Accommodating high penetration of PEV in distribution networks

M. F. Shaabar; E. F. El-Saadany

doi:10.1109/EPEC.2013.6802945

Accommodating high penetration of PEV in distribution networks

M. F. Shaabar, E. F. El-Saadany

Electrical Engineering

University of Waterloo

Research output: Contribution to conference › Paper › peer-review

2 Scopus citations

Abstract

This paper proposes a multi-objective planning algorithm to accommodate high penetration of plug-in electric vehicles (PEVs) in distribution networks. The proposed algorithm is based on allocating different distributed generation (DG) units to minimize system costs and emissions. A Non-dominated sorting genetic algorithm (NDSGA) based approach is utilized for the planning problem of determining the optimal PEV penetration, location, and sizes of DG units. The problem is defined as multi-objective mixed integer nonlinear programming. The proposed methodology can help the local distribution companies (LDCs) to better assess the PEV impacts on their systems and mitigate them. Moreover, the proposed methodology can help the LDCs to better assess the DG connections proposals to their networks.

Original language	British English
DOIs	https://doi.org/10.1109/EPEC.2013.6802945
State	Published - 2013
Event	2013 IEEE Electrical Power and Energy Conference, EPEC 2013 - Halifax, NS, Canada Duration: 21 Aug 2013 → 23 Aug 2013

Conference

Conference	2013 IEEE Electrical Power and Energy Conference, EPEC 2013
Country/Territory	Canada
City	Halifax, NS
Period	21/08/13 → 23/08/13

Keywords

Capacity factor
Carbon dioxide emissions
Distributed power generation
Electric vehicles

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/EPEC.2013.6802945

Cite this

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title = "Accommodating high penetration of PEV in distribution networks",

abstract = "This paper proposes a multi-objective planning algorithm to accommodate high penetration of plug-in electric vehicles (PEVs) in distribution networks. The proposed algorithm is based on allocating different distributed generation (DG) units to minimize system costs and emissions. A Non-dominated sorting genetic algorithm (NDSGA) based approach is utilized for the planning problem of determining the optimal PEV penetration, location, and sizes of DG units. The problem is defined as multi-objective mixed integer nonlinear programming. The proposed methodology can help the local distribution companies (LDCs) to better assess the PEV impacts on their systems and mitigate them. Moreover, the proposed methodology can help the LDCs to better assess the DG connections proposals to their networks.",

keywords = "Capacity factor, Carbon dioxide emissions, Distributed power generation, Electric vehicles",

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note = "2013 IEEE Electrical Power and Energy Conference, EPEC 2013 ; Conference date: 21-08-2013 Through 23-08-2013",

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AU - El-Saadany, E. F.

PY - 2013

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N2 - This paper proposes a multi-objective planning algorithm to accommodate high penetration of plug-in electric vehicles (PEVs) in distribution networks. The proposed algorithm is based on allocating different distributed generation (DG) units to minimize system costs and emissions. A Non-dominated sorting genetic algorithm (NDSGA) based approach is utilized for the planning problem of determining the optimal PEV penetration, location, and sizes of DG units. The problem is defined as multi-objective mixed integer nonlinear programming. The proposed methodology can help the local distribution companies (LDCs) to better assess the PEV impacts on their systems and mitigate them. Moreover, the proposed methodology can help the LDCs to better assess the DG connections proposals to their networks.

AB - This paper proposes a multi-objective planning algorithm to accommodate high penetration of plug-in electric vehicles (PEVs) in distribution networks. The proposed algorithm is based on allocating different distributed generation (DG) units to minimize system costs and emissions. A Non-dominated sorting genetic algorithm (NDSGA) based approach is utilized for the planning problem of determining the optimal PEV penetration, location, and sizes of DG units. The problem is defined as multi-objective mixed integer nonlinear programming. The proposed methodology can help the local distribution companies (LDCs) to better assess the PEV impacts on their systems and mitigate them. Moreover, the proposed methodology can help the LDCs to better assess the DG connections proposals to their networks.

KW - Capacity factor

KW - Carbon dioxide emissions

KW - Distributed power generation

KW - Electric vehicles

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DO - 10.1109/EPEC.2013.6802945

M3 - Paper

AN - SCOPUS:84901311938

T2 - 2013 IEEE Electrical Power and Energy Conference, EPEC 2013

Y2 - 21 August 2013 through 23 August 2013

ER -

Accommodating high penetration of PEV in distribution networks

Abstract

Conference

Keywords

UN SDGs

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