real-time charging optimization scheme is also formulated, using mixed-integer linear programming (MILP) to coordinate the charging or discharging power of EVs along with the power dispatches of power grid and ESS based on the vehicles' charging or discharging priorities and electricity price preferences. Extensive simulations show that the proposed approach not only maximizes the satisfaction of EV owners in terms of fulfilling all charging and discharging requests, but also minimizes the overall operational cost of the parking station by prioritizing the utilization of energy from PVS, ESS, and scheduling of every EV's charging and discharging.

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Section: Review Of Existing Literaturementioning

confidence: 99%

“…The works in [7,11,12,[14][15][16][17][18][19][20][21][22] rely on the electricity generated from conventional units for EV charging. The proposed work considers PVS as a power source for EV charging, hence is designed to fully deliver the economic and environmental advantages of EVs.…”

mentioning

confidence: 99%

Optimal Charging and Discharging Scheduling for Electric Vehicles in a Parking Station with Photovoltaic System and Energy Storage System

2017

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“…In addition, while we propose the communication of intentions as a way to coordinate EVs, others have discussed different types of coordination mechanisms. Many of these focus on scheduling of electricity charging at home or while parked away from home to reduce peak loads and/or satisfying constraints of the electricity network (e.g., [14]- [16]). However, this is different from our work, which coordinates vehicles for enroute charging.…”

Section: Related Workmentioning

confidence: 99%

Intention-Aware Routing of Electric Vehicles

Weerdt

Stein

Gerding

et al. 2016

IEEE Trans. Intell. Transport. Syst.

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Abstract-This paper introduces a novel intention-aware routing system (IARS) for electric vehicles. This system enables vehicles to compute a routing policy that minimizes their expected journey time while considering the policies, or intentions, of other vehicles. Considering such intentions is critical for electric vehicles, which may need to recharge en route and face potentially significant queueing times if other vehicles choose the same charging stations. To address this, the computed routing policy takes into consideration predicted queueing times at the stations, which are derived from the current intentions of other electric vehicles. The efficacy of IARS is demonstrated through simulations using realistic settings based on real data from The Netherlands, including charging station locations, road networks, historical travel times, and journey origin-destination pairs. In these settings, IARS is compared with a number of state-of-the-art benchmark routing algorithms and achieves significantly lower average journey times. In some cases, IARS leads to an over 80% improvement in waiting times at charging stations and a more than 50% reduction in overall journey times.

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“…Direct methods are suitable for public places such as parking lots and do not motivate for house charging. Based on realistic vehicular mobility/parking patterns, a centralized EVs recharge scheduling system for parking lots is proposed in [151]. In order to show the performance of the method, the authors compared the proposed method with two different scheduling mechanisms, first-come-first-served and earliest deadline first, using two objective functions, maximizing the total parking lot revenue and maximizing the total number of EVs.…”

Section: Grid To Vehicle (G2v)mentioning

confidence: 99%

Electrical Market Management Considering Power System Constraints in Smart Distribution Grids

Divshali

Choi

2016

Energies

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Rising demand, climate change, growing fuel costs, outdated power system infrastructures, and new power generation technologies have made renewable distribution generators very attractive in recent years. Because of the increasing penetration level of renewable energy sources in addition to the growth of new electrical demand sectors, such as electrical vehicles, the power system may face serious problems and challenges in the near future. A revolutionary new power grid system, called smart grid, has been developed as a solution to these problems. The smart grid, equipped with modern communication and computation infrastructures, can coordinate different parts of the power system to enhance energy efficiency, reliability, and quality, while decreasing the energy cost. Since conventional distribution networks lack smart infrastructures, much research has been recently done in the distribution part of the smart grid, called smart distribution grid (SDG). This paper surveys contemporary literature in SDG from the perspective of the electricity market in addition to power system considerations. For this purpose, this paper reviews current demand side management methods, supply side management methods, and electrical vehicle charging and discharging techniques in SDG and also discusses their drawbacks. We also present future research directions to tackle new and existing challenges in the SDG.

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A Smart Parking Lot Management System for Scheduling the Recharging of Electric Vehicles

Cited by 185 publications

References 28 publications

Optimal Charging and Discharging Scheduling for Electric Vehicles in a Parking Station with Photovoltaic System and Energy Storage System

Optimal Charging and Discharging Scheduling for Electric Vehicles in a Parking Station with Photovoltaic System and Energy Storage System

Intention-Aware Routing of Electric Vehicles

Electrical Market Management Considering Power System Constraints in Smart Distribution Grids

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