Development and Characterization of HDPE Composite Floating Photovoltaic Structures: Performance Optimization and Reliability under Multi-Environmental Loading

Abstract

The increasing demand for sustainable renewable energy and limited land availability have accelerated the development of Floating Photovoltaic (FPV) systems as an efficient alternative to conventional solar installations. FPV technology provides advantages such as improved land utilization, reduced water evaporation, and enhanced photovoltaic efficiency due to the cooling effect of water. However, existing floating solar structures face major challenges including structural deformation, wind–wave interaction, hydrodynamic instability, mooring failure, UV degradation, and reduced material durability under long-term environmental exposure.
This research proposes an AI-assisted multi-physics framework for the design optimization and structural enhancement of composite floating solar photovoltaic structures using Finite Element Analysis (FEA), Computational Fluid Dynamics (CFD), and Fluid–Structure Interaction (FSI) techniques. A 3D floating platform model is developed and optimized considering buoyancy stability, PV module arrangement, and environmental loading conditions. High-Density Polyethylene (HDPE)-based composite material is selected for float development due to its lightweight nature, corrosion resistance, and excellent durability. Reinforcement materials and UV stabilizing additives are incorporated to improve mechanical strength, impact resistance, and ageing performance. Material characterization is performed through tensile, flexural, impact, hardness, and durability testing.
The proposed methodology integrates mathematical modelling, FEA-based structural evaluation, CFD-based hydrodynamic analysis, and FSI simulation to investigate stress distribution, deformation behaviour, pressure variation, and wave-induced dynamic response. Machine learning models such as ANN, Random Forest, and XGBoost are utilized for performance prediction and optimization using simulation-generated datasets. Results demonstrate improved structural stability, reduced deformation, enhanced safety factor, optimized hydrodynamic behaviour, and better energy performance compared with conventional floating structures.
The study concludes that the integration of composite materials, multi-physics simulation, and artificial intelligence provides an effective approach for developing reliable, durable, and energy-efficient next-generation floating photovoltaic systems. The proposed framework supports future implementation of intelligent FPV platforms with digital twin monitoring and predictive maintenance capabilities.