MW Offshore Wind Research Articles

Techno-financial analysis of 100 % renewable electricity for the south west region of the UK by 2050

In the UK, the transition to 100 % Renewable Energy Systems is a critical strategy in addressing climate change, aligning with the UK government's 2050 net-zero objective. This study explores the potential for such a transformation within the South West region of the UK by 2050. EnergyPLAN16.2 software was utilised for scenario modelling and the fmincon algorithm in MATLAB for optimisation analysis. The focus was on two scenarios involving hybrid renewable energy systems incorporating onshore wind, solar, offshore wind, and two energy storage systems which are lithium-ion battery energy storage and hydrogen fuel cell energy storage. The optimisation process entailed two stages: determining renewable energy configurations for cost-efficient coverage of annual electricity demand and computing the minimum energy storage capacity to ensure a constant power supply. The results suggest an optimal configuration of 4,460 MW onshore wind, 9,880 MW solar, 6,982 MW offshore wind, and 2,273,662 MWh of lithium-ion battery energy storage for 100 % hybrid renewable energy systems in the South West region of the UK in 2050. This configuration achieves the lowest annual cost of 3208 M£/year, with a balanced wholesale electricity price ranging from 4.3p/kWh to 6.6p/kWh and a levelized cost of energy of 6.44p/kWh. Furthermore, hydrogen fuel cell storage systems can be another alternative, however, the present study showed it is not economical enough compared to lithium-ion battery storage systems. This research broadens the understanding of hybrid renewable energy systems implementation in large regions, offering valuable insights for sustainable energy planning in the South West region of the UK.

The impact of extreme wind conditions and yaw misalignment on the aeroelastic responses of a parked offshore wind turbine

As global energy demands rise and the urgent need to reduce carbon emissions, offshore wind energy technology has evolved rapidly, becoming a vital component of the world’s energy portfolio. However, offshore wind turbines face new challenges due to complex marine environments. Under extreme conditions such as strong winds and yaw misalignment, parked wind turbines exhibit complex aerodynamic and structural responses that significantly differ from those in normal operating conditions. These responses, crucial to the integrity and safety of wind turbines, demand thorough analysis. This article presents an in-depth aeroelastic analysis of a parked 5 MW offshore wind turbine using a sophisticated and precise numerical model. It explores the impacts of incoming wind speed and yaw misalignment on the aerodynamic loads and structural behaviors of the wind turbine. The findings indicate that gravity plays a significant role in blade structural responses for a parked wind turbine. Additionally, higher wind speeds elevate aerodynamic forces, leading to more pronounced fluctuations in root forces and tip deflections. The increase in wind speed triggers and exacerbates high-frequency edgewise vibrations of the blade, further leading to fluctuations and instability in the loads. The study also reveals that yaw misalignment causes the AOA changes significantly over time, and generates intermittent fluctuations in lift and drag, leading to extra blade vibrations with the maximum amplitude exceeding 10% of the blade length. This research enhances the current understanding of the operational safety of offshore wind turbines, particularly under extreme conditions. It aims to provide valuable insights and guidance for researchers and developers in designing and monitoring the performance of offshore wind turbines, ensuring their resilience and efficiency in challenging environments.

Rapid assessment of seismic performance of large monopile-supported offshore wind turbines under scour

