A Hybrid FPSO-MPC Energy Management System for Grid-Connected Solar Electric Vehicle Charging Stations | IJORET – Volume 11- Issue 3 | IJORET-V11I3P7
International Journal of Research in Engineering & Technology (IJORET)
Innovative Peer-Reviewed Open Access Journal – ISSN: 2394-4893
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Volume 11 , Issue 3 | Published: May – June 2026
Article Author(s)
Anandu krishnan.S
Abstract
The rapid increase in electric vehicle adoption and renewable energy integration has created significant challenges in power management, charging coordination, and grid stability. This paper proposes a hybrid Fuzzy-Particle Swarm Optimization-Model Predictive Control (FPSO-MPC) framework for solar-assisted EV charging stations. The proposed framework integrates day-ahead scheduling using MPC, real-time uncertainty management using FIS, and offline parameter optimization using PSO.
Keywords
^Conclusion
The proposed hybrid framework significantly improves charging reliability, renewable energy utilization, and economic performance.
References
C. C. Chan, ‘The State of the Art of Electric Vehicles,’ Proceedings of the IEEE.
International Energy Agency (IEA), Global EV Outlook Report.
Mouelhi et al., ‘Optimization of PV Benefits for EV Charging Stations Using Fuzzy Inference Systems,’ Journal of Engineering Research, 2024.
J. Larminie and J. Lowry, Electric Vehicle Technology Explained.
IEEE Transactions on Industrial Electronics – Battery Management Systems.
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