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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. [ABSTRACT FROM AUTHOR]

The installation of offshore wind farms is rising, driven by the goal of changing the global energy matrix. However, many of their possible impacts are still unknown. Increased noise levels, disruptions to food chains, pollution due to traffic, and impacts on fishing communities and tourism are all potential effects to consider. Marine habitats are essential carbon dioxide sinks. Therefore, losing marine biodiversity due to offshore wind farms can be counterproductive in mitigating climate change. Balancing biodiversity conservation, wind potential, and political interests is challenging. Today, Uruguay has significantly decreased the fossil share in its electricity generation, incorporating electricity generation from wind, solar, and biomass energy alongside hydroelectricity. In line with this, the country's Hydrogen Roadmap highlights green hydrogen as relevant, potentially serving as a fuel for both domestic and export transportation. Combining the country's strong base of wind energy production experience with its sustainable policy, it plans to implement offshore wind farms to produce green hydrogen, making studies of its impacts crucial. This paper reviews the current social and environmental information on the Uruguayan coastal habitat, analyzes onshore wind farms' ecological studies, and examines offshore wind farms' global environmental and social impacts. Finally, it proposes studies for environmental approval of offshore wind farms. [ABSTRACT FROM AUTHOR]

By multivariate econometric analysis of UK offshore wind farms, we demonstrate a life cycle effect of the capacity factor of offshore wind. From the bathtub curve findings in reliability engineering, we would expect a long, flat segment of stable operation in the middle of the life cycle production schedule. Our general findings deviate from the standard curve as it does not have a long segment where production is stable. Production starts falling too early. Lack of stable operation period is harmful to wind farm economics. It indicates immature technology and a potential for improvement. We examine the effect life cycle production schedules have on project economics and compare with a common assumption of a flat production schedule. We find that project profitability (net present value) is very sensitive to the life cycle profile of production. [ABSTRACT FROM AUTHOR]

With the continuous advancement of science and technology, there is a growing global focus on new energy sources. Despite the rapid progress of offshore wind power generation systems, they are still plagued by issues such as significant transmission loss, limited transmission distance, and low-frequency oscillation, which hinder further development. To address these challenges, the Flexible Direct Current Transmission System (VSC-HVDC) has emerged as a widely studied solution. The integration of energy storage power stations presents new opportunities for enhancing offshore wind power transmission systems. These power stations not only serve as energy buffer pools to reduce transmission loss but also improve transmission efficiency through intelligent regulation and control, effectively mitigating low-frequency oscillation. This article introduces an optimization control parameter design method based on sensitivity analysis to enhance the stability of MTDC based on MMC. It outlines the topology structure of the offshore VSC-HVDC system, covering the main circuit and control system. Additionally, the article delves into the derivation of the small signal stability model of the system and investigates the selection of control parameters based on the eigenvalue objective function. Lastly, it analyzes the impact of the control system on the stability of the wind power flexible direct output converter station, highlighting the significant influence of control system parameters on the small signal stability of MTDC systems based on MMC. The MMC parameter selection strategy proposed in this paper is shown to effectively enhance system stability. [ABSTRACT FROM AUTHOR]

To achieve net zero emissions from ships by 2050 and align with the IMO 2023 GHG strategy, the maritime industry must significantly increase zero-emission vessels by 2030. Transitioning to fully electric ferry lines requires enhanced energy supply through renewable energy sources (RES) for complete GHG mitigation and net-zero emissions. This study presents a GIS-based framework for optimally selecting offshore wind farm locations to meet the energy demands of electric ferry operations along coastal routes. The framework involves two stages: designing feasible zero-emission ferry routes between islands or to the mainland and identifying optimal offshore wind farm sites by evaluating technical, spatial, economic, social, and environmental criteria based on national legislation and the academic literature. The aim is to create a flexible framework to support decision making for establishing sustainable electric ferry operations at a regional level, backed by strategically located offshore wind farms. The study applies this framework to the Greek Coastal Shipping Network, focusing on areas with potential for future electrification. The findings can aid policymakers in utilizing spatial decision support systems (SDSS) to enhance efficient transportation and develop sustainable island communities. [ABSTRACT FROM AUTHOR]

Abstract Offshore wind farms (OWFs) play a crucial role in producing renewable energy in modern electrical power systems. However, to ensure that these facilities operate smoothly, they require robust control systems. As a result, this paper employed the newly developed Walrus Optimization algorithm (WaOA) to optimize the design parameters of fractional-order proportional-integral-derivative (FOPID) controllers in the power electronic interface circuits of the studied wind energy conversion system (WECS). In contrast to conventional optimization techniques like GA and PSO, the suggested approach proves more effective. The paper validates the WaOA application in optimizing FOPID controllers within a WECS comprising two, onshore and offshore, VSC stations at the two ends of an HVDC transmission system connecting OWFs to the mainland. The study shows that the WaOA outperforms GA and PSO, improving system stability and enabling quick recovery after disturbances. The study carried out using MATLAB/Simulink highlights the significance of newly recently introduced optimization techniques to ensure efficient and reliable operation of offshore wind energy systems, thereby expediting the transition to sustainable energy sources.

