Method to improve charging power quality of electric vehicles

Li, Fucun; Guo, Liang; Liu, Lijun; Li, Xiao; Qing, Wang

doi:10.1049/joe.2018.8544

Cited by 6 publications

(4 citation statements)

References 7 publications

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“…The power quality issues due to implementation of vehicle to grid system is implemented in [6]. The problem due to incoordination in charging of electric vehicle problem is handled in [7]- [8]. The charger with good efficiency using the sliding mode control is implemented in [9].…”

Section: Introductionmentioning

confidence: 99%

Validation of photovoltaics powered UPQC using ANFIS controller in a standard microgrid test environment

Sumana

Dhanalakshmi

Dhamodharan³

2022

IJECE

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The power quality improvement becomes one of the important tasks while using microgrid as main power supply. Because the microgrid is combination of renewable energy resources. The renewable energy resources are intermittent in power supply and at the peak loading condition it has to supply the required power. So, the power quality problems may increase in that time. Out of all power quality issues the voltage drop and harmonic distortion is considered as the most serious one. In recent years unified power quality conditioner (UPQC) is emerged as most promising device which compensates both utility as well as customer side power quality disturbances in effective way. The compensating potentiality used in the UPQC is limited by the use of DC link voltage regulation and the conventional proportional integral (PI) controller. In this paper the compensating potentiality of the UPQC device is controlled by an adaptive neuro fuzzy inference system (ANFIS) control and it is powered from the available photovoltaics (PV) power generation. The effect of adding an intelligent UPQC is tested in the standard IEEE-14bus environment. MATLAB 2017b is used here for testing and plotting the simulation results.

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Section: Introductionmentioning

confidence: 99%

Validation of photovoltaics powered UPQC using ANFIS controller in a standard microgrid test environment

Sumana

Dhanalakshmi

Dhamodharan³

2022

IJECE

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“…These chargers may be affected due to the usage of the intermittent power source like solar and wind to protect that a new control is proposed in [11]. A new topology of bidirectional power transmission for charging and mitigating the power quality by using the sliding mode control is implemented in [12]. The bidirectional operation causes the voltage problems in the grid when using it as V2G and G2V an low voltage ride through (LVRT) is used to improve the voltage profile in [13], [14].…”

Section: Introductionmentioning

confidence: 99%

Power quality mitigation and transient analysis in AC/DC hybrid microgrid for electric vehicle charging

Rao

Rangaswamy

2021

IJEECS

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The usage of electric vehicles (EV) increased in recent years as the vehicles design and performances are nearly similar to petrol vehicles. The main source of energy for EV is taken from the grid for charging. So, the penetration of EVs in alternating current (AC) grid creates more power quality issues like voltage sag, swell and harmonics in the current. This energy can also be produced from the renewable energy resources like photovoltaic (PV) power generation. This PV energy can also be used as direct current (DC) grid. The electric vehicle chargers which come with intelligent grid operation is considered as load in this paper. This paper is an attempt to discuss the penetration of EVs in AC/DC hybrid micro grid which causes the power quality problems, and the power quality problem is mitigated by using the unified power quality conditioner (UPQC). The results are analyzed for three cases and four scenarios which is based on the function of UPQC and the action of smart charger in grid connected as well as autonomous mode operation of the AC/DC micro grid when the load is considered as dynamic load. The simulation is carried out in MATLAB2017b environment

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“…Most of the EVs have the capability of regenerative braking, which can reduce external energy consumption by 20% in urban areas. [14][15][16] Coordinated or controlled charging of EV can be used to alleviate issues arisen from the uncontrolled charging. EV owner may opt for level 1 and level 2 charging at home or level 3 fast charging at public and commercial charging stations.…”

Section: Introductionmentioning

confidence: 99%

“…Increased penetration of EV can cause phase-unbalance, under-voltage, harmonics, and outages in the distribution grid. [14][15][16] Coordinated or controlled charging of EV can be used to alleviate issues arisen from the uncontrolled charging. Unidirectional (ie, grid to vehicle [G2V]) controlled charging can be mainly classified as indirectly controlled charging and directly controlled charging.…”

Section: Introductionmentioning

confidence: 99%

Charging cost minimisation by centralised controlled charging of electric vehicles

Patil

Kalkhambkar

2019

Int Trans Electr Energ Syst

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Summary With the recent breakthroughs in battery technology and large scale production, electric vehicles (EVs) are becoming cheaper. In a few years, mass deployment of EVs will put severe stress on the electricity network. Charging of EV during peak hours may overload the distribution grid transformer, and EV owners may have to pay more money for electricity during peak hours. To address these issues, a coordinated scheduling model is proposed in this paper. A mathematical model is formulated to minimise the charging cost of each EV while satisfying the constraints. In this work, time of use (ToU) tariff from the utility and actual power demand from household and EVs are used to conduct simulation for one week in summer and winter season with different levels of EV penetration. The results demonstrate that the proposed scheduling model can significantly reduce the charging cost for the EV owner and power peaks in the distribution network.

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Method to improve charging power quality of electric vehicles

Cited by 6 publications

References 7 publications

Validation of photovoltaics powered UPQC using ANFIS controller in a standard microgrid test environment

Validation of photovoltaics powered UPQC using ANFIS controller in a standard microgrid test environment

Power quality mitigation and transient analysis in AC/DC hybrid microgrid for electric vehicle charging

Charging cost minimisation by centralised controlled charging of electric vehicles

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