Ev charging management in a real-time optimization framework considering operational constraints

Authors

Hilmi Cihan Güldorum, E.T.S. de Ingeniería Industrial, Universidad de Castilla-La Mancha, Ciudad Real, Spain; Department of Electrical Engineering, Yildiz Technical University, Istanbul, Türkiye
Ayşe Kübra Erenoğlu, Department of Electrical Engineering, Yildiz Technical University, Istanbul, Türkiye; Clean Energy Technologies Institute, Yildiz Technical University, Istanbul, Türkiye
İbrahim Şengör, Department of Electrical and Electronic Engineering, Munster Technological University, Cork, IrelandFollow
Barry P. Hayes, MaREI, the SFI Research Centre for Energy, Climate and Marine, University College Cork, Cork, Ireland; School of Engineering and Architecture, University College Cork, Cork, Ireland
Ozan Erdinç, Department of Electrical Engineering, Yildiz Technical University, Istanbul, Türkiye

ORCID

https://orcid.org/0000-0002-9451-4218

Abstract

The electrification of transportation plays a central role in the decarbonization of energy systems. Although electric vehicles (EVs) are expected to reduce energy related emissions, the increasing demand imposed by large scale EV adoption presents serious challenges for distribution systems (DSs), which were not originally designed to accommodate such loads. This study proposes a mixed integer quadratically constrained programming (MIQCP) framework to optimize the operation of an EV parking lot (EVPL) under DS constraints. The model compares three widely adopted objective functions: minimization of active power loss, charging cost, and uncontrolled charging impact, which is represented by minimizing the total charging time. The optimization is based on an AC power flow formulation that explicitly captures voltage limits, load factor, and active and reactive power constraints. A rolling horizon based real time optimization strategy is employed to manage forecast uncertainties in EV behavior and photovoltaic generation. Real world conditions are reflected by incorporating two actual DS topologies from Türkiye and ten EV types with different technical specifications, evaluated at fifteen minute resolution. The results show that cost oriented EV charging strategies lead to the most adverse effects on system operation, including a %23.06 increase in distribution line losses and a %38.56 reduction in load factor compared to a base scenario without EVs. These findings highlight the critical need for objective aware planning by distribution system operators and aggregators, particularly in the context of growing EV penetration and uncertain renewable integration.

Disciplines

Computer Sciences | Electrical and Computer Engineering

DOI

10.1016/j.ijepes.2025.110926

Publication Details

International Journal of Electrical Power & Energy Systems

Publisher

Elsevier

License Condition

This work is licensed under a Creative Commons Attribution 4.0 International License.

Recommended Citation

Hilmi Cihan Güldorum, Ayşe Kübra Erenoğlu, İbrahim Şengör, Barry P. Hayes, Ozan Erdinç, Ev charging management in a real-time optimization framework considering operational constraints, International Journal of Electrical Power & Energy Systems, Volume 170, 2025, https://doi.org/10.1016/j.ijepes.2025.110926.