Offshore wind farms are becoming an increasingly common feature in the marine environment as a renewable energy source. There is a growing body of evidence on the effects of wind farms on the seabed and its organisms. However, an important and understudied aspect of site development is the interaction of turbine foundations on the surrounding marine environment. Structures exert significant disturbance on tides, waves and currents; these are visible as optically-distinct, elongate wakes at the sea surface with elevated suspended particulate matter. Despite this, there is uncertainty on the mechanisms that lead to the visible manifestation of wakes at turbine foundations, primarily due to a lack of direct measurements. Here, in situ measurements along with a 15- year time series of satellite images of the Thanet offshore wind farm, located within the Thames Estuary, were used to investigate the formation of visible monopile wakes, and the effects these have on the surrounding water column. We show the optically distinct wakes are near-constant at Thanet; visible in >90% of all satellite images, yet no regional change in sea surface turbidity could be attributed to wind farm construction or operation. Monopile wake in situ water samples and acoustic Doppler current profiler (ADCP) backscatter measurements demonstrated colour change related to elevated sea surface sediment concentration. However, averaged water column measurements of suspended sediment within wakes, and upstream of monopiles, remained consistent. These measurements demonstrate that sediment was redistributed towards surface waters, rather than additional sediment becoming suspended in the wake. ADCP velocity measurements supported a mechanism of sediment lofting towards the surface, with enhanced vertically upwards flow recorded in wakes. [ABSTRACT FROM AUTHOR]

This study introduces a novel multi-channel predictive deconvolution method enhanced by Shearlet-based sparse regularization, aimed at improving the accuracy and stability of subsurface seismic imaging, particularly in offshore wind farm site assessments. Traditional multi-channel predictive deconvolution techniques often struggle with noise interference, limiting their effectiveness. By integrating Shearlet transform into the multi-channel predictive framework, our approach leverages its directional and multiscale properties to enhance sparsity and directionality in seismic data representation. Tests on both synthetic and field data demonstrate that our method not only provides more accurate seismic images but also shows significant resilience to noise, compared to conventional methods. These findings suggest that the proposed technique can substantially improve geological feature identification and has great potential for enhancing the efficiency of seabed surveys in marine renewable energy development. [ABSTRACT FROM AUTHOR]

The global energy demand is increasing due to climate changes and carbon usages. Accumulating evidences showed energy sources using offshore wind from the sea can be added to increase our consumption capacity in long term. In addition, building offshore wind farms can also be environmentally advantageous compared to onshore farms. The assessment of wind energy resources is crucial for the site selection of wind farms. Currently, short-term wind forecast models have been developed to predict the wind power generation. However, methods are needed to improve the forecasting accuracy for ever-changing weather data. So, we try to use deep learning methods to predict long-term wind energy for identifying potential offshore wind farms. The experimental results indicate that PredRNN++ prediction model designed from the spatiotemporal perspective is feasible to evaluate long-term wind energy resources and has better performance than traditional LSTM. [ABSTRACT FROM AUTHOR]

Constructing offshore wind turbines on artificial islands is considered a viable option, but negative skin friction (NSF) is a significant adverse factor that cannot be ignored. The NSF adversely affects the bearing capacity of pile foundations. Currently, design methods for studying the impact of NSF group effects mainly rely on empirical approaches. Moreover, existing experimental studies do not simulate the NSF experienced by offshore wind turbine pile groups on artificial islands. In order to further explore the impact of pile group effects on NSF experienced by offshore wind turbine pile foundations on artificial islands, this study conducted indoor model tests on single piles and 3 × 3 rectangular pile groups in sandy soil under uniformly distributed loading on surrounding soil. The experiment measured the settlement of piles at various positions within single piles and rectangular pile groups, as well as the settlement of the soil surrounding the piles and the NSF. Through calculations, the experiment determined the neutral points and NSF group effect coefficients for each pile. The results indicate that densely spaced pile groups are advantageous in reducing settlement of the surrounding soil, thereby mitigating the adverse effects of NSF. Due to the influence of pile group effects, different positions within the group experience varying degrees of NSF. Consequently, in practical engineering applications, settlement of both the pile groups and the surrounding soil should be calculated separately. Furthermore, design considerations for the uplift forces and neutral points of piles at different positions within the pile group should adhere to distinct standards. [ABSTRACT FROM AUTHOR]

