An Optimization Framework for Distributed Energy Resource Planning and Energy Management Strategy of Storage Devices and Electric Vehicles

Bahman Ahmadi, Oguzhan Ceylan, Aydogan Ozdemir

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

2 Citations (Scopus)
59 Downloads (Pure)

Abstract

This paper proposes an optimal coordination strategy for electric vehicles and energy storage devices in distribution grids besides the optimal allocation problem of renewable distributed generation (RDGs) and energy storage devices (ESDs). By finding the optimal number, size, and site of the RDGs and ESDs, together with the operation strategy of the ESDs and smart charging of a large number of EVs, the performance of the distribution grids will be improved. An advanced grey wolf optimization (AGWO) algorithm is used to minimize energy losses and voltage violations simultaneously in the test systems. Simulations are tested on IEEE 33 and 69 bus networks to find near-optimal solutions for the optimization problem. Based on the simulation results, the proposed optimization framework reduced the systems' losses while minimizing the voltage violations by finding the optimal control parameters of the devices.

Original languageEnglish
Title of host publicationSyNERGY MED 2022 - 2nd International Conference on Energy Transition in the Mediterranean Area, Proceedings
Place of PublicationPiscataway, NJ
PublisherIEEE
ISBN (Electronic)978-1-6654-6107-8
ISBN (Print)978-1-6654-6108-5
DOIs
Publication statusPublished - 10 Nov 2022
Event2nd International Conference on Energy Transition in the Mediterranean Area, SyNERGY MED 2022 - Thessaloniki, Greece
Duration: 17 Oct 202119 Oct 2021
Conference number: 2

Conference

Conference2nd International Conference on Energy Transition in the Mediterranean Area, SyNERGY MED 2022
Abbreviated titleSyNERGY MED 2022
Country/TerritoryGreece
CityThessaloniki
Period17/10/2119/10/21

Keywords

  • Distributed generation
  • Electric vehicle charging management
  • Heuristics
  • Real power losses
  • Storage systems
  • 22/4 OA procedure

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