Economic assessment of phase reconfiguration to mitigate the unbalance due to plug-in electric vehicles charging

Gray, Matthew K.; Morsi, Walid G.

doi:10.1016/j.epsr.2016.06.008

Cited by 32 publications

(16 citation statements)

References 24 publications

(44 reference statements)

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“…In [53], the economic aspects of a phase reconfiguration to mitigate the EVs' unbalance impacts on an LV distribution system has been assessed. The results obtained in [60] verified that a phase reconfiguration approach could reduce the EVs' unbalance impact through using the time-of-use tariff.…”

Section: Phase Unbalancesupporting

confidence: 53%

Power quality improvement in smart grids using electric vehicles: a review

Ahmadi

Tavakoli

Jamborsalamati³

et al. 2019

IET Electrical Systems in Transportation

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The global warming problem together with the environmental issues has already pushed the governments to replace the conventional fossil-fuel vehicles with electric vehicles (EVs) having less emission. This replacement has led to adding a huge number of EVs with the capability of connecting to the grid. It is noted that the presence of such vehicles may introduce several challenges to the electrical grid due to their grid-to-vehicle and vehicle-to-grid capabilities. In between, the power quality issues would be the main items in electrical grids highly impacted by such vehicles. Thus, this study is devoted to investigating and reviewing the challenges brought to the electrical networks by EVs. In this regard, the current and future conditions of EVs along with the recent research works made into the issue of EVs have been discussed in this study. Accordingly, the problems due to the connection of EVs to the electrical grid have been discussed, and some solutions have been proposed to deal with these challenges.

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Section: Phase Unbalancesupporting

confidence: 53%

Power quality improvement in smart grids using electric vehicles: a review

Ahmadi

Tavakoli

Jamborsalamati³

et al. 2019

IET Electrical Systems in Transportation

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“…The amount of voltage, current [7], power imbalance [8], and energy loss increase when both EV and DG units are integrated in an uncoordinated method. This network imbalance reduces available hosting capacity which leads to reduced uptake of network asset and increased reinforcement cost [9]- [11].…”

Section: Introductionmentioning

confidence: 99%

Multiobjective Optimization Technique for Mitigating Unbalance and Improving Voltage Considering Higher Penetration of Electric Vehicles and Distributed Generation

Islam

Hossain

et al. 2020

IEEE Systems Journal

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The increasing penetration of distributed generations (DGs) and electric vehicles (EVs) offers not only several opportunities but also introduces many challenges for the distribution system operators (DSOs) regarding power quality. This article investigates the network performances due to uncoordinated DG and EV distribution. It also considers power quality-related performances such as the neutral current, energy loss, voltage imbalance, and bus voltage as a multiobjective optimization problem. The differential evolution optimization algorithm is employed to solve the multiobjective optimization problem to coordinate EV and DG in a distribution grid. This article proposed a method to coordinate EV and DG distribution. The proposed method allows DSOs to jointly optimize the phase sequence and optimal dispatch of DGs to improve the network's performance. If the network requires further improvement, the EV charging or discharging rate is coordinated for a particular location. The efficacy of the proposed method is tested in an Australian low-voltage distribution grid considering the amount of imbalance due to higher penetration of DG and EV. It is observed that the proposed method reduces voltage unbalance factor by up to 98.24%, neutral current up to 94%, and energy loss by 59.45%, and improve bus voltage by 10.42%. Index Terms-Compensating neutral current, coordinated/ uncoordinated charging, distributed generation (DG) dispatch, electric vehicle (EV), mitigating voltage unbalance.

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“…A low voltage four‐wire multi grounded network is chosen as the case study network. In Reference 16, the unbalanced network resulted from electric cars is examined. In this reference, the Monte Carlo method is used to manage the probability of electric cars.…”

Section: Introductionmentioning

confidence: 99%

Reconfiguration of distribution network using discrete particle swarm optimization to reduce voltage fluctuations

Behbahani

Jalilian

Amini

2020

Int Trans Electr Energ Syst

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Summary Reconfiguration of the distribution network (DN) is the changing of status of normally open and close switches for a specific purpose. In this paper, a situation is studied in which a fluctuating load (such as a welder) violates the network power quality (PQ) standards. Therefore, in order to mitigate the emission of the generated flicker, an optimization problem is developed for improving the PQ of the network comprising voltage flicker level and voltage profile in addition to the network power loss as a traditional objective of the DN reconfiguration. The optimization procedure is performed by changing the network configuration using tie and sectionalizing switches. Discrete particle swarm optimization is utilized to optimize the network configuration. The proposed method is evaluated in two DNs. IEEE standard 69‐bus DN and 95‐bus practical Iranian DN are considered as case study networks. The results show the effectiveness of the proposed method for improving the network PQ, especially in case of voltage flicker. The presented studies and procedure will guide the utility engineers in making decisions associated with the choice of reasonable mitigation technique to overcome the identified PQ problems.

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Economic assessment of phase reconfiguration to mitigate the unbalance due to plug-in electric vehicles charging

Cited by 32 publications

References 24 publications

Power quality improvement in smart grids using electric vehicles: a review

Power quality improvement in smart grids using electric vehicles: a review

Multiobjective Optimization Technique for Mitigating Unbalance and Improving Voltage Considering Higher Penetration of Electric Vehicles and Distributed Generation

Reconfiguration of distribution network using discrete particle swarm optimization to reduce voltage fluctuations

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