Towards modelling and control strategies for hybrid wind-wave energy converters: Challenges and opportunities

Hybrid wind-wave energy converters (HWWECs) offer a promising renewable energy solution by harnessing both wind and wave resources, supporting the diversification of the global energy mix. Despite their potential, HWWEC development is at an early stage, with key challenges hindering commercial availability. To reach optimal performance, HWWECs must effectively balance wind and wave energy absorption, an inherently complex task that requires accurate (yet tractable) mathematical modelling and the subsequent design of tailored control strategies, capable of handling this trade-off systematically. Aiming to shed light on the state-of-the-art of this crucial problem, this study provides a critical review of current research on modelling and control of HWWECs, focusing on the development of control-oriented dynamical models and their role in control design. Modelling is divided into key macroareas, including, e.g. , aerodynamics, hydrodynamics and mooring systems, common to a large class of HWWEC concepts. Given their non-traditional nature, controllers are prioritised on the wave energy converter side and categorised according to the defined performance objective. Among the key findings, this review highlights significant gaps, including a lack of a unified/generalised modelling framework, inconsistencies among similar devices when deriving control-oriented models, and a lack of development and detailed understanding of the parameterisation and solution of the associated control problem. By identifying these gaps and highlighting clear future directions, this study provides a primer for researchers seeking to enter this emerging field, contributing to accelerating the development of HWWECs and helping establish their role as a key technology in the energy transition. • Overview of potential and challenges of hybrid wind-wave energy converters. • Critical analysis of the modelling frameworks and control strategies for these systems. • Comparison of existing approaches, highlighting strengths and limitations. • Suggestions for future research to accelerate development and commercialisation.