This study focuses on investigating the seismic performance of a reference 15 MW offshore wind turbine (OWT) supported by a large-diameter monopile, under various scour conditions. Fully coupled nonlinear finite element models considering 3D soil continuum for seismic response analysis of monopile-supported OWTs are very complicated and computationally expensive. Therefore, it is important to have good insight on the dynamic behaviour of monopile-supported OWTs subjected to earthquake excitations before performing high-fidelity fully nonlinear 3D simulations, which will not generally be practical in cases considering various seismic loading and scouring scenarios. The purpose of this study is to provide a fast and efficient tool to understand the interaction between the seismic behaviour of emerging large-capacity OWTs when scour erosion affects the dynamic properties of the structure. The dynamic stiffness method (DSM) is applied for the free vibration analysis of the structure. Modal superposition is used to calculate the seismic responses of the OWT by using the exact mode shapes obtained from the dynamic stiffness formulations. The rotor-nacelle-assembly (RNA) is idealized as a lumped mass at the tower top. The tower and monopile are modelled as Timoshenko beam-columns under axial compressive loading. The soil-structure interaction (SSI) is modelled using the Winkler framework, whereby the soil contribution is assumed as elastic to take advantage of the modal superposition method. Two different approaches are considered for the soil stiffness; a constant profile, and a linearly-varying subgrade modulus along the embedded depth of the pile, and both are appraised in this paper. Firstly, natural frequencies obtained from dynamic stiffness formulations are validated using experimental data from literature for the case of controlled dynamic SSI experiments, and for operating OWTs. Additionally, the natural frequency provided by a technical document for the reference 15 MW OWT is compared to the result from the DSM, where a very good agreement is observed. The seismic response time-histories of the OWT model are obtained under different input earthquake conditions, and subsequently verified by comparison with the results of finite element simulations. The effects of different scour scenarios and foundation modelling approaches on the free vibration and seismic responses are subsequently investigated. A parametric analysis is also performed using different soil properties to observe the interaction between the soil stiffness, scour condition, and seismic response. Finally, the influence of the frequency content of seismic records on the dynamic response of the OWT, specifically the tower top acceleration, the mudline rotation, and the mudline stress, is investigated considering various scour scenarios. The specific numerical case study undertaken for a reference 15 MW OWT, which is supported by a large monopile in very dense sand, shows that the seismic responses are very limited and that the elastic soil behaviour assumption is reasonable. Additionally, considering the computational efficiency, the proposed combination of DSM and modal superposition can be used for rapid seismic performance assessment of large diameter monopile-supported OWTs at the preliminary design stage to gain insight to the global dynamic response of the whole vibrating system.

Conceptual design of a prestressed precast UHPC-steel hybrid tower to support a 15 MW offshore wind turbine

Ultra-high-performance-concrete (UHPC) possesses favorable mechanical properties and economy efficiencies and has the potential to be used as the main material to construct tower structures of offshore wind turbines (OWTs). Then the shortages of widely used pure steel OWT towers such as relatively small lateral stiffness, weak fatigue behavior and corrosion resistance can be avoided. In this work, a new type of hybrid tower structure combining a prestressed UHPC tube at the bottom and an upper steel tube is proposed to support a large-size 15 MW OWT. Detailed and carefully refined finite element (FE) analysis by ABAQUS was conducted to explore the dynamic performance of the proposed hybrid tower. The modal properties, dynamic responses, ultimate strength, fatigue strength, and economy performance of the hybrid tower were comprehensively evaluated. It shows that with a similar lateral stiffness but greatly reduced material and maintenance costs compared to a reference steel tower, the hybrid tower has enough ultimate and fatigue strength to resist huge environmental loads caused by extreme winds, waves and earthquakes.

Energy efficiency evaluation of wind turbines based on entropy weight method and stacked autoencoder

Abstract To solve the problems of complex operating conditions of wind turbines and difficult to measure and evaluate energy efficiency, a quantitative evaluation method of energy efficiency of wind turbines based on the entropy weight method (EWM) and stacked automatic encoder (SAE) was proposed. Firstly, based on the Supervisory Control And Data Acquisition (SCADA) data of wind turbines, key evaluation indicators are extracted through preprocessing and feature extraction of wind turbine data. The EWM is used to determine the weights, and deep learning is combined with SAE to comprehensively obtain the energy efficiency value of wind turbines. Subsequently, the quartile method was used to determine the discrimination threshold for inefficient units, and the effectiveness of this method on SCADA data of a 5.5MW offshore wind farm was verified through numerical examples. The results show that this method can evaluate the energy efficiency level of wind turbines in real time and achieve 100% accuracy in identifying inefficient units, providing a reference for the maintenance and technical improvement of wind turbine energy efficiency performance.

