Multi-objective Advanced Grey Wolf optimization Framework for Smart Charging Scheduling of EVs in Distribution Grids

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Abstract

This paper proposes a multi-objective optimization technique for scheduling the charging of electric vehicles (EVs) in electrical distribution systems (DSs). A multi-objective advanced grey wolf optimization algorithm (MOAGWO) is developed to find the Pareto optimal solutions that minimize the DS's operational costs, energy losses costs, voltage violations, and the energy not supplied to EV users using several scenarios. A 449-node system with 63% penetration of EVs is used to demonstrate the efficiency of the proposed method. The quality of the non-dominated optimal solutions found by MOAGWO are validated via a comparison analysis with other well-known methods such as the multi-objective grey wolf optimizer (MOGWO) and the multi-objective particle swarm optimization (MOPSO) algorithm, based on domination rate, spacing index, hypervolume index, and computational cost measurements. The Pareto solutions indicate that the smart charging coordination found by MOAGWO makes the techno-economic operation of the DS possible while satisfying energy-based goals of the EV users.

Original languageEnglish
Title of host publication2022 57th International Universities Power Engineering Conference
Subtitle of host publicationBig Data and Smart Grids, UPEC 2022 - Proceedings
Place of PublicationPiscataway, NJ
PublisherIEEE
ISBN (Electronic)978-1-6654-5505-3
ISBN (Print)978-1-6654-5506-0
DOIs
Publication statusPublished - 18 Oct 2022
Event57th International Universities Power Engineering Conference: Big Data and Smart Grids, UPEC 2022 - Istanbul, Turkey
Duration: 30 Aug 20222 Sept 2022
Conference number: 57

Conference

Conference57th International Universities Power Engineering Conference: Big Data and Smart Grids, UPEC 2022
Abbreviated titleUPEC 2022
Country/TerritoryTurkey
CityIstanbul
Period30/08/222/09/22

Keywords

  • Electric vehicles
  • Meta-heuristic
  • Multi-objective optimization
  • Pareto front
  • Smart grids
  • 22/4 OA procedure

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