An optimized scheduling strategy for plugged-in electric vehicles integrated into a residential smart microgrid for both grid-tied and Islanded modes

Mohammad Amin Kazemi, Reza Sabzehgar, Mohammad Rasouli

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

This paper presents an optimized scheduling method for Plugged-in Electric Vehicles (PEV) that are connected to a residential smart microgrid. Two modes of operation are studied: grid-tied and islanded mode. A Genetic Algorithm (GA)-based method is utilized to optimize an objective function, which includes the cost of energy production, and guarantees the best possible energy consumption profile. The profit of the PEV owners, which has been ignored in most of the existing strategies, is included in the proposed objective function. Furthermore, in order to make the study more realistic, the grid constraints are taken into consideration in the new strategy. Simulation results are used to validate the effectiveness of the proposed approach.

Original languageEnglish (US)
Title of host publication2017 6th International Conference on Renewable Energy Research and Applications, ICRERA 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages251-256
Number of pages6
ISBN (Electronic)9781538620953
DOIs
StatePublished - Dec 12 2017
Event6th IEEE International Conference on Renewable Energy Research and Applications, ICRERA 2017 - San Diego, United States
Duration: Nov 5 2017Nov 8 2017

Publication series

Name2017 6th International Conference on Renewable Energy Research and Applications, ICRERA 2017
Volume2017-January

Other

Other6th IEEE International Conference on Renewable Energy Research and Applications, ICRERA 2017
CountryUnited States
CitySan Diego
Period11/5/1711/8/17

All Science Journal Classification (ASJC) codes

  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment

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