Floating wave energy converters (WECs) operating in the resonance region are strongly affected by non-linearities arising from the interaction between the waves, the WEC motion and the mooring restraints. To compute the restrained WEC motion thus requires a method which readily accounts for these effects. This paper presents a method for coupled mooring analysis using a two-phase Navier-Stokes (VOF-RANS) model and a high-order finite element model of mooring cables. The method is validated against experimental measurements of a cylindrical buoy in regular waves, slack-moored with three catenary mooring cables. There is overall a good agreement between experimental and computational results with respect to buoy motions and mooring forces. Most importantly, the coupled numerical model accurately recreates the strong wave height dependence of the response amplitude operators seen in the experiments.
Hydrogen is believed as a promising energy carrier that contributes to deep decarbonization, especially for the sectors hard to be directly electrified. A grid-connected wind/hydrogen system is a typical configuration for hydrogen production. For such a system, a critical barrier lies in the poor cost-competitiveness of the produced hydrogen. Researchers have found that flexible operation of a wind/hydrogen system is possible thanks to the excellent dynamic properties of electrolysis. This finding implies the system owner can strategically participate in day-ahead power markets to reduce the hydrogen production cost. However, the uncertainties from imperfect prediction of the fluctuating market price and wind power reduce the effectiveness of the offering strategy in the market. In this paper, we proposed a decision-making framework, which is based on data-driven robust chance constrained programming (DRCCP). This framework also includes multi-layer perception neural network (MLPNN) for wind power and spot electricity price prediction. Such a DRCCP-based decision framework (DDF) is then applied to make the day-ahead decision for a wind/hydrogen system. It can effectively handle the uncertainties, manage the risks and reduce the operation cost. The results show that, for the daily operation in the selected 30 days, offering strategy based on the framework reduces the overall operation cost by 24.36%, compared to the strategy based on imperfect prediction. Besides, we elaborate the parameter selections of the DRCCP to reveal the best parameter combination to obtain better optimization performance. The efficacy of the DRCCP method is also highlighted by the comparison with the chance-constrained programming method.
This study proposes a novel tower damping system to enhance the structural performance of the NREL 5 MW semi-submersible wind turbine under operational and extreme load conditions. Environmental load data from the Norwegian MET center was analyzed to characterize the loading conditions for floating offshore wind turbines (FOWT). The probability density spectrum of sea state data was employed to identify operational load conditions. At the same time, the Inverse First-Order Reliability Method (IFORM) was used to derive the 50-year extreme sea state. Perform a fully coupled Aero-Hydro-Servo-Elastic simulation of the FOWT dynamic model with a damping system using OrcaFlex software. The results reveal that: Under operational sea states, the turbine tower-top displacement was reduced by 60–70%, and acceleration by 30–40%, enhancing tower-top stability. Under extreme loads, tower-top acceleration was reduced by 5–7%, and displacement by 6–8%. Cumulative damage assessments indicate a reduction in fatigue damage of up to 72%, with the effective fatigue life of the tower base extended by 136%. The proposed damping system significantly reduces vibration under fatigue and extreme load conditions.
This study proposes a novel tower damping system to enhance the structural performance of the NREL 5 MW semi-submersible wind turbine under operational and extreme load conditions. Environmental load data from the Norwegian MET center was analyzed to characterize the loading conditions for floating offshore wind turbines (FOWT). The probability density spectrum of sea state data was employed to identify operational load conditions. At the same time, the Inverse First-Order Reliability Method (IFORM) was utilized to derive the 50-year extreme sea state. Perform a fully coupled Aero-Hydro-Servo-Elastic simulation of the FOWT dynamic model with a damping system using OrcaFlex software. The results reveal that: Under operational sea states, the turbine tower-top displacement was reduced by 60–70%, and acceleration by 30–40%, enhancing tower-top stability. Under extreme loads, tower-top acceleration was reduced by 5–7%, and displacement by 6–8%. Cumulative damage assessments indicate a reduction in fatigue damage of up to 72%, with the effective fatigue life of the tower base extended by 136%. The proposed damping system significantly reduces vibration under fatigue and extreme load conditions.
With increasing demand for renewable energy resources, the development of alternative concepts is still ongoing. The wave energy sector is still in vast development on the way to contribute to the energy production world wide. The present study presents the development of the Exowave wave energy converter made so far. A numerical model has been established supported by wave flume tests performed at Aalborg University during the first phase of the development. Furthermore, a successful open sea demonstration has been performed on 7 meters of water at Blue Accelerator, Belgium, from which the concept has been proven. As part of the ongoing research, verification of the numerical model will be made through experimental testing in the wave tank of Aalborg University, and an open sea demonstration at 14 meters of water depth will be executed off the coast of Hanstholm, Denmark.
