Offshore Wind Turbines Research Articles

Vibration analysis of a partially submerged structure using the DIC technique

The continuous expansion of offshore wind turbine sites has been garnering increasing attention, particularly in countries where available land is limited. Nevertheless, efficiently allocating resources for the maintenance and repair of offshore wind turbines presents a formidable challenge. This challenge is compounded by the complex and often unpredictable weather conditions, as well as various business-related issues specific to the offshore environment. To tackle these challenges, one effective solution is to implement vibration analysis through the use of digital image correlation (DIC) methods. This approach has a well-established theoretic background dating back to approximately 2008 and has demonstrated its effectiveness in the realm of structural health monitoring for large structures like bridges and towers. Relevant information on the upper structure of the wind turbines has been obtained using numerical models in our previous work. Changes in the structural feature frequencies of wind turbines are the primary focus in vibration analysis. However, changes in feature frequencies can occur for various reasons, and relying solely on frequency shifts can make it challenging to pinpoint the precise areas of damage within wind turbine structures, especially without the benefit of long-term observations. In this study, the DIC method is employed on scaled cylindrical models to gain insights into the frequency variations stemming from the erosion of non-cohesive soils beneath offshore wind turbine foundations. Changes in modal curvature within the upper structure of the wind turbine will also be analyzed. This additional investigation will enable a clear differentiation between defects in the upper structure and frequency shifts resulting from erosion or problems with the underwater foundation.

Unveiling Future Offshore Wind Potential: A Multi-Criteria Framework for Sustainable Development

Climate change poses a critical threat to the environment and human societies, prompting a shift towards clean energy sources. Among these sources, offshore wind energy emerged as a promising alternative, due to its consistent and strong wind resource availability, coupled with matured technology. However, offshore wind energy being susceptible to the climate change, the efficiency, reliability, and financial viability of the offshore wind farms is location specific. Therefore, the present study introduces a novel framework for identifying suitable regions for offshore wind farm development by considering future projections under the various Shared Socioeconomic Pathway (SSP) scenarios. A weighted multi-model ensemble (MMEwt) created using nine Coupled Model Intercomparison Project Phase 6 (CMIP6) climate models was considered for the analysis. The suitability of a location is evaluated considering richness, stability of the resource, risk, and economic factors. CRiteria Importance Through Intercriteria Correlation (CRITIC) multi-criteria technique is used to evaluate the prominence of each factor Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) technique is used to determine the suitability of each grid within the study area and their hierarchy. Findings of this study showed that the north-western and southern regions within the study area are relatively plausible compared to other regions. The proposed methodology built on the theoretical framework of multi-criteria techniques can be extended to other regions and determine the suitability map of plausible wind regions over the specified area for future time periods.

Assessing the Feasibility of Climate Policies of Japan, Latvia and Lithuania to Reach the Targets of the Paris Agreement

The study compares the most recent developments in energy policies of Japan, Lithuania and Latvia as a way to mitigate climate change. Latvia, Lithuania and Japan have all pledged to reach net zero by 2050 but face significant challenges, namely the dependence on energy imports in the form of fossil fuels, as they keep dominating the final energy supply. All three countries have a goal to sharply reduce this dependence, with Lithuania and Latvia even striving to become net energy exporters by focusing almost entirely on renewable energy. Japan, on the other hand, also aim to boost a renewable energy share, yet focuses more on the diversification of imported energy sources. The study attempts to discuss the differing approaches in climate change mitigation in Japan as compared to Latvia and Lithuania. The ambition of each country is estimated by Intended Nationally Determined Contributions (INDCs), the roadmap to reduce the emissions in different sectors as enshrined in the climate strategy of each country, and the penetration of the renewable energy sector, estimating the scope of the ambition and implementation gaps compared to the goals set by the Paris Agreement. The study also estimates the impact of external impacts, namely the COVID-19 pandemic and the Russian invasion of Ukraine in shaping climate change policies. Therefore, this study offers a comprehensive outlook on what needs to be achieved so that all three countries could be role models to follow in the climate policy. All three countries could collaborate on solar power, off-shore wind power, and hydrogen technologies. There have already been joint projects between Japan and the EU on advanced biofuels and the new generation of concentrator photovoltaics. However, there are significant differences regarding the role of ammonia and hydrogen production in the Climate change policy strategies of the three countries. Some contributing sectors are left behind and the current climate change strategies, even if properly implemented, may not be 2°C-compatible, let alone 1.5°C-compatible. The policies look even direr for a fair share target, and the implementation gap generally remains wide for the 2024-2030 period.

