Combined Solar Charging Stations and Energy Storage Units Allocation for Electric Vehicles by Considering Uncertainties

Babak  Yousefi Khanghah; Amjad Anvari-Moghaddam; Josep M. Guerrero; Juan Carlos Vasquez Quintero

doi:10.1109/EEEIC.2017.7977806

Combined Solar Charging Stations and Energy Storage Units Allocation for Electric Vehicles by Considering Uncertainties

Babak Yousefi Khanghah, Amjad Anvari-Moghaddam, Josep M. Guerrero, Juan Carlos Vasquez Quintero

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

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Abstract

Electric vehicles (EVs) are becoming a key feature of smart grids. EVs will be embedded in the smart grids as a mobile load-storage with probabilistic behavior. In order to manage EVs as flexible loads, charging stations (CSs) have essential roles. In this paper, a new method for optimal sitting and sizing of solar CSs using energy storage (ES) options is presented. Also, behavior of EVs in the presence of other loads, electricity price and solar power generation uncertainties are considered. The proposed optimization model maximizes the distribution company (DisCo) benefit by appropriate use of CSs, maximizes the benefit of CSs owners and minimizes the power loss, load demand and voltage sags during peak times considering different technical constraints. The optimization variables are the location and capacity of solar units and energy storage systems. In this paper, charge-discharge process of EVs are considered based on time-of-use (TOU) demand response programs (DRPs). In order to solve the optimization problem considering uncertainty of load growth, electricity price, initial state of charge of batteries and solar power generation, genetic algorithm method using Monte-Carlo simulation is used. The simulation results show that the proposed method has advantages for DisCo and owners of CSs.

Original language	English
Title of host publication	Proceedings of the 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)
Number of pages	6
Publisher	IEEE Press
Publication date	Jun 2017
Pages	1-6
ISBN (Print)	978-1-5386-3917-7
DOIs	https://doi.org/10.1109/EEEIC.2017.7977806
Publication status	Published - Jun 2017
Event	2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) - Milano, Italy Duration: 6 Jun 2017 → 9 Jun 2017

Conference

Conference	2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)
Country/Territory	Italy
City	Milano
Period	06/06/2017 → 09/06/2017

Keywords

Electric vehicles
Charging station
Multi-objective optimization
Energy storage
Demand response program
Smart grid

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10.1109/EEEIC.2017.7977806

Combined Solar Charging Stations and Energy Storage Units Allocation for Plug-In Electric Vehicles by Considering UncertaintiesFinal published version, 434 KB

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Yousefi Khanghah, B., Anvari-Moghaddam, A., Guerrero, J. M., & Quintero, J. C. V. (2017). Combined Solar Charging Stations and Energy Storage Units Allocation for Electric Vehicles by Considering Uncertainties. In Proceedings of the 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) (pp. 1-6). IEEE Press. https://doi.org/10.1109/EEEIC.2017.7977806

Yousefi Khanghah, Babak ; Anvari-Moghaddam, Amjad ; Guerrero, Josep M. et al. / Combined Solar Charging Stations and Energy Storage Units Allocation for Electric Vehicles by Considering Uncertainties. Proceedings of the 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). IEEE Press, 2017. pp. 1-6

@inproceedings{a2762eed45004634bc1a05bce739723b,

title = "Combined Solar Charging Stations and Energy Storage Units Allocation for Electric Vehicles by Considering Uncertainties",

abstract = "Electric vehicles (EVs) are becoming a key feature of smart grids. EVs will be embedded in the smart grids as a mobile load-storage with probabilistic behavior. In order to manage EVs as flexible loads, charging stations (CSs) have essential roles. In this paper, a new method for optimal sitting and sizing of solar CSs using energy storage (ES) options is presented. Also, behavior of EVs in the presence of other loads, electricity price and solar power generation uncertainties are considered. The proposed optimization model maximizes the distribution company (DisCo) benefit by appropriate use of CSs, maximizes the benefit of CSs owners and minimizes the power loss, load demand and voltage sags during peak times considering different technical constraints. The optimization variables are the location and capacity of solar units and energy storage systems. In this paper, charge-discharge process of EVs are considered based on time-of-use (TOU) demand response programs (DRPs). In order to solve the optimization problem considering uncertainty of load growth, electricity price, initial state of charge of batteries and solar power generation, genetic algorithm method using Monte-Carlo simulation is used. The simulation results show that the proposed method has advantages for DisCo and owners of CSs.",

keywords = "Electric vehicles, Charging station, Multi-objective optimization, Energy storage, Demand response program, Smart grid",

author = "{Yousefi Khanghah}, Babak and Amjad Anvari-Moghaddam and Guerrero, {Josep M.} and Quintero, {Juan Carlos Vasquez}",

year = "2017",

month = jun,

doi = "10.1109/EEEIC.2017.7977806",

language = "English",

isbn = "978-1-5386-3917-7",

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booktitle = "Proceedings of the 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)",

publisher = "IEEE Press",

note = "2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) ; Conference date: 06-06-2017 Through 09-06-2017",

