DocumentCode
1759033
Title
Environmental/economic dispatch incorporating renewable energy sources and plug-in vehicles
Author
Gholami, Amir ; Ansari, Javad ; Jamei, Mahdi ; Kazemi, A.
Author_Institution
Centre of Excellence for Power Syst. Autom. & Oper., Iran Univ. of Sci. & Technol., Tehran, Iran
Volume
8
Issue
12
fYear
2014
fDate
12 2014
Firstpage
2183
Lastpage
2198
Abstract
Transportation and electricity industries are considered as major sources of greenhouse gases (GHGs) emission. Different methods have been proposed to deal with the increasing rate of the emission, such as employing plug-in electric vehicles (PEVs) and integrating renewable energy sources (RESs). However, it is important to scrutinise different scenarios of incorporating the mentioned elements to decrease the concerning emission rate while considering the economic constraints. In this study, a combined economic emission dispatch (CEED) is employed to investigate the effectiveness of using PEVs and RESs from different aspects. A sensitivity analysis is executed to survey the influence of emission and cost coefficients. Two test cases each including different scenarios are simulated to determine the efficacy of different types of integration in the proposed model. To have a more accurate and realistic survey, an extended model of the wind farm´s cost function is employed in economic dispatch calculations. The particle swarm optimisation algorithm is applied to solve the CEED non-linear problem. The obtained results indicate that the integration of PEVs cannot necessarily reduce the net emission of two industries. In fact, the optimum solution should include the incorporation of PEVs along with RESs to return the desired results.
Keywords
air pollution control; electric vehicles; nonlinear programming; particle swarm optimisation; power generation dispatch; power generation economics; renewable energy sources; wind power plants; CEED; GHG emission; PEV; RES; combined economic emission dispatch; electricity industry; environmental-economic dispatch; greenhouse gas emission; nonlinear problem; particle swarm optimisation algorithm; plug-in electric vehicle; renewable energy source; sensitivity analysis; transportation; wind farm;
fLanguage
English
Journal_Title
Generation, Transmission & Distribution, IET
Publisher
iet
ISSN
1751-8687
Type
jour
DOI
10.1049/iet-gtd.2014.0235
Filename
6985864
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