Offshore wind farms (OWFs) play a crucial role in producing renewable energy in modern electrical power systems. However, to ensure that these facilities operate smoothly, they require robust control systems. As a result, this paper employed the newly developed Walrus Optimization algorithm (WaOA) to optimize the design parameters of fractional-order proportional-integral-derivative (FOPID) controllers in the power electronic interface circuits of the studied wind energy conversion system (WECS). In contrast to conventional optimization techniques like GA and PSO, the suggested approach proves more effective. The paper validates the WaOA application in optimizing FOPID controllers within a WECS comprising two, onshore and offshore, VSC stations at the two ends of an HVDC transmission system connecting OWFs to the mainland. The study shows that the WaOA outperforms GA and PSO, improving system stability and enabling quick recovery after disturbances. The study carried out using MATLAB/Simulink highlights the significance of newly recently introduced optimization techniques to ensure efficient and reliable operation of offshore wind energy systems, thereby expediting the transition to sustainable energy sources. [ABSTRACT FROM AUTHOR]

The development of offshore wind farms is an important step toward increasing the share of green energy in Poland's energy mix, offering promising prospects for the energy industry. However, in addition to numerous benefits, such investments also carry potential risks for the marine environment, including the risk of spills of hazardous substances such as gear oils, hydraulic oils, and lubricants. This paper analyses the potential impact of oil spills from offshore wind farms on the marine ecosystems of the Baltic Sea, taking into account hydrometeorological factors, particularly protected areas (such as Natura 2000 sites) and the intensity of ship traffic in the area of the planned farms. Simulations of spill scenarios are also presented to assess the potential extent of pollution and its impact on the environment. This paper emphasises the importance of advanced monitoring and safety systems in minimising the risk of accidents and responding quickly to possible incidents. The development of offshore wind farms in Poland presents itself as a key element in a sustainable energy development strategy, combining advanced technology with environmental concerns. [ABSTRACT FROM AUTHOR]

The continued technical and economic development of offshore wind farms needs to match their sustainable siting transparently and fairly. Aiming to assess existing methodologies widely used in the field of OWFs spatial planning, as well as to identify the proposed enhancements for the improvement of such methods, this study examines 80 peer-reviewed papers over the past eight years. The analysis encompasses articles from 34 scientific journals, with a notable concentration in the journals Renewable Energy, Renewable and Sustainable Energy Reviews, and Energies, and it sheds light on geographical distribution, journal classification, funding sources, and the various methodological approaches. Most of the studies were conducted in Turkey, China, and Greece; half of the surveyed papers utilize multi-criteria decision-making approaches, predominantly addressing bottom-fixed technologies for offshore wind farms, which currently dominate the field. The 80 papers are categorized into five methodological domains: Marine Spatial Planning, Feasibility Analysis, Probabilistic Methods, Meteorological Data, and Multi-Criteria Decision Making. One hundred and seventy criteria were identified and condensed into a final set of 41 critical criteria. This article provided an overview of the site selection process and the most crucial findings and recommendations. [ABSTRACT FROM AUTHOR]

Fatigue damage can lead to failures of structural systems. To reduce the failure risk and enhance the reliability of structural systems, inspection and maintenance interventions are required, and it is important to develop an efficient inspection strategy. This study, for the first time, develops a system-level reliability growth model to establish efficient inspection planning. System-level reliability growth is defined as an increase in the percentage of the system reliability index with and without inspection. The probabilistic S-N approach is used to obtain the reliability index without inspection. Moreover, advanced risk analysis and Bayesian inference techniques are used to obtain the reliability index with inspection. The optimal inspection planning is obtained by maximizing system-level reliability growth. This model is applied to an offshore wind farm. The results show that inspection efficiency can be improved by increasing the number of repair objects in response to a 'detection' inspection outcome, changing the inspection object for each inspection, and increasing the inspection quality. The maximum system-level reliability growth gained from one additional inspection decreases as the number of inspections increases. This study quantifies the inspection efficiency of offshore wind farms by explicit system-level reliability growth computation, offering valuable insights for promoting sustainable energy solutions. [ABSTRACT FROM AUTHOR]