GREENER IS CHEAPER: AN EXAMPLE FROM OFFSHORE WIND FARMS

Abstract Offshore wind farms (OWF) are now in operation and increasingly under construction as scalable, sustainable energy sources. In fact OWFs are currently the cheapest form of new energy projects in Europe. The levelized cost of energy (LCOE) for OWF has fallen drastically due to decades of innovation facilitated by both taxpayer and private sector funding. This emerging industry is experiencing massive worldwide growth with the potential to accelerate the decarbonization of regional and the global economy as well as bring a reliable source of green hydrogen into commercial use, all with minimal disruption to ecosystems and impacts on biodiversity. This paper provides a historical perspective of wind energy harnessing and shows that wind turbines are the oldest, largest and one of the smartest machines. We also highlight the potential of offshore wind energy to provide new solutions to (a) meet clean energy demand for a growing world population, (b) improve energy security of nations through other downstream technologies such as production and storage of dispatchable fuel (such as green hydrogen battery storage) and (c) through supply complementarity improve resilience of nuclear power plants in high-seismic-activity areas. Offshore wind industry can also become a gold standard for future industries, and the paper provides insights into the new green economics and jobs and factories for the future. We show that environment-friendly regulation is driving innovations even further to enhance sustainability of OWF. Examples include material recycling, landfill ban on blade disposal and ecofriendly low-noise offshore construction to protect biodiversity.

Modelling error chains in offshore wind energy systems: Examining the interplay of human performance and machine state

A dynamic model of the mutual interdependency between humans and machines in offshore wind farms (OWFs) is developed in this paper. The model emphasises the importance of having early indicators to dynamically moderate human behaviour and the need to account for both human and physical subsystems and their mutual interactions for optimal asset management practices. This work simulates three distinct scenarios for: (1) examining the interconnectedness of technical and human dynamics and their implications on error and failure; (2) assessing the impact of production loss on human and organisational behaviour; and (3) evaluating human error probability as an early warning sign of production loss. The findings suggest that adopting an appropriate maintenance culture and considering human error likelihood and production rate in decision-making leads to optimising production and mitigating the risks associated with human error. The research highlights the significance of comprehending the complex interactions between human and machine factors in the operation and maintenance (O&M) of offshore wind turbines (OWTs). The proposed dynamic model helps organisations identify the underlying causes of errors, allowing them to improve their maintenance strategies.

Quantification and mitigation of bottom-trawling impacts on sedimentary organic carbon stocks in the North Sea

