Optimal decentralized protocol for electric vehicle charging

Gan, Lingwen; Topcu, Ufuk; Low, Steven H.

doi:10.1109/cdc.2011.6161220

Cited by 282 publications

(372 citation statements)

References 10 publications

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“…The bottom level is EV aggregator which communicates with each EV owner and schedules the charging and discharging. It also uploads the individual information on all EVs, namely departure time, arrival time and driving distance [20,25,26]. In this section, a coordinated two-stage energy exchange strategy is proposed.…”

Section: Problem Formulationmentioning

confidence: 99%

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Integrated Energy Exchange Scheduling for Multimicrogrid System With Electric Vehicles

Wang

Guan

et al. 2016

IEEE Trans. Smart Grid

153

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Abstract-Electric vehicles (EVs) can be considered as flexible mobile battery storages in microgrids. For multiple microgrids in an area, coordinated scheduling on charging and discharging are required to avoid power exchange spikes between the multimicrogrid system and the main grid. In this paper, a two-stage integrated energy exchange scheduling strategy for multimicrogrid system is presented, which considers EVs as storage devices. Then several dual variables, which are representative of the marginal cost of proper constraints, are utilized to form an updated price, thereby being a modification on the original electricity price. With this updated price signal, a price-based decentralized scheduling strategy is presented for the Microgrid Central Controller (MGCC). Simulation results show that the two-stage scheduling strategy reduces the electricity cost and avoids frequent transitions between battery charging/discharging states. With the proposed decentralized scheduling strategy, each microgrid only needs to solve its local problem and limits the total power exchange within the safe range.Index Terms--Microgrid, electric vehicle, energy exchange, dual variable, updated price signal, decentralized scheduling strategy. I. NOMENCLATURE Index:i Index for microgrid,, ( ) i s B t Lower bound of the aggregate batteries' remaining energy in microgrid i during t in scenario s (kWh).Upper bound of the aggregate batteries' remaining energy in microgrid i during t in scenario s (kWh). ( ) C tOriginal electricity price during t (CNY/kWh).

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Section: Problem Formulationmentioning

confidence: 99%

“…The depth of discharge (DOD) must be less than (1 soc − ) to avoid over-discharge, as shown in (24). Equation (25) means that the sum of charging/discharging power of all EVs should be equal to the optimal aggregate value that is achieved from the MGCC scheduling problem. The daily number of cycles is limited by (26).…”

Section: Ev Aggregator Scheduling Problemmentioning

confidence: 99%

Integrated Energy Exchange Scheduling for Multimicrogrid System With Electric Vehicles

Wang

Guan

et al. 2016

IEEE Trans. Smart Grid

153

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“…A feasible charging profile is a charging profile which satisfies both plug-in constraints and the state of charge condition, i.e. SOC i ðMÞ ¼ SOC i max [46]. The following are also defined: 1) Aggregate non-EV base load at time k is given by:…”

Section: Ev Charging Problem Formulationmentioning

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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“…A centralized control strategy will require a central repository that collects parameter information from all vehicles to provide an optimal charging profile. It has also been suggested that this might be taxing on communication channels and computation time [11]. However, we believe that a centralized solution is the preferred approach under current technological capabilities.…”

Section: Introductionmentioning

confidence: 98%

Economic Scheduling of Residential Plug-In (Hybrid) Electric Vehicle (PHEV) Charging

Maigha

Crow

2014

Energies

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Abstract:In the past decade, plug-in (hybrid) electric vehicles (PHEVs) have been widely proposed as a viable alternative to internal combustion vehicles to reduce fossil fuel emissions and dependence on petroleum. Off-peak vehicle charging is frequently proposed to reduce the stress on the electric power grid by shaping the load curve. Time of use (TOU) rates have been recommended to incentivize PHEV owners to shift their charging patterns. Many utilities are not currently equipped to provide real-time use rates to their customers, but can provide two or three staggered rate levels. To date, an analysis of the optimal number of levels and rate-duration of TOU rates for a given consumer demographic versus utility generation mix has not been performed. In this paper, we propose to use the U.S. National Household Travel Survey (NHTS) database as a basis to analyze typical PHEV energy requirements. We use Monte Carlo methods to model the uncertainty inherent in battery state-of-charge and trip duration. We conclude the paper with an analysis of a different TOU rate schedule proposed by a mix of U.S. utilities. We introduce a centralized scheduling strategy for PHEV charging using a genetic algorithm to accommodate the size and complexity of the optimization.

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Optimal decentralized protocol for electric vehicle charging

Cited by 282 publications

References 10 publications

Integrated Energy Exchange Scheduling for Multimicrogrid System With Electric Vehicles

Integrated Energy Exchange Scheduling for Multimicrogrid System With Electric Vehicles

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

Economic Scheduling of Residential Plug-In (Hybrid) Electric Vehicle (PHEV) Charging

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