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Cited by 23Electric Vehicles and InfrastructureOptimal Power Flow DistributionSmart Grid Energy Management

The DOI matches its Crossref record.

Optimal planning of PEVs Charging Stations and Demand Response programs considering distribution and traffic networks

Pazouki, Samaneh, Mohsenzadeh, Amin, Haghifam, Mahmoud-Reza·2013·2013 Smart Grid Conference (SGC)
DOI 10.1109/sgc.2013.6733806
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Abstract

One of the challenges of big cities is Green House Gases (GHG) emissions due to driving cars with Internal Conventional Engines (ICE), which are dependent on fossil fuels. Plug-In Electric Vehicles (PEVs) have been developing to cope with the challenges. Flexible fuels, convenience, safe charging, high performance and cost saving are also considered as significant benefits of the technologies. In spite of aforementioned advantages, inappropriate place and size of aggregated PEVs increase loss and voltage degradation. Therefore, optimal planning of Charging Stations (CSs), which consider loss and voltage, is presented in this paper. Time-based programs of Demand Response (DR) are also employed for improving loss and voltage. Time-Of-Use (TOU), Critical Peak Pricing (CPP) and Real Time Pricing (RTP) are applied on the problem. Candidate place of CSs is optimally found by traffic network along with distribution network. Genetic Algorithm (GA) is used to solve the problem. Simulation carries out a 33 bus radial distribution network. Results reveal optimal size of CSs as well as DR programs effect to minimize loss and voltage drop in distribution network. Results demonstrate CSs with more capacity farther power supply may increase loss and voltage degradation. Thus, close candidate places are sized by CSs with more capacity. Results also approve integration of CSs to grid may cause %33 loss and %0.3-%2.3 voltage degradation, which DR with different programs (CPP, TOU and RTP) can…

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Research works printed but not linked: 17

  1. 10.1109/TPWRS.2002.1007912 · DOI
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  14. guibin, 2013, Traffic-Constrained Multiobjective Planning of Electric-Vehicle Charging Stations
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Metadata

Authors
Pazouki, S., Mohsenzadeh, A., & Haghifam, M.-R.
Affiliations
  • Islamic Azad University, Tehran (IR)
  • Tarbiat Modares University (IR)
ORCID
Venue
2013 Smart Grid Conference (SGC)
Publisher
IEEE
Published
2013-12
Pages
90-95
DOI
10.1109/sgc.2013.6733806
OpenAlex
W2045537704
Cited by
23
References
0
Citations by year
2024: 3 · 2023: 4 · 2022: 3 · 2020: 1 · 2019: 2 · 2018: 4 · 2017: 1 · 2016: 2 · 2015: 2 · 2013: 1
FWCI
2.03
Type
conference paper
Language
en
Open access
closed
Locations
Smart Grid Conference (publishedVersion)
Topics
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Vehicles and Infrastructure
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Optimal Power Flow Distribution
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
Keywords
plug-in electric vehicles, charging station siting and sizing, demand response, distribution losses, voltage drop, traffic networks, time-of-use pricing, critical peak pricing, real-time pricing, genetic algorithm, greenhouse gas emissions

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