Assessing offshore wind plants for energy and green hydrogen production: A case study in the Mostaganem coastal region, Algeria

This study assesses the feasibility and strategic implications of establishing a 500 MW offshore wind farm utilizing fixed wind turbine technology along Algeria’s western coastal economic zone, with a focus on the Mostaganem region. The study recommends integrating 33 Vestas V-235 wind turbines, each boasting a 15 MW capacity to harness offshore wind resources for electricity and green hydrogen production. Utilizing the Wind Atlas Analysis and Application Program (WAsP), offshore wind potential is assessed based on meteorological data from a land-based station, overcoming the lack of in situ sea level measurements. Results show that the proposed wind farm could yield 1361.63 GWh/year of electricity at a cost of 0.89 $/kWh. Additionally, it would produce 28,571 tons of hydrogen at a cost of 2.12 $/kg. This initiative is anticipated to significantly reduce CO2 emissions, by approximately 595,450 tons/year, highlighting the effectiveness of offshore wind resources in promoting sustainable energy production and advancing green hydrogen as a viable energy carrier in this region.

Operation and maintenance cost comparison between 15 MW direct-drive and medium-speed offshore wind turbines

Abstract. Determining offshore wind energy operational expenditures relies on acquiring reliability data, particularly as turbine power ratings increase. The uncertainty surrounding operational costs and optimal drivetrain configurations for larger turbines persists. While previous research has addressed reliability data for 3 MW offshore wind turbines, this study reviews and collates updated failure data for 15 MW turbines, comparing direct-drive and medium-speed configurations. It employs an operation and maintenance (O&M) modelling tool to calculate total operational costs. The study concurs with existing literature, showing that direct-drive turbines have lower operational costs than medium-speed turbines in three case studies. However, the cost and availability differences between configurations are smaller than previously suggested. For 15 MW turbines, the analysis reveals that the cost disparity between direct-drive and medium-speed turbines is significantly smaller than for smaller-rated turbines, with percentages of 1.59 %, 1.58 %, and 5.78 % for the three ScotWind sites selected. Previously, the absolute percentage difference in cost between direct-drive and medium-speed turbines was estimated to be 29.79 %. Sensitivity analyses explore the influence of three factors – failure rates, accessibility limits, and major replacement times – on total operational costs. These analyses demonstrate that medium-speed configurations exhibit more significant cost fluctuations, and the cost gap between configurations is reduced if failure rates are lowered at the same rate for each configuration, accessibility increases, or the major replacement time is reduced for the larger wind turbine components.

Data driven damping separation method for the Mega-offshore wind turbine tower

This study proposes a novel damping separation method based on operating state-measured data collected from a 6.7 MW offshore wind turbine tower to provide various damping ratios caused by different loads. First, the operating frequencies and total damping ratios for various operating states are identified using the dynamic responses under normal operating conditions. Subsequently, the natural and harmonic frequencies caused by the rotation of the blades are distinguished using rotor speed data and the Campbell diagram. Finally, to determine the various damping ratios of different modal orders of offshore wind turbines under multiple load conditions using only actual response data, a new damping equation based on different damping sources is proposed. Filtering strategies for total damping ratios corresponding to different damping sources with varying vibration amplitudes and wind speed thresholds were proposed. The outlier elimination method was introduced to remove error-scattered points, and the average value calculation was used to identify various damping ratios. The actual measured data of a 6.7 MW offshore wind turbine tower was studied, and the results show that the proposed method can effectively separate various damping ratios.

