Offshore floating photovoltaics (OFPVs) emerge as a promising solution to overcome land constraints associated with inland renewable energy deployment. However, as OFPVs are still a developing technology, several performance-related uncertainties persist. The reduction in energy yield caused by wave-induced losses (WIL) is one such critical uncertainty that needs to be understood, quantified and minimised. To address this need, this work introduces a physics-based modelling framework that couples validated hydrodynamic simulations with opto-electrical analysis to accurately estimate WIL. An extensive sensitivity analysis is then carried out, performing over 100 simulations by systematically varying both design and environmental parameters. The results show that WIL ranges between 1%–30% on an hourly basis and exhibits a nonlinear dependence on both parameter groups. The resulting dataset is then used to develop S [Figure presented] IFT 1.0 - a surrogate model capable of predicting WIL across a wide range of design and operating conditions, achieving an average absolute RMSE of 3% relative to the physics-based model. The insights from S [Figure presented] IFT 1.0 are finally used to provide practical measures that minimise WIL at a system design level. Overall, this work provides a complete pathway to model, quantify, predict, and minimise WIL, promoting confident and scalable OFPV deployment.

The uncertainty surrounding land availability for renewable energy deployment is a growing concern, creating a strong need for alternative solutions. In recent years, offshore floating photovoltaic (OFPV) systems have shown great promise in meeting global energy demands without competing for land resources. With ambitious targets like 3 GW in The Netherlands by 2030 and global projections exceeding 20 GW, OFPVs are emerging as a key solution at this critical juncture in energy transition. The significance of this technology is also reflected in the 95% increase in research outputs over the past five years. Despite this growth, insights remain scattered, with limited understanding of both the technology and performance. This review fills this gap by providing a comprehensive overview of OFPV systems, addressing both technical and performance aspects. Specifically, the objectives are to: provide detailed information about technology readiness levels, real-world deployments, and a new classification matrix to categorize different OFPV designs; identify key processes like dynamic motion, cooling, optical changes, and long-term degradation that impact energy yield (EY); and quantify the impact of each process on EY based on reported data. The findings reveal that dynamic motion (-0.4% to -15%) and long-term degradation (-2% to -20%) generally reduce EY, while cooling (-4% to +20%) and optical effects (-40% to +5%) can enhance or reduce EY depending on operating conditions. While these insights are crucial, several challenges remain, with the most pressing being the need to standardize measurement and modeling techniques for EY prediction to propel OFPVs towards large-scale commercialization.