Offshore Wind Turbines Research Articles

Coordinated control of single-point moored floating multi-wind turbines under fault events and shutdowns

Abstract The emergence of novel concepts aimed at the reduction of floating offshore wind energy cost is increasingly demanding new control approaches. This is the case of floating offshore multi-wind turbine assets (FOMWT), with two or more full wind turbines placed on the same floating platform. The strong dynamic interaction among the sub-components of such systems requires appropriate coordination of the commands driven by the individual wind turbine controllers. The impact of such coupling may increase depending on the asset confguration, as is the case of single-point distribution of mooring lines, commonly applied to FOMWTs. Among the most demanding situations are those under fault events and shutdowns, which may cause large uncontrolled platform rotation and put the system integrity at risk. To address this, a new coordinated control level, mastering the individual turbine controllers hierarchically, is proposed to govern the whole asset. The control concept proves to be effective under a reduced set of extreme load cases in accordance with standards for a two-wind turbine FOMWT. The simulations are performed with the multi-wind turbine simulation tool MUST, which accounts not only for the interaction among the two turbines and the platform, but also for the communication of the coordinated control and the individual turbine control levels.

Mapping of Artificial Intelligence and Robotics Technologies Applied to Offshore Wind Energy

Mapping of Artificial Intelligence and Robotics Technologies Applied to Offshore Wind Energy

Collocating wind data: A case study on the verification of the CERRA dataset

Abstract Wind resource assessment often relies on reanalysis data or meso-scale models due to the challenges and costs associated with on-site measurement campaigns, especially in offshore locations. While these datasets offer extensive spatial coverage, they often provide the desired parameters on a coarse grid only. The spatial averaging over the grid and the low frequency of the outputs hinders the model’s ability to capture the short-term wind speed variability and events with a time scale of a few minutes to a few dozen of minutes. In this paper we investigate the temporal scales of the wind events resolved by the Copernicus European Regional Re-Analysis (CERRA) dataset, ERA5, and an in-house regional down-scaling of ERA5 using the WRF model by comparing them against measurements. We propose a method to collocate the two sources of wind data (measured and modeled), focusing on the verification of CERRA with respect to first and second-order statistics in the North Sea. The results highlight the superiority of CERRA compared to ERA5 in estimating the wind speed distribution, improving the 95th percentile error from -0.85 to -0.19 ms−1 and the average bias from -0.286 to -0.004 m s−1 across all locations. The wind speed change over one hour is underestimated by both CERRA and ERA5 when collocated with 10-minute measurements at the full hour. However, hourly averaged measurements align well with CERRA’s wind speed variation predictions, while an averaging window of 3.5 hours is needed to align with ERA5’s hourly wind speed changes. The results showed that the synthetic wind speeds exhibit optimal correlation with the measurements when the measurements are averaged over 4.5 to 7 hours, depending on the modeled dataset. This time scale corresponds to a length scale of 160-250 km, assuming a mean wind speed of 10 m s−1, which falls within the meso-scale range. The study contributes to the understanding of model validation in offshore wind energy studies, with the potential to enhance wind resource assessment calculations and improve the results of long-term extrapolations.

An Early-Stage Structural Design of a Semi-Submersible Platform for Floating Offshore Wind Turbines in Chilean Waters

To advance offshore wind energy technologies in South America, this study addresses the early-stage design challenges of a floating support structure for a 5 MW wind turbine. The aim is to develop a robust and efficient floating structure capable of withstanding the diverse forces imposed by the Valdivian environment. Utilizing SolidWorks, a 3D model based on a comprehensive review of semi-submersible structures with three columns is proposed. The structural model is subjected to a rigorous evaluation using the finite element method, with which linear static and buckling analyses are performed in compliance with the Det Norske Veritas (DNV) classification society. The proposed tri-floater platform design shows a 30% weight reduction when compared with other proposed models. The finite element analysis includes an extreme condition of 13 m waves that suggests the adequate performance of the proposed platform in Chilean waters, and offers a conceptual preliminary step for floating support structure designs in Chile.

