Simultaneous Planning of PEV Charging Stations and DGs Considering Financial, Technical,and Environmental Effects

Pazouki, Samaneh; Mohsenzadeh, Amin; Ardalan, Shahab; Haghifam, Mahmoud‐Reza

doi:10.1109/cjece.2015.2436811

Cited by 58 publications

(22 citation statements)

References 24 publications

(25 reference statements)

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“…In [17] a dc-grid interconnection is proposed to integrate EVs in power system and to enhance power handling capacity of AC distribution feeder. In another study, results confirm that simultaneous planning of charge station and distributed generation (DG) improves total costs, losses, voltage profile and reduces GHG emissions levels [18]. In another hand, ICT can help to estimate and prognosticate the state of charge of the EVs batteries and detect a fault in early stages [19].…”

Section: Introductionmentioning

confidence: 89%

A model for electric vehicle integration in a connected microgrid considering Greenhouse gas emissions.

Jacome-Ruiz¹,

Hidalgo-León²,

Sanchez-Zurita³

et al. 2017

Proceedings of the 15th LACCEI International Multi-Conference for Engineering, Education, and Technology: “Global Partnership F

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In this paper we present a solution for an interconnected micro grid's design including electrical vehicles. This micro grid is oriented to be placed in Guayaquil-Ecuador and integrates electric vehicle charge stations, a photovoltaic generator, a thermal unit, a battery energy storage system and an interconnection point to a distribution network. Moreover, the proposed microgrid includes an electric vehicle fleet oriented for the commercial sector. The model takes advantage of renewable resource generated locally (photovoltaic solar energy). This helps us to minimize the purchases from distribution network and to reduce costs for electric vehicles charging. Technical and economic considerations are taken into account in the present analysis. Additionally, the model minimizes the greenhouse gas emissions including as an input a tax rate for emissions. The simulations results allow us to determine the minimal cost of implementing the microgrid and the optimal strategies to reduce the implicit cost of integrating electric vehicles in the network.

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Section: Introductionmentioning

confidence: 89%

A model for electric vehicle integration in a connected microgrid considering Greenhouse gas emissions.

Jacome-Ruiz¹,

Hidalgo-León²,

Sanchez-Zurita³

et al. 2017

Proceedings of the 15th LACCEI International Multi-Conference for Engineering, Education, and Technology: “Global Partnership F

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show abstract

“…Mohsenzadeh, Pazouki, Haghifam, and Pang () presented a novel methodology for optimal planning of parking lots in distribution network considering power loss and voltage profile. Pazouki, Mohsenzadeh, Ardalan, and Haghifam () presented a scheme for efficient planning of PEV charging stations and distributed generation (DG) considering financial, technical, and environmental effects. They carried out the simulation study on IEEE 33 bus radial distribution network.…”

Section: Modeling Of Charging Infrastructure Planning Problemmentioning

confidence: 99%

Review of recent trends in charging infrastructure planning for electric vehicles

Deb

Tammi

Kalita

et al. 2018

WIREs Energy & Environment

129

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1. This work presents the scenario of charging infrastructure development across selected countries. An overview and importance of home charging is also presented in the work. 2. This paper also provides a deep insight of the complex and dynamic nature of the optimal placement of charging station problem, thereby considering the demand, logistics, and supply aspects related to the problem. 3. An overview and comparative analysis of different modeling approaches of charging station placement problem adopted by researchers is provided. 4. The different objective functions and constraints of the charging station placement problem are also discussed along with a brief understanding of the optimization algorithms adopted for the solution of this placement problem.The paper starts with an attempt to provide scenario of the charging infrastructure planning across selected countries, importance of home charging, and then presents a general overview and brief classification of the problem. The modeling approaches and the objective functions presented in different charging system studies are discussed in the work. Finally, the work concludes by identifying the future direction of work possible in this paradigm.

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“…The planning for EV charging station networks has been recently explored intensively in the literature by many researchers in both industry and academia from several viewpoints such as: (1) modeling the charging demands of the EVs [4][5][6][7][8][9][10][11]; (2) the considered planning targets and scenarios such as number of stations, locations and cost factors [12][13][14][15][16], and (3) in terms of the solution algorithms [17][18][19]. Here, we put together a brief review concerning the EVCS planning in terms of the main objectives and solution techniques (optimization methods) that have been used.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Electric Vehicle Charging Station Network Planning via a Co-Evolution Approach

Hayajneh

Zhang

2019

Energies

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The optimal planning of electric vehicle charging infrastructure has attracted extensive research interest in recent years. Most of the optimization problems were formulated by assuming that the configurations will be fixed at the optimal solution while overlooking the fact that the charging stations and the electric vehicles are “evolving” over time and have mutual impacts. On the other hand, little attention has been paid to evaluate the performance of the solutions in such a dynamic environment. Motivated by these gaps, this work develops a simulation model that captures the interactions between charging station configurations and electric vehicle population (and the preference of electric vehicles when choosing charging station). This modeling framework is then implemented to evaluate the performance of planned charging infrastructure in providing services to electric vehicles. Two indicators are calculated, i.e., usage rate and rejection rate. The former measures the “waste” due to abundant facilities installed; the latter measures the inadequacy of planned facilities, especially when the electric vehicle population is larger. The simulation results presented in this work validate the model and show the potential of the model not only to evaluate designs but also to be used for optimal planning in subsequent works.

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Simultaneous Planning of PEV Charging Stations and DGs Considering Financial, Technical,and Environmental Effects

Cited by 58 publications

References 24 publications

A model for electric vehicle integration in a connected microgrid considering Greenhouse gas emissions.

A model for electric vehicle integration in a connected microgrid considering Greenhouse gas emissions.

Review of recent trends in charging infrastructure planning for electric vehicles

Evaluation of Electric Vehicle Charging Station Network Planning via a Co-Evolution Approach

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