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Adaptive ANFIS-based MPPT for PV-powered green ships with high gain SEPIC converter Jegadeeswari, G.; Govindaraju, Rohini; Balakumar, D.; Lakshmi, D.; Marisargunam, S.; Batumalay, M.; Kirubadurai, B.
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 4: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v16.i4.pp2768-2779

Abstract

To align with global climate goals, the International Maritime Organization (IMO) has enforced strict measures to reduce greenhouse gas emissions from the shipping industry by promoting energy efficiency and cleaner propulsion methods. Ship engines remain major contributors to environmental pollution due to their dependence on fossil fuels and inefficient propulsion systems, highlighting the need for clean and sustainable alternatives. This study aims to design a renewable energy-based marine power system that effectively stores and utilizes solar energy, improving overall efficiency and reducing emissions for process innovation. A hybrid setup was developed using photovoltaic (PV) panels, batteries, and a bidirectional DC-DC converter to enable flexible power flow during both charging and discharging cycles. An adaptive neuro-fuzzy inference system (ANFIS)-based maximum power point tracking (MPPT) algorithm was employed alongside a SEPIC converter to enhance energy extraction from the PV system under dynamic conditions. The integrated system achieved a power extraction efficiency of 97.12%, confirming the effectiveness of the ANFIS-based MPPT strategy and showcasing the viability of intelligent renewable energy solutions in maritime applications.