Enhancing Grid Operation with Electric Vehicle Integration in Automatic Generation Control

Zahid Ullah, Kaleem Ullah, Cesar Diaz-Londono (), Giambattista Gruosso and Abdul Basit
Additional contact information
Zahid Ullah: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Piazza Leonardo da Vinci, 32, 20133 Milano, Italy
Kaleem Ullah: US-Pakistan Center for Advanced Studies in Energy, University of Engineering and Technology Peshawar, Peshawar 25000, Pakistan
Cesar Diaz-Londono: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Piazza Leonardo da Vinci, 32, 20133 Milano, Italy
Giambattista Gruosso: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Piazza Leonardo da Vinci, 32, 20133 Milano, Italy
Abdul Basit: Manager R&D, National Power Control Center, National Transmission and Dispatch Company, Islamabad 44000, Pakistan

Energies, 2023, vol. 16, issue 20, 1-18

Abstract: Wind energy has been recognized as a clean energy source with significant potential for reducing carbon emissions. However, its inherent variability poses substantial challenges for power system operators due to its unpredictable nature. As a result, there is an increased dependence on conventional generation sources to uphold the power system balance, resulting in elevated operational costs and an upsurge in carbon emissions. Hence, an urgent need exists for alternative solutions that can reduce the burden on traditional generating units and optimize the utilization of reserves from non-fossil fuel technologies. Meanwhile, vehicle-to-grid (V2G) technology integration has emerged as a remedial approach to rectify power capacity shortages during grid operations, enhancing stability and reliability. This research focuses on harnessing electric vehicle (EV) storage capacity to compensate for power deficiencies caused by forecasting errors in large-scale wind energy-based power systems. A real-time dynamic power dispatch strategy is developed for the automatic generation control (AGC) system to integrate EVs and utilize their reserves optimally to reduce reliance on conventional power plants and increase system security. The results obtained from this study emphasize the significant prospects associated with the fusion of EVs and traditional power plants, offering a highly effective solution for mitigating real-time power imbalances in large-scale wind energy-based power systems.

Keywords: electric vehicle area; automatic generation control; forecasting errors; power dispatch strategies; modern power grid (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.mdpi.com/1996-1073/16/20/7118/pdf (application/pdf)
https://www.mdpi.com/1996-1073/16/20/7118/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:16:y:2023:i:20:p:7118-:d:1261284

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().