Abstract. The depletion of sedimentary organic carbon stocks by the use of bottom-contacting fishing gear and the potential climate impacts resulting from remineralization of the organic carbon to CO2 have recently been heavily debated. An issue that has remained unaddressed thus far regards the fate of organic carbon resuspended into the water column following disturbance by fishing gear. To resolve this, a 3D-coupled numerical ocean sediment macrobenthos model is used in this study to quantify the impacts of bottom trawling on organic carbon and macrobenthos stocks in North Sea sediments. Using available information on vessel activity, gear components, and sediment type, we generate daily time series of trawling impacts and simulate 6 years of trawling activity in the model, as well as four management scenarios in which trawling effort is redistributed from areas inside to areas outside of trawling closure zones. North Sea sediments contained 552.2±192.4 kt less organic carbon and 13.6±2.6 % less macrobenthos biomass in the trawled simulations than in the untrawled simulations by the end of each year. The organic carbon loss is equivalent to aqueous emissions of 2.0±0.7 Mt CO2 each year, roughly half of which is likely to accumulate in the atmosphere on multi-decadal timescales. The impacts were elevated in years with higher levels of trawling pressure and vice versa. Results showed high spatial variability, with a high loss of organic carbon due to trawling in some areas, while organic carbon content increased in nearby untrawled areas following transport and redeposition. The area most strongly impacted was the heavily trawled and carbon-rich Skagerrak. Simulated trawling closures in planned offshore wind farms (OWFs) and outside of core fishing grounds (CFGs) had negligible effects on net sedimentary organic carbon, while closures in marine protected areas (MPAs) had a moderately positive impact. The largest positive impact arose for trawling closures in carbon protection zones (CPZs), which were defined as areas where organic carbon is both plentiful and labile and thereby most vulnerable to disturbance. In that scenario, the net impacts of trawling on organic carbon and macrobenthos biomass were reduced by 29 % and 54 %, respectively. These results demonstrate that carbon protection and habitat protection can be combined without requiring a reduction in net fishing effort.

New Adaptive Super-Twisting Extended-State Observer-Based Sliding Mode Scheme with Application to FOWT Pitch Control

This paper details the transformation of the velocity or position-tracking problem of a class of uncertain systems using finite time stability control for first-order uncertain systems. A new composite extended-state observer sliding mode (ESOSM) scheme is proposed, which includes an adaptive super-twisting-like ESO and an adaptive super-twisting controller. The adaptive super-twisting controller is implemented through a barrier function-based second-order sliding mode algorithm. To further reduce control chattering and improve control performance, the adaptive super-twisting-like ESO, which employs high-order terms in the super-twisting algorithm to accelerate convergence, is designed to observe the lumped uncertainty in real time. The advantages of the proposed scheme are verified by a numerical example and application with regard to floating offshore wind turbine (FOWT) pitch control. Compared with proportional integral (PI) and adaptive super-twisting sliding mode (ASTSM) schemes, better results are obtained in velocity tracking and fatigue load suppression. For the FOWT pitch control application, the platform roll, pitch, and yaw are decreased by 3%, 2%, and 4%, respectively, compared to the PI scheme at an average turbulent wind speed of 17 m/s and turbulence intensity of 17.27%.

Inter-array cabling optimization in offshore wind power plants, a new reliability indicator for radial grids

The inter-array grid relates to a significant share of the investments into an offshore wind power plant (OWPP). Optimizing the cable connections regarding costs and reliability is a mathematically complex task due to the high variety of possible wind and component (wind turbine or cable) failure scenarios. This paper presents a novel mixed integer linear programming approach to support investment decisions into OWPPs by trading off cabling purchase and installation costs with power capacity risk (PCR), which is defined as a length-weighed cumulative power flow summation that reflects the consequences of cable failures. Then, quasi-random Monte Carlo simulations assess the optimized collection grids (CGs) to quantify their levelized cost of energy (LCOE). To construct relevant case studies, this work investigates the real OWPPs Ormonde, Horns Rev 1, Thanet, and London Array, which contain 30, 80, 100, and 175 wind turbines. The results reveal Pearson correlation coefficients around 0.99 between the proposed PCR and the expected energy not supplied. Furthermore, this paper’s findings indicate that minimum-cost CGs do not necessarily present the lowest LCOE.