Short-term extreme value prediction for the structural responses of the IEA 15 MW offshore wind turbine under extreme environmental conditions

As offshore wind turbines enter deep seas, large-scale models ranging from 15 MW to 20 MW are becoming the mainstream choice for the future market. The dynamic responses of 15 MW wind turbines under extreme environmental conditions should be considered in the design process. With increasing structure sizes, the mooring systems and tower base structures play essential roles in maintaining position and supporting wind turbines under harsh environmental conditions. Accurate estimation of the extreme mooring loads and dynamic responses at the tower base is crucial, particularly for the ultimate limit state (ULS) analysis. The dynamic responses of the offshore wind turbine are calculated by Open Fast and validated with other numerical tools. For the safety of deep-sea structures, it is necessary to consider the extreme environmental conditions with a 100-year return period, which is beyond the current standards. An environmental contour-based approach is proposed to select the short-term extreme conditions, enabling approximate prediction of the extreme values of the dynamic responses during the preliminary design stage. The Gumbel method and the ACER method are used to predict the short-term extreme dynamic responses. Comparative evaluations against the relevant standards for floating wind turbines are conducted to assess structural safety.

Analysing the cost impact of failure rates for the next generation of offshore wind turbines

AbstractOffshore wind turbines have rapidly scaled up in recent years, with plans to construct turbines up to 22 MW in the next decade. However, the operations and maintenance (O&M) requirements for these ‘next‐generation turbines’ remain largely unknown. In this study, the total O&M costs are calculated, using a bench‐marked O&M model, for a hypothetical 10 MW turbine scenario using two drive train configurations, based on known failure rates of smaller turbines. The O&M costs of the 10 MW turbines are compared with those of existing 3 MW turbines in two case studies: a North Sea wind farm and an East Coast US wind farm. Overall, direct drive 10 MW turbines performed better depending on the site's climate conditions. The study indicated that the two‐stage drive train configuration may be more suitable for the US site than the North Sea, depending on the turbine's failure rate. The US site benefited from increased availability due to more favourable weather windows, resulting in lower lost revenue for the two‐stage configuration despite high transport costs. The study found that the failure rate of 10 MW offshore wind turbines in the North Sea with a two‐stage gearbox can increase by as much as 30% compared to the 3 MW failure rates without increasing direct O&M costs. These findings are crucial for the offshore wind energy industry, particularly for OEMs, developers and maintenance providers, as they provide insights into the required reliability for next generation turbines to reduce O&M costs compared to existing 3 MW turbines.

Design and optimisation of a 20 MW offshore wind turbine blade

In the global pursuit of Net Zero emissions by 2050, wind turbines have become a leading solution. These renewable energy generators offer a trifecta of benefits, significantly reducing CO2 emissions, minimizing environmental impact, and delivering cost-competitive clean power. However, the key to maximizing their potential lies in the aerodynamic design of the turbine blades. By improving the blade performance, researchers and engineers can significantly increase wind energy capture, propelling wind turbines to the forefront of the global transition to a sustainable future. Higher power generating wind turbines are needed to reach the Net Zero target. By upscaling the “DTU 10 MW Reference Wind Turbine”, this research has achieved an aerodynamically stable 20 MW offshore wind turbine blade design. Variable rotation speed and variable pitch angle configurations have been considered to achieve an ideal power curve. The aerodynamic performance has been evaluated and quantified for a length optimised blade design, wherein the power and thrust have been increased by 80.84% and 88.67%, respectively, at a rated wind velocity of 12 m/s.

Virtual sensing via Gaussian Process for bending moment response prediction of an offshore wind turbine using SCADA data

Offshore wind turbines (OWTs) can be equipped with two types of monitoring systems: (1) a Supervisory Control and Data Acquisition (SCADA) system that monitors operational data such as wind speed and power generation, and (2) vibration sensors like accelerometers and strain gauges to track structural dynamics. While strain gauges enable fatigue damage calculations, not all OWTs in a wind farm have these sensors installed. This paper proposes a Gaussian process regression (GPR) strategy to predict the bending moment time-histories of an OWT. The model takes into account various SCADA data such as wind speed, power, and nacelle acceleration as input and learns to predict the high and low-frequency dynamic response of the system. The strategy is implemented and tested to predict the bending moment response of a 6 MW offshore wind turbine in the fore-aft and side-side directions of the turbine. The accuracy and reliability of the proposed strategy are evaluated and demonstrated considering different operational conditions and multiple hotspot locations along the height of the turbine. The proposed strategy proves to be an efficient virtual sensing strategy and can be easily transferred to other turbines in the same wind farm without the need for widespread installation of strain gauges.

