Multi-Objective Intelligent Control of Bi-Directional V2X Charging Using NSGA-II in an Integrated Energy Management System

This study presents the development and evaluation of an intelligent control system for a real-time bi-directional Electric Vehicle (EV) charging infrastructure integrated with solar Photovoltaic (PV), Energy Storage Systems (ESS), and the power grid. The proposed system aims to optimize energy flow decisions such as cost minimization, energy efficiency maximization, and prioritization of renewable sources. Two evolutionary optimization techniques are implemented and compared: a traditional single-objective Genetic Algorithm (GA) and the Non-dominated Sorting Genetic Algorithm II (NSGA-II). The GA approach focuses solely on minimizing operational cost, while NSGA-II considers multiple objectives simultaneously, offering a set of optimal trade-off solutions. Real-time switching decisions are formulated based on binary control variables corresponding to relay states in the V2X energy system. Simulation results demonstrate that NSGA-II provides superior flexibility in handling multi-objective trade-offs, achieving improved solar utilization and reduced grid dependency without compromising cost efficiency. The hybrid integration of NSGA-II with rule-based override logic further enhances the system's adaptability to dynamic operating conditions, making it suitable for deployment in smart energy management applications.

@article{Hassan2026,
  title     = {Multi-Objective Intelligent Control of Bi-Directional V2X Charging Using NSGA-II in an Integrated Energy Management System},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {17},
  number    = {3},
  year      = {2026},
  publisher = {The Science and Information Organization},
  author    = {Muhammad Aqmal Bin Abu Hassan and Ezmin Abdullah and Muhammad Umair and Nik Hakimi Nik Ali and Roslina Mohamad and Nabil M. Hidayat},
  doi       = {10.14569/IJACSA.2026.0170323},
  url       = {https://doi.org/10.14569/IJACSA.2026.0170323}
}