Offshore wind farms are growing in complexity and size, expanding deeper into maritime environments to capture stronger and steadier wind energy. Like other domains in the energy sector, the wind energy domain is continuing to digitalize its systems by embracing Industry 4.0 technologies such as the Industrial Internet of Things (IIoT), virtualization, and edge computing to monitor and manage its critical infrastructure remotely. Adopting these technologies creates dynamic, scalable, and cost-effective data-acquisition systems. At the heart of these data-acquisition systems is a communication network that facilitates data transfer between communicating nodes. Given the challenges of configuring, managing, and troubleshooting large-scale communication networks, this review paper explores the adoption of the state-of-the-art software-defined networking (SDN) and network function virtualization (NFV) technologies in the design of next-generation offshore wind farm IIoT–Edge communication networks. While SDN and NFV technologies present a promising solution to address the challenges of these large-scale communication networks, this paper discusses the SDN/NFV-related performance, security, reliability, and scalability concerns, highlighting current mitigation strategies. Building on these mitigation strategies, the concept of resilience (that is, the ability to recover from component failures, attacks, and service interruptions) is given special attention. The paper highlights the self-X (self-configuring, self-healing, and self-optimizing) approaches that build resilience in the software-defined IIoT–Edge communication network architectures. These resilience approaches enable the network to autonomously adjust its configuration, self-repair during stochastic failures, and optimize performance in response to changing conditions. The paper concludes that resilient software-defined IIoT–Edge communication networks will play a big role in guaranteeing seamless next-generation offshore wind farm operations by facilitating critical, latency-sensitive data transfers. [ABSTRACT FROM AUTHOR]

The traditional power prediction methods cannot fully take into account the differences and similarities between units. In the face of the complex and changeable sea climate, the strong coupling effect of atmospheric circulation, ocean current movement, and wave fluctuation, the characteristics of wind processes under different incoming currents and different weather are very different, and the spatio-temporal correlation law of offshore wind processes is highly complex, which leads to traditional power prediction not being able to accurately predict the short-term power of offshore wind farms. Therefore, aiming at the characteristics and complexity of offshore wind power, this paper proposes an innovative short-term power prediction method for offshore wind farms based on a Gaussian mixture model (GMM). This method considers the correlation between units according to the characteristics of the measured data of units, and it divides units with high correlation into a category. The Bayesian information criterion (BIC) and contour coefficient method (SC) were used to obtain the optimal number of groups. The average intra-group correlation coefficient (AICC) was used to evaluate the reliability of measurements for the same quantized feature to select the representative units for each classification. Practical examples show that the short-term power prediction accuracy of the model after unit classification is 2.12% and 1.1% higher than that without group processing, and the mean square error and average absolute error of the short-term power prediction accuracy are reduced, respectively, which provides a basis for the optimization of prediction accuracy and economic operation of offshore wind farms. [ABSTRACT FROM AUTHOR]

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.

With the continuous advancement of science and technology, there is a growing global focus on new energy sources. Despite the rapid progress of offshore wind power generation systems, they are still plagued by issues such as significant transmission loss, limited transmission distance, and low-frequency oscillation, which hinder further development. To address these challenges, the Flexible Direct Current Transmission System (VSC-HVDC) has emerged as a widely studied solution. The integration of energy storage power stations presents new opportunities for enhancing offshore wind power transmission systems. These power stations not only serve as energy buffer pools to reduce transmission loss but also improve transmission efficiency through intelligent regulation and control, effectively mitigating low-frequency oscillation. This article introduces an optimization control parameter design method based on sensitivity analysis to enhance the stability of MTDC based on MMC. It outlines the topology structure of the offshore VSC-HVDC system, covering the main circuit and control system. Additionally, the article delves into the derivation of the small signal stability model of the system and investigates the selection of control parameters based on the eigenvalue objective function. Lastly, it analyzes the impact of the control system on the stability of the wind power flexible direct output converter station, highlighting the significant influence of control system parameters on the small signal stability of MTDC systems based on MMC. The MMC parameter selection strategy proposed in this paper is shown to effectively enhance system stability.

Abstract To enhance the resilience of transmission systems with offshore wind farms before the advent of typhoons, a proactive unit commitment scheme is proposed. A novel scenario tree is proposed to quantify the uncertain impacts of typhoons on offshore wind farms, transmission lines, and system states, where the inertia support from offshore wind farms and random system state are in‐cooperated. The frequency security constraint is captured by a multi‐variative piece‐wise linear function, where the frequency nadir are simulated under varying inertia and disturbance combinations. The unit commitment problem is formulated as a two‐stage stochastic optimisation problem with nonlinear recourse. This problem is solved by a multi‐cuts Benders decomposition algorithm with finite iteration convergence property. Simulations are conducted on a modified IEEE‐RTS 79 test system with offshore wind farms. Results verify the effectiveness of the proposed model regarding the load shedding and frequency nadir enhancement.