Study on the Ratio and Model Test of Similar Materials of Heavily Weathered Granite

To study the bearing characteristics of rock-socketed single piles on the southeast coast of Fujian Province, we conducted similar material ratio tests and single pile model tests. Initially, based on the mechanical parameters of strongly weathered granite, 10 groups of similar material samples were prepared using iron concentrate powder, barite powder, and quartz sand as aggregates, with rosin and alcohol as the cementing agents and gypsum as the modulating agent. Through triaxial testing and range and variance analysis, it was determined that the binder concentration has the most significant impact on the material properties. Consequently, Specimen 1 was selected as the simulation material. In the model test, the strongly weathered granite stratum was simulated using the ratio of Specimen 1. A horizontal load was applied using a pulley weight system, and the displacement at the top of the pile was measured with a laser displacement meter, resulting in a horizontal load–displacement curve. The results indicated that the pile foundation remained in an elastic state until a displacement of 2.5 mm. Measurements of the horizontal displacement and bending moment of the pile revealed that the model pile behaves as a flexible pile; the bending moment initially increases along the pile length and then decreases, approaching zero at the pile’s bottom. The vertical load test analyzed the relationship between vertical load and settlement of the single pile, as well as its variation patterns. This study provides an experimental basis for the design of single pile foundations in weathered granite formations on the southeast coast of Fujian Province and aids in optimizing offshore wind power engineering practices.

A multi-task spatio-temporal fusion network for offshore wind power ramp events forecasting

With the accelerated development of offshore wind farms, the impact of Wind Power Ramp Events (WPRE) on power systems has become more pronounced. Accurate prediction of WPRE is essential for mitigating their adverse effects on the grid. However, current studies on offshore WPRE are limited, especially regarding their spatio-temporal correlations and variability across large wind farm clusters. To address this, a novel forecasting approach using a multi-task spatio-temporal fusion network is presented. This method improves WPRE prediction by integrating spatial and temporal data and utilizing multitask learning to characterize ramp features. Firstly, an index system for WPRE characterization is developed, including metrics such as power change rate and duration. Based on this, an X-means classification method for WPRE is established. Secondly, a spatio-temporal encoder combining graph convolutional networks and temporal attention mechanisms has been proposed to model the spatiotemporal dependencies of meteorological changes in offshore wind farms. Finally, a multitask learning framework has been introduced to predict WPRE characteristic indices and occurrence probabilities. This approach enhances feature extraction efficiency through the joint feedback of multiple related tasks, thereby improving prediction accuracy. A case study using data from five offshore wind farms in Eastern China validates the efficacy of the proposed method.

Shear behavior at the interface of rough surfaces and cohesive soils under axial loading

Foundation elements with rough (textured) surfaces mobilize larger interface shear resistance than ones with conventional smooth or random rough surfaces when sheared against soils under monotonic loading. The overall performance of foundation elements such as piles supporting offshore wind turbines, suction caissons supporting tidal energy converters, soil nails, and soil anchors installed in cohesive soils could be enhanced through utilizing rough (textured) surfaces to resist applied static and/or cyclic loading. This paper describes the shear behavior of smooth and rough (textured) surfaces in kaolinite clay and kaolinite clay-sand mixture soils under static and cyclic axial loading. The experimental investigation presented herein consists of a series of interface shear tests performed on 3D printed rough (textured) surfaces and a 3D printed smooth reference surface utilizing the Cyclic Interface Shear Test system. The paper includes a description of the interface testing system components, cohesive soil specimens’ preparation procedure, smooth and rough (textured) surfaces details, testing procedure, and results of static and cyclic tests. Test results indicate that kaolinite clay-sand mixture soil mobilized larger static and post-cyclic interface shear resistance and volume contraction relative to kaolinite clay soil when sheared against the smooth reference surface. When tested against rough (textured) surfaces with variable asperity height, larger shear resistance was mobilized and larger soil dilation greater than that mobilized by the reference untextured surface in both soils. The results also indicate rough (textured) surfaces exhibited a prevalent frictional anisotropy increases with asperity angle and height in cohesive soils, the surfaces mobilized larger shear resistance and volume change in one direction (i.e., against the asperity right-angled side) than the other direction (i.e., along the asperity inclined side).

