Wave-induced losses in offshore floating PV

Physics-based modelling, sensitivity-driven quantification, surrogate-model prediction, and design-guided mitigation strategies

Journal Article (2026)
Author(s)

Sathya Shanka Vasuki (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Jack Levell (Shell Global Solutions International B.V.)

Teddy Simanjuntak (Shell Global Solutions International B.V.)

Rudi Santbergen (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Olindo Isabella (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Research Group
Photovoltaic Materials and Devices
DOI related publication
https://doi.org/10.1016/j.ecmx.2026.101723 Final published version
More Info
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Publication Year
2026
Language
English
Research Group
Photovoltaic Materials and Devices
Journal title
Energy Conversion and Management: X
Volume number
30
Article number
101723
Downloads counter
33
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Abstract

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.