The exploitation of renewable energy resources is an effective option to respond to climate change challenges. Wind energy can be exploited more efficiently and effectively than any other renewable energy source. By switching from onshore wind energy projects to offshore, the positive aspects of onshore wind energy remain and, at the same time, no valuable onshore area is occupied, while their efficiency (e.g., capacity factor) is increased. Greece has a rich wind potential and the maritime region of Thrace is one of Greece's maritime regions with the greatest potential for the development of offshore wind energy. The aim of the present paper is to identify the most appropriate sites for the deployment of offshore wind farms in the region of Thrace. The methodology includes (i) the delineation of the study area and the definition of the support structure of the wind turbine, (ii) the identification of seven (7) exclusion and fifteen (15) assessment criteria, (iii) the suitability analysis under five different zoning scenarios (equal weight, environmental, social, techno-economic, and researchers' subjective), and (iv) the micro siting and qualitative assessment of the most suitable sites based on energy, environmental, social, and economic criteria. The methodology is based on the combined use of Geographical Information Systems (GISs), specifically ArcGIS Desktop version 10.8.1, wind assessment software tools (WaSPs), specifically WaSP version 12.8, and multi-criteria decision-making methods. The results of the paper illustrate that the optimal suitability area that is proposed for offshore wind farm deployment is located at the easternmost end of the Greek part of the Thracian Sea. The planning and the deployment of offshore wind farm projects should follow a holistic and environmentally driven approach to ensure the integrity of all habitats and species affected. [ABSTRACT FROM AUTHOR]

To enhance the resilience of transmission systems with offshore wind farms before the advent of typhoons, a proactive unit commitment scheme is proposed. A novel scenario tree is proposed to quantify the uncertain impacts of typhoons on offshore wind farms, transmission lines, and system states, where the inertia support from offshore wind farms and random system state are in‐cooperated. The frequency security constraint is captured by a multi‐variative piece‐wise linear function, where the frequency nadir are simulated under varying inertia and disturbance combinations. The unit commitment problem is formulated as a two‐stage stochastic optimisation problem with nonlinear recourse. This problem is solved by a multi‐cuts Benders decomposition algorithm with finite iteration convergence property. Simulations are conducted on a modified IEEE‐RTS 79 test system with offshore wind farms. Results verify the effectiveness of the proposed model regarding the load shedding and frequency nadir enhancement. [ABSTRACT FROM AUTHOR]

Introduction: Offshore wind energy development (OWED) has been identified as a major contributor to the aspired growth in Norwegian renewable energy production. Spatially explicit vulnerability assessments are necessary to select sites that minimize the harm to biodiversity, including seabird populations. Distributional data of seabirds in remote areas are scarce, and to identify vulnerable areas, species, and seasons it is necessary to combine data sets and knowledge from different sources. Methods: In this study, we combined seabird tracking data, data from dedicated coastal and seabird at-sea surveys, and presence-only data from citizen science databases to develop habitat suitability maps for 55 seabird species in four seasons throughout the Norwegian exclusive economic zone; in total 1 million km2 in the Northeast Atlantic. The habitat suitability maps were combined with species-specific vulnerability indicators to yield maps of seabird vulnerability to offshore wind farms (OWFs). The resulting map product can be used to identify the relative vulnerability of areas prospected for OWED with respect to seabird collision and habitat displacement. More detailed assessments can be done by splitting the spatial indicators into seasonal and species-specific components. Results and discussion: Associated with higher diversity of seabirds near the coast, the cumulative vulnerability indicator showed a strong declining gradient from the coast to offshore waters while the differences in vulnerability between ocean areas and seasons were negligible. Although the present map product represents the best currently available knowledge, the indicators are associated with complex uncertainties related to known and unknown sampling biases. The indicators should therefore be used cautiously, they should be updated regularly as more data become available, and we recommend that more detailed environmental impact assessments based on dedicated seabird surveys, tracking of birds from potentially affected populations and population viability analyses are conducted in areas ultimately selected for OWED. [ABSTRACT FROM AUTHOR]

The coordinated optimization of maintenance and generation schedules of multiple offshore wind farms (OWFs) bring great benefits in reducing the maintenance and operation cost of OWF cluster. Firstly, a two-stage coordinated risk-averse distributionally robust optimization (CRDRO) model for maintenance and generation schedules of wind turbines (WTs) in OWF cluster is proposed. This model takes into account uncertainties related to the prediction errors in WTs’ maximum available active power outputs, the travel time of maintenance vessels, and the high operational cost risks associated with these uncertainties. A feasible route generating algorithm is designed to obtain all feasible maintenance combinations for WTs and the corresponding routes of maintenance vessels for the CRDRO model. The risk-averse term, which is a weighted sum of expected operation costs and GlueVaR value, is used to measure the tail risk of the worst probability distribution. To solve the two-stage CRDRO model, the risk-averse term is simplified into the form of expected value calculation, which can be further transformed into the tractable form by using the strong duality theorem. Finally, the two-stage CRDRO model is solved by the column-and-constraint generation algorithm, with the nonconvex sub-problem being addressed by the outer approximation algorithm. Case studies on an real-world cluster comprising three OWFs verify the correctness and efficiency of the proposed method, and demonstrate that the CRDRO model enhances the overall economic efficiency and reduces the high operational cost risk under extreme scenarios.