Scaling considerations and optimal control for an offshore wind powered direct air capture system

The optimal design and operation of an offshore wind powered direct air capture (DAC) system is complex owing to the intermittent energy supply and the modularity of the units. A solid amine DAC process involves multiple individual units which undergo periodic loading to capture carbon dioxide (CO2) from ambient air, followed by regeneration to produce pure CO2 for utilisation or sequestration. The modular nature of a solid DAC process is exploited in this study to investigate the optimal design and coordinated operation of multiple DAC units mounted on a single 15 MW offshore wind turbine platform, with battery energy storage for additional short term power buffering. Important design parameters considered include the number of independently controllable units, the cyclic capacity of each unit (proportional to the amount of adsorbent) and the battery capacity and maximum power ratings. The design study results highlighted the diminishing returns to the CO2 capture rate with scaling, with a full design optimisation based upon cost estimations left for future work as the technology matures. It was found the optimal configuration was 14 DAC units, each with a cyclic capacity of 2000 kg CO2 , giving a total annual capture rate of 45 600 ton yr−1 and a wind utilisation factor of 96.6%. Furthermore, it was found that a rules-based control strategy based on high and low loading limits was competitive with a machine learning based controller and outperformed a model predictive control scheme.

Optimization of Battery Application for Wind Energy Storage

The largest disadvantage of wind energy is the lack of exact predictability and its fluctuations, which are causing problems in the power system operation. The consequence is that even though other energy sources can be saved by using wind energy, the short-term power fluctuation has to be secured by a conventional plant. A possible solution can be the storage of wind energy. In this paper battery systems are analyzed as a backup for a 400 MW offshore wind farm with help of special developed calculation models. The goal is to reach small difference between forecasted and actual wind power and to increase the reliabilty of delivered wind energy using battery systems. For the determinations the properties of the battery system are considered and integrated into the calculation model. The overall target is to reduce the reserve energy requirement of the offshore wind farms.

Harmonic Resonance Study for Wind Power Plant

Harmonic resonance is one of an important aspect being considered in a large network such as a wind power plant (WPP). This paper analyses several factors that affect resonance characteristic in a WPP and possible mitigation measures. The first part of the paper provides an analysis of resonances in WPP. Two methods of identifying resonances are performed which are a common impedance scan method and a harmonic resonance modal method for different operating conditions. Several factors that affect resonances including the usage of passive filters as harmonic mitigation in the network are analyzed. A case study of a 400 MW offshore wind power plant is analyzed for the harmonic resonance including with the integration of a passive filter.

Installation Technique and Numerical Simulation of Stress on High-Pile Footings During the Translation of Offshore Booster Stations

The foundation of the offshore substation mainly adopts the structure of a conductor support frame, and the installation of the upper blocks of the offshore substation mainly employs a lifting vessel for hoisting. The “Zhegen Sha 300 MW Offshore Wind Power Project” adopts a high-pile cap foundation for the offshore substation, making use of a translational installation method for the upper blocks. The innovative foundation design and installation scheme together form the basis of this project, which is explored in detail in this paper. Numerical simulations examining the bearing performance of the high-pile cap foundation during the translational process of the upper blocks are also performed, allowing finer insights into the design and construction of offshore wind power projects.

A method to map the levelised cost of hydrogen from offshore wind farms coupled to onshore electrolysers via HVDC

Green hydrogen generated by electrolysis from offshore wind energy can contribute to energy security and decarbonisation by substituting fossil natural gas. The levelised cost of hydrogen (LCOH) is a commonly used metric to evaluate a project’s economic potential. In the near term, one of the potential configurations to produce hydrogen is an offshore wind farm connected to a dedicated onshore electrolyser by a high-voltage direct current (HVDC) transmission system. This study integrates a detailed, location-specific cost model with geospatial tools to create a map of LCOH generated from such plants. A case study that uses the model to map LCOH based on a 540 MW offshore wind farm in Irish waters coupled with onshore electrolysers is also presented. The transmission expenditure ranges from €500 to €800 million, depending on the offshore wind farm location. The obtained LCOH map shows that LCOH values based on wind energy from the offshore area of Ireland are mainly in the range of 5–6 €/kg. Although the locations with the lowest project capital expenditure are near the coasts, some areas with the lowest LCOH are further offshore and in deeper waters due to the superior wind resources in these areas.