Probabilistic Prediction of Floating Offshore Wind Turbine Platform Motions via Uncertainty Quantification and Information Integration

The accurate prediction of short-term platform motions in a real environment is crucial for the safe design, operation, and maintenance of floating offshore wind turbines (FOWTs). Numerical simulations of motions are typically associated with high uncertainties due to abstracted theoretical models, empirical parameters, initial environment parameters, etc. Therefore, it is necessary to integrate other sources of information associated with less uncertainty, e.g., monitoring data, for accurate predictions. In this paper, we propose a probabilistic prediction based on the Bayesian approach that logically integrates motion monitoring data with simulated motion predictions of FOWTs, considering uncertainties in the environment model, structural properties, motion prediction method, monitoring data, etc. The approach consists of constructing a prior probability density function (PDF) of a random variable (which characterizes the largest value of the initial motion response) via numerical simulations and a likelihood function based on platform motion monitoring data and deriving a posterior PDF of the random variable by Bayesian updating. Then, posterior distributions of short-term extreme motion responses are derived using the posterior PDF of the random variable, representing lower uncertainty and improved accuracy. A Metropolis–Hastings algorithm is adopted to obtain PDFs of complex probability distributions. The effectiveness of the approach is demonstrated on a real FOWT platform in Scotland. The proposed probabilistic prediction approach results in posterior distributions of short-term extreme platform motions associated with less uncertainty and higher accuracy, which is attributed to integrating prior knowledge with monitoring data.

A fault ride-through strategy for accurate energy optimization of offshore wind VSC[sbnd]HVDC system without improved fault ride-through strategy of wind turbines

The transmission of offshore wind power through High Voltage Direct Current (HVDC) systems is an important way to utilization of offshore renewable energy. However, onshore AC grid faults can make it difficult to transmit the energy from offshore wind farms, resulting in HVDC system overvoltages. Existing solutions to this problem mainly include adding DC or AC energy-dissipation devices, adding communication systems, and improving the fault ride-through(FRT) strategy of wind turbines, which have issues with economics or reliability. Based on this, this paper proposes a device-free, communication-free FRT strategy, and the fault ride-through strategy of wind turbines does not need improvement. The exchange of active power between the AC side and DC side of the onshore MMC is calculated under grid-following and grid-forming control strategy. The reference value of DC voltage and offshore MMC capacitance energy are proposed at different control stages. Especially, the dynamically calculated offshore AC voltage reference values have been theoretically provided. This approach ensures that the HVDC system avoids over-voltage and effectively stores more energy. The effectiveness and correctness of the proposed scheme were verified through simulation on the RTDS platFform. This paper is of great significance to promote the development of offshore renewable energy and ensure the safe operation of offshore wind HVDC systems.

Techno-economic and environmental analysis for the application of renewable energy sources in seaports.

Ports have an indisputable effect on the decarbonization of urban areas, helping to minimize air and environmental pollution and achieve sustainable development. In this instance, it is crucial to do research that can advance our understanding of how to increase ports' energy independence by utilizing renewable energy sources. The current study aims to study the environmental benefits and techno-economic challenges of converting three Egyptian ports to eco-friendly green ports by using solar panels, offshore wind turbines, and hydrogen fuel cells. The study shows that from a technical point of view, the required green power to be installed at Alexandria, Port Said, and Suez ports is around 13 MW, 5 MW, and 1.5 MW, respectively. Furthermore, the environmental analysis findings demonstrate that integrating green energy will significantly lower emissions in seaports. It is anticipated that the ports of Alexandria, Port Said, and Suez will achieve annual reductions in carbon dioxide emissions of roughly 68,7 k-tons, 25,8 k-tons, and 6,4 k-tons, respectively. From an economic point of view, the ports could be supplied with green energy from wind turbines for a cost of between 0.115 and 0.125 USD/kWh, while solar panels have a cost range of 0.098 to 0.129 USD/kWh. Additionally, hydrogen fuel cell systems cost about 0.102 USD/kWh.