Offshore wind farms are becoming an increasingly common feature in the marine environment as a renewable energy source. There is a growing body of evidence on the effects of wind farms on the seabed and its organisms. However, an important and understudied aspect of site development is the interaction of turbine foundations on the surrounding marine environment. Structures exert significant disturbance on tides, waves and currents; these are visible as optically-distinct, elongate wakes at the sea surface with elevated suspended particulate matter. Despite this, there is uncertainty on the mechanisms that lead to the visible manifestation of wakes at turbine foundations, primarily due to a lack of direct measurements. Here, in situ measurements along with a 15-year time series of satellite images of the Thanet offshore wind farm, located within the Thames Estuary, were used to investigate the formation of visible monopile wakes, and the effects these have on the surrounding water column. We show the optically distinct wakes are near-constant at Thanet; visible in >90% of all satellite images, yet no regional change in sea surface turbidity could be attributed to wind farm construction or operation. Monopile wake in situ water samples and acoustic Doppler current profiler (ADCP) backscatter measurements demonstrated colour change related to elevated sea surface sediment concentration. However, averaged water column measurements of suspended sediment within wakes, and upstream of monopiles, remained consistent. These measurements demonstrate that sediment was redistributed towards surface waters, rather than additional sediment becoming suspended in the wake. ADCP velocity measurements supported a mechanism of sediment lofting towards the surface, with enhanced vertically upwards flow recorded in wakes.

Global warming and environmental issues have necessitated ecofriendly energy generation from offshore wind farms. In this context, submarine cables for offshore wind farms and weak sections of the submarine cables inside the J-tube, which transmit power to offshore substations from the wind turbine generator, have been especially researched. The temperature profiles of the cable inside the J-tube of the offshore wind farm are categorized into three sections: section 1 is the high-temperature region exposed to the air. Section 2 is the temperature-change region, where the cable is repeatedly exposed to the air owing to the rising and falling seawater. Section 3 is the-low temperature region because of the cooling effect of the seafloor. We developed an accelerated aging system for submarine cables and used it to evaluate and analyze the aging characteristics of the submarine cables inside the J-tube. This study presents the different temperature profiles of the three sections of a submarine cable inside a J-tube by applying thermal, electrical, and water stress to the test sample using the developed aging system. The experimental results show that the precision of the accelerated aging system was ±1% for 1 cycle. After aging over 60 cycles, the dielectric strength of the insulation in section 2, where the temperature changes were extreme owing to the rising and falling water level, was decreased by 9% when compared with that before aging. Therefore, section 2 is considered the weak section of the J-tube and requires priority monitoring and diagnosis during cable operation.

Offshore wind power generation equipped with conventional grid following controls challenges the power system stability by reducing the inertia of the grid and weakening the AC offshore grid. To overcome this vulnerability a promising solution could be equipping the wind turbines with grid-forming (GFM) control schemes. Many methodologies have been presented in the literature for GFM inverters. In spite of this, their applications for WTGs have not been thoroughly explored. This paper presents the study of fault handling capability of wind turbines with several grid-forming control strategies. In this context, four different control schemes i.e. Visynch, P/f droop, Q/f droop and conventional grid following control are considered. The performance of these control strategies is assessed and compared during a three-phase symmetrical fault on the point of common coupling of an offshore wind farm. A case study which consists of two wind turbines connected to the main converter of an offshore substation equipped with grid-forming control is also considered. The results indicate that, during faults, each of the four control strategies (Visynch, P/f droop, Q/f droop, and Gfol) effectively limits the current and restores normal operation. A significant advantage of Q/F droop control is its reduced sensitivity to variations in system and fault parameters, adjustable frequency response, and independence from existing Phase-Locked Loops (PLLs). On the other hand, the P/f droop control provides greater voltage support during faults due to its voltage controllers. However, post-fault oscillations result from the stiff voltage controller. Visynch control, on the other hand, shows a lower margin of stability. The advantages and weaknesses of each control scheme is revealed using the simulation results.