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Yousefi Khanghah, B, Anvari-Moghaddam, A , Guerrero, JM & Quintero, JCV 2017, Combined Solar Charging Stations and Energy Storage Units Allocation for Electric Vehicles by Considering Uncertainties. in Proceedings of the 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). IEEE Press, pp. 1-6, 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), Milano, Italy, 06/06/2017. https://doi.org/10.1109/EEEIC.2017.7977806

Combined Solar Charging Stations and Energy Storage Units Allocation for Electric Vehicles by Considering Uncertainties. / Yousefi Khanghah, Babak ; Anvari-Moghaddam, Amjad ; Guerrero, Josep M. et al.
Proceedings of the 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). IEEE Press, 2017. p. 1-6.

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

TY - GEN

T1 - Combined Solar Charging Stations and Energy Storage Units Allocation for Electric Vehicles by Considering Uncertainties

AU - Yousefi Khanghah, Babak

AU - Anvari-Moghaddam, Amjad

AU - Guerrero, Josep M.

AU - Quintero, Juan Carlos Vasquez

PY - 2017/6

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N2 - Electric vehicles (EVs) are becoming a key feature of smart grids. EVs will be embedded in the smart grids as a mobile load-storage with probabilistic behavior. In order to manage EVs as flexible loads, charging stations (CSs) have essential roles. In this paper, a new method for optimal sitting and sizing of solar CSs using energy storage (ES) options is presented. Also, behavior of EVs in the presence of other loads, electricity price and solar power generation uncertainties are considered. The proposed optimization model maximizes the distribution company (DisCo) benefit by appropriate use of CSs, maximizes the benefit of CSs owners and minimizes the power loss, load demand and voltage sags during peak times considering different technical constraints. The optimization variables are the location and capacity of solar units and energy storage systems. In this paper, charge-discharge process of EVs are considered based on time-of-use (TOU) demand response programs (DRPs). In order to solve the optimization problem considering uncertainty of load growth, electricity price, initial state of charge of batteries and solar power generation, genetic algorithm method using Monte-Carlo simulation is used. The simulation results show that the proposed method has advantages for DisCo and owners of CSs.

AB - Electric vehicles (EVs) are becoming a key feature of smart grids. EVs will be embedded in the smart grids as a mobile load-storage with probabilistic behavior. In order to manage EVs as flexible loads, charging stations (CSs) have essential roles. In this paper, a new method for optimal sitting and sizing of solar CSs using energy storage (ES) options is presented. Also, behavior of EVs in the presence of other loads, electricity price and solar power generation uncertainties are considered. The proposed optimization model maximizes the distribution company (DisCo) benefit by appropriate use of CSs, maximizes the benefit of CSs owners and minimizes the power loss, load demand and voltage sags during peak times considering different technical constraints. The optimization variables are the location and capacity of solar units and energy storage systems. In this paper, charge-discharge process of EVs are considered based on time-of-use (TOU) demand response programs (DRPs). In order to solve the optimization problem considering uncertainty of load growth, electricity price, initial state of charge of batteries and solar power generation, genetic algorithm method using Monte-Carlo simulation is used. The simulation results show that the proposed method has advantages for DisCo and owners of CSs.

KW - Electric vehicles

KW - Charging station

KW - Multi-objective optimization

KW - Energy storage

KW - Demand response program

KW - Smart grid

U2 - 10.1109/EEEIC.2017.7977806

DO - 10.1109/EEEIC.2017.7977806

M3 - Article in proceeding

SN - 978-1-5386-3917-7

SP - 1

EP - 6

BT - Proceedings of the 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)

PB - IEEE Press

T2 - 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)

Y2 - 6 June 2017 through 9 June 2017

ER -

Yousefi Khanghah B, Anvari-Moghaddam A , Guerrero JM , Quintero JCV. Combined Solar Charging Stations and Energy Storage Units Allocation for Electric Vehicles by Considering Uncertainties. In Proceedings of the 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). IEEE Press. 2017. p. 1-6 doi: 10.1109/EEEIC.2017.7977806

Combined Solar Charging Stations and Energy Storage Units Allocation for Electric Vehicles by Considering Uncertainties

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