Multi-objective optimization of non-fossil energy structure in China towards the carbon peaking and carbon neutrality goals

Numerous nations and regions are earnestly dedicated to propelling energy transition. China accounts for 31.78 % of the total global carbon emissions, and China's energy structure holds paramount significance in the broader context of global initiatives. China has officially proposed to achieve the target of carbon peak by 2030 and carbon neutrality by 2060, imposing substantial pressure on the transformation of the energy structure. In this study, we propose a multi-objective optimization model for the non-fossil energy structure, encompassing three primary optimization objectives: maximizing power generation, minimizing economic costs, and reducing CO₂ emissions. The optimization involves determining the proportion of seven key non-fossil energy sources—hydropower, onshore wind, offshore wind, photovoltaic (PV), bioenergy, geothermal, and nuclear power—while adhering to constraints related to power demand, nuclear safety, and other factors. The analysis explores the installed capacity, power generation, power generation costs, and CO₂ emission reductions of non-fossil energy under distinct scenarios in 2025, 2030, and 2060. The findings reveal that by 2030, the optimal share of power generation should be sequenced as onshore wind, hydropower, nuclear power, offshore wind, PV, bioenergy, and geothermal. Subsequently, by 2060, the top three developed power should be onshore wind, nuclear power, and hydropower.

Multi-objective optimal control of a hybrid offshore wind turbine platform integrated with multi-float wave energy converters

Offshore floating wind turbines will play a pivotal role in achieving net-zero emissions. This study explores a hybrid platform combining an offshore floating wind turbine with wave energy converters (WECs) from an active control perspective to mitigate turbine damage risk while maximizing wave energy conversion. Initially, the control-oriented state-space modelling of the hybrid platform and the validation of the time-domain Cummins-type models of different orders are performed by the Eulerian-Lagrangian method with model linearization and downscaling. Then, a multi-objective non-causal optimal controller is introduced, balancing wave energy capture and penalizing the nacelle acceleration. When wave energy capture maximization is set as the control target, the proposed optimal controller can improve energy output by 184% as compared against a well-tuned passive damper across all peak periods tested. However this causes peak hub acceleration to increase marginally beyond the desirable limits of 3–4 m/s2 for wind turbine operation. When hub acceleration is penalized, the multi-objective optimal controller can reduce peak values below limits by between 40% and 61% with trivial loss of wave energy capture.

High-performance insulating materials with high breakdown strength and low permittivity for eco-friendly electrical equipment

High-performance insulating materials are essential for developing lightweight, compact, and green offshore wind power equipment. It has been shown that nanoporous structures can limit the development of electron avalanche, leading to a significant increase in the breakdown electric strength of dielectrics. Hence, we fabricated a polysiloxane nanoporous biopolymer insulating material (PNBIM) with the nanoporous structure that presents exceptionally high electrically insulating properties. Under a CO2 atmosphere, the breakdown electric strength of the PNBIM was remarkably improved, exhibiting 761.01 % enhancement relative to that of the pure gas gap. Moreover, the PNBIM demonstrates excellent dielectric performance, with a low dielectric constant (1.63) and dielectric loss (0.014), as well as high hydrophobicity and excellent thermal stability. The investigations revealed that the nanopores inside the material can effectively suppress gas discharge and improve the breakdown electric strength. This study widens our understanding of conventional insulating materials and provides a promising approach for exploring high-performance insulating materials provide valuable insights.