The expanding use of wind farms as a source of renewable energy can impact bird populations due to collisions and other factors. Globally, seabirds are one of the avian taxonomic groups most threatened by anthropogenic disturbance; adequately assessing the potential impact of off-shore wind farms (OWFs) is important for developing strategies to avoid or minimize harm to their populations. We estimated avoidance rates of OWFs--the degree to which birds show reduced utilization of OWF areas--by Sandwich Terns (Thalasseus sandvicensis) at 2 breeding colonies in western Europe: Scolt Head (United Kingdom) and De Putten (the Netherlands). The foraging ranges of birds from each colony overlapped with multiple OWFs. We modeled GPS tracking data using integrated step selection functions (iSSFs) to estimate the relative selection of habitats at the scale of time between successive GPS relocations--in our case, 10 min, in which Sandwich Terns traveled ~2 km on average. Besides the effects of OWFs and the direct surroundings of OWFs, iSSFs considered distance from the colony and habitat characteristics (water depth and sediment grain size) as well as movement characteristics. Macro-avoidance rates, where 1 means complete avoidance, were estimated at 0.54 (95% CI: 0.35, 0.7) for birds originating from Scolt Head and 0.41 (95% CI: 0.21, 0.56) for those from De Putten. Estimates for individual OWFs also indicated avoidance but were associated with considerable uncertainty. Our results were inconclusive with regard to the behavioral response to the areas directly surrounding OWFs (within 1.5 km); estimates suggested indifference and avoidance, and were associated with large uncertainty. Avoidance rate of OWFs significantly increased with turbine density, suggesting that OWF design may help to reduce the impact of OWFs on Sandwich Terns. The partial avoidance of OWFs by Sandwich Terns implies that the species will experience risks of collision and habitat loss due to OWFs constructed within their foraging ranges. [ABSTRACT FROM AUTHOR]

Scientific monitoring is a fundamental basis of scientific advice. Among others, monitoring aims at contributing towards understanding the influence of anthropogenic use (e.g. fisheries), the health of a stock and individuum and effectiveness of management and conservation measures (e.g. MPAs). Monitoring of demersal and benthic fish communities is often based on invasive methods like bottom trawling, however in some cases less invasive methods might be available. The need for developing alternative and less invasive monitoring methods is supported by an increasing number of Marine Protected Areas and Windfarms where traditional methods such as trawls cannot be deployed due to conservational or technical and safety reasons. To support the development of new monitoring concepts, we conducted a literature review to identify limits and opportunities of methods that are already available. Furthermore, we present a fit-for purpose guide that can help identifying the appropriate method for individual purposes. We defined eight different methods which were analyzed using four different criteria and listed their advantages and disadvantages. We further apply this guide to monitoring in Marine Protected Areas in the Baltic Sea as a case study, indicating that besides traditional bottom trawling, alternative and less invasive methods could be sufficient for specific research purposes. We therefore, encourage scientists and managers to consider alternative data collection methods to minimize environmental impact of scientific sampling. However, our results also indicate that most of the methods still need further refinement especially regarding sampling design, standardization of methods and comparability with established survey methods. [ABSTRACT FROM AUTHOR]

The current modified Jensen wake model does not correct both the initial wake radius and the initial wake wind speed, and cannot accurately predict the actual wake wind speed of offshore wind farms. A three-time modified Jensen wake model was proposed based on the second modified Jensen wake model and was verified by wind tunnel experimental data from offshore wind farms. Secondly, considering the full wake and partial wake area, the three-time modified Jensen wake model was applied to the layout optimization of the offshore wind farm. The optimization variables were the coordinates and number of wind turbines and the optimization objective function was the cost of electricity. Then, the wind turbine layout of the offshore wind farm was optimized using salp swarm algorithm. The results show that the layout of the wind farm was more homogeneous used the three-time modified Jensen model than corrected Jensen model. Compared to a full tail flow layout, the cost of electricity is reduced by 2. 16% when a partial tail flow layout is considered. [ABSTRACT FROM AUTHOR]

The offshore wind farm industry has recently experienced significant global growth. This study presents a thorough site investigation and analysis of the cyclic resistance of marine clay for offshore foundation design, using the Shaba wind farm in southern China as a case study. In-situ cone penetrometer (CPTu) tests and borehole sampling are conducted to explore the geotechnical characteristics of the soils. However, the soil conditions are characterized by multiple layers and complex sedimentary components. The classification and mechanical properties, such as water content and cyclic resistances, are compared through CPTu interpretation and laboratory tests. The findings indicated that a single physical indicator cannot determine cyclic resistance. In addition, the well-established method in existing literature proved unsuitable for marine clay. Consequently, multiple regression analysis shows that a linear relationship exist between cyclic resistance and depth-corrected CPTu index [EXP(qE/fs)0.3/H], hence a new evaluation method is developed to predict the cyclic resistance of marine clay based on CPTu data. This research aims to provide more reliable guidance for geotechnical investigations, supporting the rapid expansion of offshore wind farms. [ABSTRACT FROM AUTHOR]

