Optimizing Critical Parameters Influencing Floating Solar PV System Performance Using Response Surface Methodology

Solar PV systems, essential for achieving UN Goal 7 on Affordable and Clean Energy, face land constraints, particularly in densely populated areas, which can be mitigated by deploying floating solar PV. The nascent development stage of floating PV systems poses challenges for performance estimation due to the reliance on suboptimal parameters. To address this gap, the study examines critical parameters specific to floating PV systems and optimizes them using Response Surface Methodology, PVsyst simulations, and real-time monitored data from a 732 kW floating PV system. The performance ratio’s root mean square error was reduced to 3.889 by optimizing the parameters; the optimized values were supported by the particular system type and environmental factors. Building on prior findings, this study remarkably enhanced prediction accuracy of the tool by $\mathbf{4 0. 5 \%}$, challenging the assertion that no tool can accurately model floating PV systems. The methodology presented in this study allows stakeholders to evaluate and optimize critical parameters for such system type, thereby improving performance prediction accuracy and reducing both field measurement costs and time.