Control Structures for Combined H2/Electricity from Offshore Wind Turbines

Wind energy proves to be a highly favourable choice for electricity generation due to its clean and renewable nature, and is playing a significant role in reducing global greenhouse gas emissions. Offshore wind turbine systems have gained widespread popularity as they can capitalise on elevated and consistent wind speeds surpassing those found in onshore locations, resulting in increased energy efficiency. Furthermore, offshore wind power possesses the potential to emerge as a significant electricity source for the production of green hydrogen. As water electrolysis technology for hydrogen production continues to advance, utilizing offshore wind power for hydrogen generation is becoming more economically viable and practical. Offshore wind power with higher wind speeds in combination with efficient control structures presents an attractive option for electricity generation and hydrogen co-production. This paper aims to present and evaluate four different production structures for combined H2/energy generation from offshore wind turbines. Previous research studies in this area often overlook control structures and lack information on power converter operations. In contrast, this article studies control structures that enable proper functionality and ensure adequate interoperability, enhancing the reliability of renewable energy integration. Each structure, including both wind turbines and electrolyser, is described in detail, along with the corresponding controllers. Simulation results are presented for each structure and controller to demonstrate their effective operation.

LiDAR-Based Unmanned Aerial Vehicle Offshore Wind Blade Inspection and Modeling

The deployment of offshore wind turbines (WTs) has emerged as a pivotal strategy in the transition to renewable energy, offering significant potential for clean electricity generation. However, these structures’ operation and maintenance (O&M) present unique challenges due to their remote locations and harsh marine environments. For these reasons, it is fundamental to promote the development of autonomous solutions to monitor the health condition of the construction parts, preventing structural damage and accidents. This paper explores the application of Unmanned Aerial Vehicles (UAVs) in the inspection and maintenance of offshore wind turbines, introducing a new strategy for autonomous wind turbine inspection and a simulation environment for testing and training autonomous inspection techniques under a more realistic offshore scenario. Instead of relying on visual information to detect the WT parts during the inspection, this method proposes a three-dimensional (3D) light detection and ranging (LiDAR) method that estimates the wind turbine pose (position, orientation, and blade configuration) and autonomously controls the UAV for a close inspection maneuver. The first tests were carried out mainly in a simulation framework, combining different WT poses, including different orientations, blade positions, and wind turbine movements, and finally, a mixed reality test, where a real vehicle performed a full inspection of a virtual wind turbine.

Grid Integration of Offshore Wind Energy: A Review on Fault Ride Through Techniques for MMC-HVDC Systems

Over the past few decades, wind energy has expanded to become a widespread, clean, and sustainable energy source. However, integrating offshore wind energy with the onshore AC grids presents many stability and control challenges that hinder the reliability and resilience of AC grids, particularly during faults. To address this issue, current grid codes require offshore wind farms (OWFs) to remain connected during and after faults. This requirement is challenging because, depending on the fault location and power flow direction, DC link over- or under-voltage can occur, potentially leading to the shutdown of converter stations. Therefore, this necessitates the proper understanding of key technical concepts associated with the integration of OWFs. To help fill the gap, this article performs an in-depth investigation of existing alternating current fault ride through (ACFRT) techniques of modular multilevel converter-based high-voltage direct current (MMC-HVDC) for OWFs. These techniques include the use of AC/DC choppers, flywheel energy storage devices (FESDs), power reduction strategies for OWFs, and energy optimization of the MMC. This article covers both scenarios of onshore and offshore AC faults. Given the importance of wind turbines (WTs) in transforming wind energy into mechanical energy, this article also presents an overview of four WT topologies. In addition, this article explores the advanced converter topologies employed in HVDC systems to transform three-phase AC voltages to DC voltages and vice versa at each terminal of the DC link. Finally, this article explores the key stability and control concepts, such as small signal stability and large disturbance stability, followed by future research trends in the development of converter topologies for HVDC transmission such as hybrid HVDC systems, which combine current source converters (CSCs) and voltage source converters (VSCs) and diode rectifier-based HVDC (DR-HVDC) systems.

