An Optimized EV Charging Model Considering TOU Price and SOC Curve

Cao, Yijia; Tang, Shengwei; Li, Canbing; Zhang, Peng; Tan, Yi; Zhang, Zhikun; Li, Junxiong

doi:10.1109/tsg.2011.2159630

Cited by 580 publications

(228 citation statements)

References 15 publications

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“…The daily charging cost is reduced from $0.46 to $0.20. Cao et al (2012) proposed an intelligent method to control EV charging load in response to time-of-use (TOU) price in a regulated market [9]. Their simulation results showed that the optimized charging pattern has great benefit in reducing cost and flatting the load curve if the peak and valley time periods are partitioned appropriately.…”

Section: Introductionmentioning

confidence: 99%

Charge Management Optimization for Future TOU Rates

Zhang

Markel

2016

WEVJ

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SummaryThe effectiveness of future time of use (TOU) rates to enable managed charging depends on the vehicle's flexibility and the benefits to owners. This paper adopts opportunity, delayed, and smart charging methods to quantify these impacts, flexibilities, and benefits. Simulation results show that delayed and smart charging methods can shift most charging events to lower TOU rate periods without compromising the charged energy and individual driver mobility needs.

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Section: Introductionmentioning

confidence: 99%

Charge Management Optimization for Future TOU Rates

Zhang

Markel

2016

WEVJ

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“…While centralised coordination gives the best performance possible [18], centralised algorithms require access to global system information, which might not always be accessible, and centralised algorithms typically do not scale well [18][19][20]. For these reasons, several decentralised strategies have been proposed recently for EV charging [21][22][23][24][25][26]. In decentralised charging strategies individual EVs are given a certain level of decision making autonomy.…”

Section: Introductionmentioning

confidence: 99%

Residential electrical vehicle charging strategies: the good, the bad and the ugly

Liu

McNamara

Shorten

et al. 2015

J. Mod. Power Syst. Clean Energy

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In recent years, a wide variety of centralised and decentralised algorithms have been proposed for residential charging of electric vehicles (EVs). In this paper, we present a mathematical framework which casts the EV charging scenarios addressed by these algorithms as optimisation problems having either temporal or instantaneous optimisation objectives with respect to the different actors in the power system. Using this framework and a realistic distribution network simulation testbed, we provide a comparative evaluation of a range of different residential EV charging strategies, highlighting in each case positive and negative characteristics.

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“…Although EV advocates have spent decades on tackling all kinds of challenges, EV charging control strategies which can affect the impacts and benefits significantly are still under discussion [24,25]. Yilmaz et al [26] reviewed the current status and implementation of battery chargers, charging power levels, and infrastructure for plug-in EVs.…”

Section: Introductionmentioning

confidence: 99%

The Concept of EV’s Intelligent Integrated Station and Its Energy Flow

et al. 2015

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Abstract:The increasing number of electric vehicles (EVs) connected to existing distribution networks as time-variant loads cause significant distortions in line current and voltage. A novel EV's intelligent integrated station (IIS) making full use of retired batteries is introduced in this paper to offer a potential solution for accommodating the charging demand of EVs. It proposes the concept of generalized energy in IIS, based on the energy/power flow between IIS and EVs, and between IIS and the power grid, to systematically evaluate the energy capacity of IIS. In order to derive a unique and satisfactory operation mode, information from both the grid (in terms of load level) and IIS (in terms of its energy capacity and EVs battery charging/exchanging requests) is merged. Then, based on the generalized energy of different systems, a novel charging/discharging control strategy is presented and whereby the operating status of the grid and energy capacity of IIS are monitored to make reasonable operation plans for IIS. Simulation results suggest that the proposed IIS offers peak load shifting when EV battery charging/exchanging requests are satisfied compared to existing charging stations. OPEN ACCESSEnergies 2015, 8 4189

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An Optimized EV Charging Model Considering TOU Price and SOC Curve

Cited by 580 publications

References 15 publications

Charge Management Optimization for Future TOU Rates

Charge Management Optimization for Future TOU Rates

Residential electrical vehicle charging strategies: the good, the bad and the ugly

The Concept of EV’s Intelligent Integrated Station and Its Energy Flow

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