Techno-economic analysis and comparison of hydrogen supply using offshore wind power sources on the coast of the Korean peninsula

In response to the rapidly changing industry caused by climate change, the Korean government has set a goal of supplying 3 million tons of green hydrogen by 2050. This study aims to determine the leveled cost of hydrogen (LCOH) resulting from floating offshore wind power generation. Initially, we created a numerical model to represent the power curve for large-capacity offshore wind power generation. Additionally, we accounted for the variability in electrolytic cell efficiency by modeling predictions based on real PEMEC parameters using the Aspen Custom Model. The power-hydrogen quantity was then predicted using Aspen Plus. A comparison is also made regarding the transportation of gaseous hydrogen and liquid hydrogen. Gaseous hydrogen is produced through pipelines, while liquid hydrogen is produced using a modified Claude cycle and transported via trucks. Finally, a Techno-economic analysis was conducted, considering the net present value (NPV) derived from capital expenditure (CAPEX) and operating expenditure (OPEX) throughout the entire process. The analysis of LCOH indicated that the most economically viable option for the region with the lowest LCOH per kg is the supply of liquid hydrogen, priced at $11.04/kgH2. Our sensitivity analysis also reveals that while liquid hydrogen is more cost-effective at up to 250 MW, gaseous hydrogen becomes cheaper as its scale exceeds 500 MW because of its greater sensitivity to production volume.

Prediction of Compression Coefficients Based on Machine Learning: A Case of Offshore Wind Farm Site

Prediction of Compression Coefficients Based on Machine Learning: A Case of Offshore Wind Farm Site

Numerical investigation of the coupled aero-hydrodynamic performances of a semi-submersible floating offshore wind turbine with inclined columns

Numerical investigation of the coupled aero-hydrodynamic performances of a semi-submersible floating offshore wind turbine with inclined columns

Optimization of offshore wind farm inspection paths based on K-means-GA.

As global demand for offshore wind energy continues to rise, the imperative to enhance the profitability of wind power projects and reduce their operational costs becomes increasingly urgent. This study proposes an innovative approach to optimize the inspection routes of offshore wind farms, which integrates the K-means clustering algorithm and genetic algorithm (GA). In this paper, the inspection route planning problem is formulated as a multiple traveling salesman problem (mTSP), and the advantages of the K-means clustering algorithm in distance similarity are utilized to effectively group the positions of wind turbines, thereby optimizing the inspection schedule for vessels. Subsequently, by harnessing the powerful optimization capability and robustness of genetic algorithms, further refinement is conducted to search for the optimal inspection routes, aiming to achieve cost reduction objectives. The results of simulation experiments demonstrate the effectiveness of this integrated approach. Compared to traditional genetic algorithms, the inspection route length has been significantly reduced, from 93 kilometers to 79.36 kilometers. Simultaneously, operational costs have also experienced a notable decrease, dropping from 141,500 Chinese Yuan to 125,600 Chinese Yuan.

A Review on the Aero-Hydro Partially Coupled Dynamics of Floating Offshore Wind Turbine

A Review on the Aero-Hydro Partially Coupled Dynamics of Floating Offshore Wind Turbine

Techno-Economic Assessment of a Full-Chain Hydrogen Production by Offshore Wind Power

Offshore wind power stands out as a promising renewable energy source, offering substantial potential for achieving low carbon emissions and enhancing energy security. Despite its potential, the expansion of offshore wind power faces considerable constraints in offshore power transmission. Hydrogen production derived from offshore wind power emerges as an efficient solution to overcome these limitations and effectively transport energy. This study systematically devises diverse hydrogen energy supply chains tailored to the demands of the transportation and chemical industries, meticulously assessing the levelized cost of hydrogen (LCOH). Our findings reveal that the most cost-efficient means of transporting hydrogen to the mainland is through pipelines, particularly when the baseline distance is 50 km and the baseline electricity price is 0.05 USD/kWh. Notably, delivering hydrogen directly to the port via pipelines for chemical industries proves considerably more economical than distributing it to hydrogen refueling stations, with a minimal cost of 3.6 USD/kg. Additionally, we assessed the levelized cost of hydrogen (LCOH) for supply chains that transmit electricity to ports via submarine cables before hydrogen production and subsequent distribution to chemical plants. In comparison to offshore hydrogen production routes, these routes exhibit higher costs and reduced competitiveness. Finally, a sensitivity analysis was undertaken to scrutinize the impact of delivery distance and electricity prices on LCOH. The outcomes underscore the acute sensitivity of LCOH to power prices, highlighting the potential for substantial reductions in hydrogen prices through concerted efforts to lower electricity costs.

