Published March 2014 | Version v1
Journal article

Multi-objective scheduling of electric vehicles in smart distribution system

  • 1. Department of Electrical Engineering, Iran University of Science and Technology, Tehran (Iran, Islamic Republic of)
  • 2. Department of Industrial Engineering, University of Salerno, Fisciano (Italy)

Description

Highlights: • Environmental/economic operational scheduling of electric vehicles. • The Vehicle to Grid capability and the actual patterns of drivers are considered. • A novel conceptual model for an electric vehicle management system is proposed. - Abstract: When preparing for the widespread adoption of Electric Vehicles (EVs), an important issue is to use a proper EVs' charging/discharging scheduling model that is able to simultaneously consider economic and environmental goals as well as technical constraints of distribution networks. This paper proposes a multi-objective operational scheduling method for charging/discharging of EVs in a smart distribution system. The proposed multi-objective framework, based on augmented ε-constraint method, aims at minimizing the total operational costs and emissions. The Vehicle to Grid (V2G) capability as well as the actual patterns of drivers are considered in order to generate the Pareto-optimal solutions. The Benders decomposition technique is used in order to solve the proposed optimization model and to convert the large scale mixed integer nonlinear problem into mixed-integer linear programming and nonlinear programming problems. The effectiveness of the proposed resources scheduling approach is tested on a 33-bus distribution test system over a 24-h period. The results show that the proposed EVs' charging/discharging method can reduce both of operation cost and air pollutant emissions

Availability note (English)

Available from http://dx.doi.org/10.1016/j.enconman.2013.11.042

Additional details

Identifiers

DOI
10.1016/j.enconman.2013.11.042;
PII
S0196-8904(13)00763-2;

Publishing Information

Journal Title
Energy Conversion and Management
Journal Volume
79
Journal Page Range
p. 43-53
ISSN
0196-8904
CODEN
ECMADL

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
46022443
Subject category
S42: ENGINEERING; S29: ENERGY PLANNING, POLICY AND ECONOMY;
Descriptors DEI
AIR POLLUTION; DISTRIBUTION; LINEAR PROGRAMMING; MANAGEMENT; NONLINEAR PROBLEMS; NONLINEAR PROGRAMMING; OPERATING COST; OPTIMIZATION
Descriptors DEC
CALCULATION METHODS; COST; POLLUTION

Optional Information

Copyright
Copyright (c) 2013 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.