Synergy of random balance design method and intelligent optimization technique for model updating of the 4 MW offshore wind turbine benchmark

The technical challenges for model updating of real marine engineering structures include the extraction of modal parameters associated with incomplete measurement information and the correction of a large number of structural parameters. As it is difficult to verify the effectiveness of model updating methods for engineering applications, the representative models have to be adopted in finite element (FE) analysis or lab-scale tests, leading to the incomplete reflection of actual structural performances. Based on these factors, a practical model updating method is developed in this study to make full use of field measurement data from a 4 MW offshore wind turbine for the accurate estimation of structural parameters using the random balance designs-Fourier amplitude sensitivity test (RBD-FAST) strategy and an improved particle swarm optimization (IPSO). Leveraging the measured acceleration signals from offshore wind turbines under the conditions including operation, shutdown, collision and typhoon scenarios, the complex exponential decomposition method is applied to accurately extract the time-varying acceleration components (TVAC) for the construction of the frequency response function (FRF). Following that, RBD-FAST is implemented into IPSO with adaptive inertia weights and asynchronously varying learning factors to enable efficient selection of numerous updated physical parameters, thus improving time cost and computational accuracy. The correctness of the proposed method is verified by a numerical jacket platform model. Furthermore, the 4 MW offshore wind turbine benchmark is developed to assess the feasibility of the proposed model updating method using field measured data from different scenarios. Results show that the synergy of RBD-FAST and IPSO in the proposed method can accurately update parameters and minimize a maximum discrepancy of 0.8970% for the first-three orders of natural frequencies between the benchmark and the updated models in the collision scenario. Summarily, the present work provides a potential technique and practical engineering references for model updating of offshore wind turbines subject to harsh marine environments.

System identification and finite element model updating of a 6 MW offshore wind turbine using vibrational response measurements

Offshore wind energy is playing an increasingly vital role in the clean energy transition around the world, and improved reliability of wind turbine structures is necessary for the long-term success and efficiency of renewable energy. Increased reliability would reduce costs associated with maintenance due to breakages and in turn reduce the levelized cost of energy for offshore wind energy sources. Structural health monitoring methods can be used to predict breakages and extend lifetimes by continuously monitoring instrumented structures. This paper presents system identification and model updating of a 6 MW offshore wind turbine using vibration measurements under varying operational conditions. The turbine is monopile-supported and instrumented with strain gauges and accelerometers at several elevations along the tower and monopile. Effective stiffness of soil springs in the model are updated to match modal-predicted natural frequencies and mode shapes of the first two modes with those identified from measurements at different operating conditions. A deterministic and probabilistic (Bayesian) approach to model updating are compared. The sensitivity of identified modal parameters and the updated model parameters are investigated with respect to operational and environmental conditions such as wind speed. Results show that deterministic model updating can match modal parameters with high accuracy across datasets and environmental conditions. Bayesian model updating results successfully estimate the posterior distribution of updating model parameters with an increasing degree of certainty as more data is used.

Effects of negative shear on loads for a 15 MW offshore wind turbine during low-level jet events

Wind turbines are more often interacting with the negative shear region of a low-level jet due to increasing turbine sizes. However, the effects of negative shear on wind turbines are not sufficiently studied, particularly for offshore wind applications. In this paper, we studied the effects of negative shear on wind turbine loading. This was done using user-defined wind profiles and a model chain. The model chain consisted of a turbulence generator and a wake modelling tool coupled to an aero-hydro-servo-elastic engineering tool. We observed significant variations in the structural loading in the case of low-level jets. We also observed changes in the power spectral density estimates. Additionally, we briefly examined the wake recovery distance.