Impact of electric vehicle load response variation on frequency stability

Qazi, Hassan W.; Flynn, Damian; Rather, Zakir Hussain

doi:10.1109/isgteurope.2016.7856268

Cited by 12 publications

(3 citation statements)

References 15 publications

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“…This, therefore, means that the electricity sector needs to be upgraded and made robust to accommodate strategically placed electric vehicle charging stations (EVCS). The Increased penetration of EVs into the distribution network will necessitate solutions to compensate for the effects they have on the network such as increased power loss, voltage and frequency instability due to random charging, and network overloads [4]. A potential solution is the installation of distributed generation (DG) such as photovoltaic (PV) systems.…”

Section: Introductionmentioning

confidence: 99%

Optimal Integration of Electric Vehicle Charging Stations and Compensating Photovoltaic Systems in a Distribution Network Segregated into Communities

Fokui¹,

Ngoo

Saulo

2022

J. ADV. ENG. COMPUT.

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This paper proposes a method of optimally utilizing electric vehicles (EVs) in the distribution network. The method is firstly based on segregating the distribution network into communities and then optimally placing an EV charging station (EVCS) in each community using the backward forward sweep (BFS) technique. The Second phase uses particle swarm optimization (PSO) to size and allocates photovoltaic systems in the network for power loss minimization and voltage improvement. The proposed method is tested on an IEEE 33 node test feeder and simulation results showed the effectiveness of the BFS in finding the best nodes for the placement of EVCS in each community as well as the effectiveness of the PSO in allocating the photovoltaic systems. To validate the effectiveness of the BFS technique, its results obtained are compared with those obtained when the EVCSs are placed on some nodes other than those chosen by the BFS technique.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.

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Section: Introductionmentioning

confidence: 99%

Optimal Integration of Electric Vehicle Charging Stations and Compensating Photovoltaic Systems in a Distribution Network Segregated into Communities

Fokui¹,

Ngoo

Saulo

2022

J. ADV. ENG. COMPUT.

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show abstract

“…According to the development of the EV and the charging station, many pieces of literature have been written to be able to study the effect of the large scale demand; in terms of the reduction of the steady state voltage stability, system losses, voltage profiles, voltage imbalance, and harmonics impact based on the EV charging model [3][4][5][6][7][8][9][10]. The impact of the EVs load had affected the electrical power system; in terms of power system stability.…”

Section: Introductionmentioning

confidence: 99%

“…The impact of the EVs load had affected the electrical power system; in terms of power system stability. This impact needed to mitigate the transient frequency response of the electrical power system [5]. The voltage dependent load characteristic had found that the EV loads had caused the highest impact to the electrical power system when compared to conventional constant power load, constant current load, and constant impedance load in a single machine infinite bus [4].…”

Section: Introductionmentioning

confidence: 99%

Estimation of the Quick Charging Station for Electric Vehicles based on Location and Population Density Data

Kongjeen¹,

Junlakan²,

Bhumkittipich³

et al. 2018

IJIES

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This paper has presented the estimation methodology of the quick charging station for electric vehicles (EVs) based on both area and population density data. The proportion of EV owners per number of population in location data; is also used to compute the number of the quick charging stations. The population density data and proportion of EVs owners per number of population in area data are varied from 1 to 6 % and 0.01 to 0.8 %, respectively. The simulation results showed that the number of EVs stations increased and the randomly selected Feeder No.1 was installed at EVs stations; of which range from No.1 to No.4. The total real power loss increased up to 18%. Therefore, this study could be verified that the quick charging stations should be considered both optimal in sizing and location of EVs charging stations.

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Moth Flame Optimized Automatic Generation Control with PIDF Controller for the Integration of Plug-In Electrical Vehicles with Interconnected Power System

Acharyulu¹,

Simhadri

Seshasai³

et al. 2021

Lecture Notes in Electrical Engineering

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Impact of electric vehicle load response variation on frequency stability

Cited by 12 publications

References 15 publications

Optimal Integration of Electric Vehicle Charging Stations and Compensating Photovoltaic Systems in a Distribution Network Segregated into Communities

Optimal Integration of Electric Vehicle Charging Stations and Compensating Photovoltaic Systems in a Distribution Network Segregated into Communities

Estimation of the Quick Charging Station for Electric Vehicles based on Location and Population Density Data

Moth Flame Optimized Automatic Generation Control with PIDF Controller for the Integration of Plug-In Electrical Vehicles with Interconnected Power System

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