Offshore wind farms interfacing using HVAC-HVDC schemes: A review

Offshore wind farms (OWF) have emerged as a pivotal component in the transition towards renewable energy, offering substantial potential for reducing carbon emissions and enhancing energy security. Integration these offshore installations into the existing power grid present opportunities and challenges, particularly in terms of efficiency, stability, and cost-effectiveness. This review explores the interfacing of OWF with the power grid through High Voltage Alternating Current (HVAC) and High Voltage Direct Current (HVDC) schemes. This research offers a thorough examination of the latest technologies, and comparing the benefits and drawbacks of HVAC and HVDC systems for offshore wind applications. The review delves into various aspects, including technological advancements, economic considerations, and environmental impacts of HVAC and HVDC technologies. The review also addresses recent developments and contrasting viewpoints in the field, highlighting innovations and ongoing debates related to integrating OWF. By synthesizing recent studies and industry reports, this paper offers a balanced overview of the strengths and weaknesses associated with HVAC and HVDC schemes. It identifies critical areas for future research and provides recommendations for optimizing offshore wind farm integration. This review seeks to enhance understanding of current technologies and support decision-making in the development and deployment of offshore wind energy infrastructure.

The Method of the Natural Frequency of the Offshore Wind Turbine System Considering Pile–Soil Interaction

Accurately and efficiently evaluating the influence of pile–soil interaction on the overall natural frequency of wind turbines is one of the difficulties in current offshore wind power design. To improve the structural safety and reliability of the offshore wind turbine (OWT) systems, a new closed-form solution method of the overall natural frequency of OWTs considering pile–soil interactions with highly effective calculations is established. In this method, Hamilton’s principle and the equivalent coupled spring model (ECS model) were firstly combined. In Hamilton’s theory, the Timoshenko beam assumption and continuum element theory considering the three-dimensional displacement field of soil were used to simulate the large-diameter monopile–soil interaction under lateral load in multilayer soil. Case studies were used to validate the proposed method’s correctness and efficiency. The results show that when compared with the data of 13 offshore wind projects reported in existing research papers, the difference between the overall natural frequency calculated by the proposed method and that reported in this study is within ±10%. This calculation method achieves the goal of convenient, fast and accurate prediction of the overall natural frequency of offshore wind systems.

Bayesian finite element model inversion of offshore wind turbine structures for joint parameter-load estimation

Operating in harsh and unsteady marine environment, offshore wind turbine (OWT) structures are exposed to unpredictable wind and wave loads. Identifying the structural loads and their effects on the OWTs allow for predicting the remaining fatigue life of these structures and improving the structural design procedure. In this paper, a finite element (FE) model inversion method is presented to estimate the unknown loads and model parameters of OWTs using sparse measurement data. A realistic FE model of an OWT structure with jacket substructure is created in the open-source simulation platform, OpenSees. A Bayesian inference framework is presented to integrate the measured data with the FE model to estimate unknown wind loads and mass of rotor-nacelle assembly. To evaluate the performance of this data assimilation framework, the effect of sensor type, number of sensors, and modeling errors on the estimation accuracy of wind loads and model parameters are investigated through different case studies where synthetic data are used as measurements. The results of this study are important to guide instrumentation of new OWT structures, and to understand the potential limitations and sources of error in the real-world application of this data assimilation framework for joint model parameter and input load estimation.

Investigation of the large-diameter monopiles response under flow-controlled loading

The mechanical behavior of monopile support systems for offshore wind turbines under current-induced loads was investigated through numerical simulations. Using the Large Eddy turbulence model, the fluid-structure coupling was analyzed in both unidirectional and bidirectional directions. In the unidirectional coupling, the pressure and velocity profiles of the fluid around the pile were determined. While in the bidirectional coupling, the force distribution, pile displacement, and moment distribution were obtained, along with the current-induced load transmitted from the pile to the soil. The coupling analysis revealed that the fluid flow around the pile exhibited cyclic loading behavior due to the interaction between the fluid and the pile, effectively resulting in an oscillating pile within a steady flow. Additionally, the pile’s stress distribution remained within the tensile yield limit of the steel, indicating a stable state in the fluid-pile model within the given flow conditions. Furthermore, the soil reaction forces obtained from the fluid-pile-soil coupling model validated the accuracy of the current-induced load calculations. This study introduces a novel approach that considers the fluid-pile-soil coupling, offering valuable insights for pile foundation design. The findings of this research have significant engineering implications and practical value, providing a robust foundation for future offshore wind turbine installations.