In the current transition of power industry from conventional sources to renewable energy sources, wind power generation is becoming one of the key sources of electrical energy. Although the development of wind power plants (WPPs) has made a significant contribution to addressing the demand for clean and cheap energy, the integration of large-scale WPPs introduces a series of technical challenges to power system operations. These challenges involved control, protection, and adherence to specified power quality standards. Particularly, power quality plays a vital role in utility systems and industries having direct technical and economic impact on both power consumers and suppliers. To tackle such issues, various grid codes have been initiated by regulation authorities. Moreover, different ancillary devices and control approaches have been adopted to comply with the established grid code. This article aims to review the state-of-the-art research and progress, while considering the main challenges related to dynamic performance and power quality enhancement of emerging grid-forming wind power plants. Various topologies of wind energy conversion systems (WECSs) are examined and compared, and their control strategies are investigated. A comprehensive review on power quality and dynamic response issues caused by large-scale wind power integration is presented. Moreover, the evolving grid code requirements for grid-connected WPPs in most leading countries including Denmark, U.K., Australia, Germany, and the USA are analyzed and compared. Furthermore, the improvement approaches proposed in the literature are investigated and classified on different basis and their pros and cons are discussed. A brief discussion on the solutions and future directions is presented. Finally, some conclusive considerations about the overall study are provided.
As more offshore wind energy projects are implemented, the risk of interactions between farms becomes more pronounced. While reduced surface roughness over water enhances airflow stability, it can also extend wake effects on downstream turbines. The study aims to enhance the understanding of wake interactions and efficiency variations based on the distance between neighboring farms. To assess the impact of neighboring farms across different scenarios and features, a methodology is developed to achieve computational optimality using an open-source Python-based library, PyWake, then verified by a well-established CFD software, Meteodyn. Then, the methodology is applied to a Brazilian offshore wind project currently under licensing as a reference point. The results indicate a 1–3% reduction in Annual Energy Production following the current Brazilian regulation for onshore projects of 20 times the blade tip height, as the minimum distance. This reduction translates to an approximate 3% increase in the Levelized Cost of Energy and a nearly 24% decrease in Net Present Value. These findings are crucial for offshore wind energy planning and its sustainable growth, indicating the need to define a minimum distance for the regulatory bodies. This would not only avoid future disputes but also enhance investor confidence.
The wave loads and the resulting motions of floating wave energy converters are traditionally computed using linear radiation–diffraction methods. Yet for certain cases such as survival conditions, phase control and wave energy converters operating in the resonance region, more complete mathematical models such as computational fluid dynamics are preferred and over the last 5 years, computational fluid dynamics has become more frequently used in the wave energy field. However, rigorous estimation of numerical errors, convergence rates and uncertainties associated with computational fluid dynamics simulations have largely been overlooked in the wave energy sector. In this article, we apply formal verification and validation techniques to computational fluid dynamics simulations of a passively controlled point absorber.
The phase control causes the motion response to be highly nonlinear even for almost linear incident waves. First, we show that the computational fluid dynamics simulations have acceptable agreement to experimental data. We then present a verification and validation study focusing on the solution verification covering spatial and temporal discretization, iterative and domain modelling errors. It is shown that the dominating source of errors is, as expected, the spatial discretization, but temporal and iterative errors cannot be neglected. Using hexahedral cells with low aspect ratio and 30 cells per wave height, we obtain results with less than 5% uncertainty in motion response (except for surge) and restraining forces for the buoy without phase control. The amplified nonlinear response due to phase control caused a large increase in numerical uncertainty, illustrating the difficulty to obtain reliable solutions for highly nonlinear responses, and that much denser meshes are required for such cases.
Mooring systems are required to keep floating wave energy converters (WECs) on station. The mooring concept might impact the performance of the WEC, its cost and its integrity. With the aim of clarifying the pros and cons of different mooring designs, we present the results from physical model experiments of three different mooring concepts in regular and irregular waves, including operational and survival conditions. The parameters investigated are the tension in the cables, the motions of the device in the different degrees of freedom and the seabed footprint in each case. We can see that the mooring system affects the performance of the wave energy converter, but the magnitude of the impact depends on the parameter analysed, on the mode of motion studied and on the conditions of the sea. Moreover, different configurations have similar performances in some situations and the choice of one over another might come down to factors such as the type of soil of the seabed, the spacing desired between devices, or environmental impacts. The results of our experiments provide information for a better selection of the mooring system for a wave energy converter when several constraints are taken into account (power production, maximum displacements, extreme tensions, etc).
The following report presents the results of the experimental testing of the Exowave wave energy converter (WEC) performed in September 2023 at the Ocean and Coastal Engineering Laboratory at Aalborg University, Denmark. The model tests are performed based on the current design of the WEC35 Exowave floater as part of the project 250 MW bølgekraft I den danske Nordsø før 2030 – fase 1 supported by the Danish Energy Agency under the Energy Technology Development and Demonstration Program (EUDP) contract number 64022-1062.