Influence of precast microbial reinforcement on lateral responses of monopiles

Microbially Induced Calcium Carbonate Precipitation (MICP) provides an environmentally friendly solution for reinforcing large diameter monopiles for offshore wind turbines (OWTs). This study presents an investigation into the lateral responses of monopiles with precast microbial reinforcement using a low-pH one-phase method. Both static and cyclic loading tests were carried out. The results of static loading tests show that the failure mode of the bio-reinforced monopile was an overall overturn failure. The lateral bearing capacity was increased by 50% and the bending moment was reduced by about 25% with the bio-reinforcement. Further investigation was conducted on the secant stiffness, damping ratio, and accumulated deformation of the bio-reinforced monopile under various cyclic loadings. With the bio-reinforcement, the accumulated deformation under one-way cyclic loading can be reduced by 30%–60%. The influences of cyclic loading parameters and loading sequence on pile stiffness were clarified. The growth ratio of pile stiffness due to bio-reinforcement under one-way loading was between 1.65 and 2.82, and decreased with increasing load amplitude. The ratio was smaller under two-way loading. Three competing factors on pile stiffness were identified: cyclic compaction of the unreinforced sandy soil, weakening of the bio-reinforced soil and soil subsidence around the bio-reinforced soil.

Experimental and Numerical Study of Suspended Inter-Array Cable Configurations for Floating Offshore Wind Farm

The present study evaluates the feasibility of using a fully suspended inter-array cable system for an offshore wind farm. It includes both numerical simulations and a scaled-down experiment, conducted at a 1:49 scale, to validate the numerical results. To achieve the goal, a 15 MW floating offshore wind turbine (FOWT) and a floating offshore substation (FOSS) are involved to simulate the wind farm array. This study incorporates the 50-year return period conditions of the Taiwan Hsinchu offshore area, which has a water depth of about 100 m, to validate the specifications related to the platform motion and mooring line tension. Additionally, an analysis of the tension, curvature, and fatigue damage of the dynamic cable system is discussed in this research. Because a fully suspended cable is a relatively new concept and may be more frequently considered in a deeper water depth area, numerical simulation software Orcina Orcaflex 11.4 has been chosen to conduct the fully coupled simulation, determining whether the fully suspended cable system could effectively withstand the challenges posed by extreme sea conditions. This is due to the reason that a fully suspended cable would occupy a larger space in the ocean, which may pose a risk by influencing the navigation of the vessels. Therefore, the cable laying depth under normal sea states is also discussed to evaluate the influence over vessel navigation. This study also collects the long-term environmental data from the Central Weather Bureau, Taiwan, to calculate the accumulative cable fatigue damage under different sea states. To integrate the results, this research applies fitness parameters to evaluate the feasibility of each cable configuration. Covering the cable performance under extreme sea states and regular operating sea states offers valuable insights for applications in ocean engineering.

A Fundamental Study on Inter-Array Cabling Methods Between Two Floating Offshore Wind Turbines in Shallow Waters

As the transition to renewable energy accelerates, interest in wind farms is heightening. There is a need to safely and economically transport energy produced from Floating Offshore Wind Turbines (FOWTs) to the shore. Consequently, this study conducted an analysis of inter-array cabling methods between two FOWTs in shallow waters, targeting the southwestern sea of South Korea. This research targeted four shapes of dynamic power cables: free hanging catenary, lazy wave shape, suspended and W-configuration type. To verify the economy of the dynamic power cable, the total lengths were compared, and to check safety, curvature and tension were examined. Insights obtained through this study indicate that among the four shapes of dynamic power cables, the lazy wave shape has substantial advantages in shallow waters.