Going digital: challenges in monitoring marine megafauna when comparing results from visual and digital aerial surveys

Since the first plans to develop offshore wind farms (OWFs), concerns have been raised about the impacts on marine megafauna. Today, it is required to assess these impacts over the whole lifecycle of the OWF. Before construction, initial assessments are often conducted by visual surveys, but subsequent monitoring over the lifecycle of the OWF has to be digital due to safety requirements, leading to challenges in data comparability. The aim of this study was to attempt to establish generalizable intercalibration factors for this transition between visual and digital monitoring methods. To this end, intercalibration surveys were conducted at five different sites and at different times of the year within a site, using both visual monitoring at low-altitude and digital monitoring at both low and high altitudes. We tested the potential for intercalibration of the results based on the ratio of abundance estimated from data collected by the different methods. We explored factors such as the species under study and site-specific conditions that may influence intercalibration. We computed more than 100 intercalibration factors and found that, on average, abundance estimates from digital methods were higher than those from visual methods and that flight altitude for digital monitoring did not significantly influence abundance estimates. Aside from divergent abundance estimates depending on monitoring method, the findings also revealed significant heterogeneity, only one-third of which was explained by contextual factors such as taxonomy or the sea conditions. This outcome presents a pessimistic outlook on the prospect for the intercalibration of results between an initial assessment carried out with visual observations and subsequent monitoring with digital methods after OWF construction and until decommissioning. The high heterogeneity prevents seamless transferability of intercalibration factors and highlights the importance of local context.

Design and Implementation of Modular Multi-Level Converter Based HVDC System for Grid Connection

This paper examines Modular Multilevel Converters (MMC) for harnessing power from offshore wind farms. MMCs use many simple Voltage Source Converter (VSC) submodules, enabling high-voltage and high-power applications. They offer faster response times and lower harmonic distortion than traditional two-level VSCs. The paper addresses modelling challenges due to numerous switching devices and discusses the development of Cascaded Two-Level (CTL) converters, which improve output voltage quality. Overall, the study highlights advancements in MMC technology that enhance HVDC transmission capabilities.

Fault diagnosis of floating offshore wind turbine based on bidirectional long short-term memory networks with sliding window

Owing to its ability to harvest more power in deeper waters than other types of offshore wind turbines, the floating offshore wind turbine (FOWT) has attracted significant interest from both academics and industry. However, deterioration in system performance and unscheduled shutdowns will significantly increase operation and maintenance costs. To avoid system damage and ensure operation safety, there is a great demand for developing FOWT fault diagnosis to detect and identify faults as early as feasible. Due to the enormous complexity of FOWT including dynamics and nonlinearity, effective FOWT fault diagnosis poses a significant challenge. This paper develops a novel FOWT fault diagnosis method using bidirectional long short-term memory (BiLSTM) with sliding window. Firstly, the dynamics are embedded by stacking time-dependent measurements using the sliding window technique. Then, the augmented data is fed into a BiLSTM network to exploit the nonlinearity of FOWT. Consequently, a softmax classifier is used for fault diagnosis. A high-fidelity 10 MW spar FOWT benchmark based on the NREL Fatigue, Aerodynamics, Structures, and Turbulence (FAST) model is used to validate the capability and effectiveness of the proposed method. Experimental results show that the proposed method outperforms other related methods in diagnosing critical faults in FOWTs under various operating conditions.