Control-Oriented Modelling and Adaptive Parameter Estimation for Hybrid Wind-Wave Energy Systems

TL;DR

The paper addresses the challenge of designing effective control for a hybrid wind–wave energy system by developing a low-order, six-DOF control-oriented model that captures coupled aero-hydro-mooring dynamics and implementing a novel adaptive parameter estimation law driven by parameter error. The method recasts the dynamics into a linearly parameterized form and uses low-pass filtering to guarantee exponential convergence, avoiding bursting phenomena common in gradient-descent approaches. Validation against a high-fidelity BEM-based AQWA model within an AQWA-Matlab framework across multiple wind/wave scenarios shows high fidelity (MAPE < 5% and R^2 > 0.9) and robust performance, with clear advantages over conventional adaptive laws. The study demonstrates practical potential for real-time control design aimed at increasing power capture density while ensuring safe operation of hybrid wind–wave platforms.

Abstract

Hybrid wind-wave energy system, integrating floating offshore wind turbine and wave energy converters, has received much attention in recent years due to its potential benefit in increasing the power harvest density and reducing the levelized cost of electricity. Apart from the design complexities of the hybrid wind-wave energy systems, their energy conversion efficiency, power output smoothness and their safe operations introduce new challenges for their control system designs. Recent studies show that advanced model-based control strategies have the great potential to significantly improve their overall control performance. However the performance of these advanced control strategies rely on the computationally efficient control-oriented models with sufficient fidelity, which are normally difficult to derive due to the complexity of the hydro-, aero-dynamic effects and the couplings.In most available results, the hybrid wind-wave energy system models are established by using the Boundary Element Method, devoting to understanding the hydrodynamic responses and performance analysis. However, such models are complex and involved relatively heavy computational burden, which cannot be directly used for the advanced model-based control methods that are essential for improving power capture efficiency from implementing in practice. To overcome this issue, this paper proposes a control-oriented model of the hybrid windwave energy system with six degrees of freedom. First, ...

Figures (9)

• Figure 1: (a) DeepCwind, (b) Wavestar and (c) Hybrid wind-wave energy system.
• Figure 2: AQWA-Matlab framework
• Figure 3: Dynamic response comparison between AQWA and proposed model with $60^\circ$ wind-wave direction ($5 \: m/s$ steady wind, regular wave with $1.5\: m\: H_s$ and $10\: s\: T_p$).
• Figure 4: Parameter estimation with adaptation law (\ref{['eq19']}) and gradient descent method (\ref{['eq23']}). (a) Surge. (b) Pitch. (c) Heave.
• Figure 5: Dynamic response comparison between AQWA and proposed model with $30^\circ, 60^\circ$ and $90^\circ$ wind-wave direction ($11.4\: m/s$ turbulent wind, irregular wave with $3.62\: m\: H_s$ and $10.29\: s\: T_p$), (a) $30^\circ$, (b) $60^\circ$, (c) $90^\circ$.