The foundation scouring problem of offshore wind farms endangers the overall structural durability and safety. A numerical simulation study was conducted on the scouring problem of the four-cylinder foundation of an offshore wind turbine. The SST-k棕 turbulence model was used to simulate the flow dynamics, the Exner equation was used to simulate the motion of the water-sediment interface, and the immersed boundary method were used to simulate the coupling effect of water and sediment. The accuracy and feasibility of the calculation method were verified using a single pile scouring example. For the four-cylinder foundation scouring problem of wind turbines, the foundation scouring problem at flow incidence of 0毅and 45毅inflow was studied. The simulation results show that the scour depths can be observed on each of the four-cylinders' foundation, and that the vortex field from the upstream cylinder may cause further scour phenomenon on the downstream cylinder foundation. [ABSTRACT FROM AUTHOR]

In order to harness a greater share of wind energy resources, offshore wind energy projects are venturing into deep-sea locations. In this progression, the issue of grid integration control becomes increasingly challenging. Traditional Model Predictive Control (MPC) has been introduced in offshore wind energy grid integration control due to its merits, such as not requiring modulators, dispensing with decoupling, incorporating constraint handling, and facilitating online optimization. However, it heavily relies on a model and consequently experiences a substantial loss of control effectiveness in the face of system parameter variations. In light of this, this study presents an active-disturbance-rejection-based three-vector sequence model predictive control approach. This method effectively mitigates the influence caused by changes in system parameters, endowing the system with self-disturbance rejection capabilities and enhancing its fault recovery abilities. The method employs self-disturbance control to track voltage reference values and employs the concept of sequence control to eliminate weighting factors in the cost function. Furthermore, it employs three-vector control to achieve error-free operation. The simulation results confirmed that the proposed method effectively minimizes voltage and power transients. It demonstrated superior control effectiveness and shorter response times, enabling the system to rapidly restore to a stable operational state following disturbances. [ABSTRACT FROM AUTHOR]

IntroductionOffshore wind energy development (OWED) has been identified as a major contributor to the aspired growth in Norwegian renewable energy production. Spatially explicit vulnerability assessments are necessary to select sites that minimize the harm to biodiversity, including seabird populations. Distributional data of seabirds in remote areas are scarce, and to identify vulnerable areas, species, and seasons it is necessary to combine data sets and knowledge from different sources.MethodsIn this study, we combined seabird tracking data, data from dedicated coastal and seabird at-sea surveys, and presence-only data from citizen science databases to develop habitat suitability maps for 55 seabird species in four seasons throughout the Norwegian exclusive economic zone; in total 1 million km2 in the Northeast Atlantic. The habitat suitability maps were combined with species-specific vulnerability indicators to yield maps of seabird vulnerability to offshore wind farms (OWFs). The resulting map product can be used to identify the relative vulnerability of areas prospected for OWED with respect to seabird collision and habitat displacement. More detailed assessments can be done by splitting the spatial indicators into seasonal and species-specific components.Results and discussionAssociated with higher diversity of seabirds near the coast, the cumulative vulnerability indicator showed a strong declining gradient from the coast to offshore waters while the differences in vulnerability between ocean areas and seasons were negligible. Although the present map product represents the best currently available knowledge, the indicators are associated with complex uncertainties related to known and unknown sampling biases. The indicators should therefore be used cautiously, they should be updated regularly as more data become available, and we recommend that more detailed environmental impact assessments based on dedicated seabird surveys, tracking of birds from potentially affected populations and population viability analyses are conducted in areas ultimately selected for OWED.

Typhoon is an important factor leading to large-scale off-grid of offshore wind power， which is easy to cause a serious imbalance of supply and demand in the affected power grid， thus affecting the safe and stable operation of the regional power system， especially the coastal power grid with large-scale offshore wind power access. Based on this， this paper first establishes a typhoon mathematical model based on Rankine vortex model for the actual typhoon path. The method to slow down the effect of sudden drop of wind is proposed. Then， taking full account of the operation safety requirements of the receiving end power grid， a collaborative operation strategy of offshore wind farm including energy storage was proposed. Aiming at system safety， stability and operation economy， factors such as air abandonment volume and energy storage regulation capacity were comprehensively considered to optimize the wind abandonment volume of offshore wind power. Finally， a simulation analysis is carried out on the receiving end grid system of offshore wind power with energy storage. The results show that the strategy can minimize the operating cost of offshore wind power farm while ensuring the safety and stability of the receiving end system.

Abstract Power systems are currently experiencing a transition towards decarbonisation through the large‐scale deployment of renewable energy sources. These are gradually replacing conventional thermal power plants which today are the main providers of black start services. Consequently, in case of a total/partial blackout, conventional black‐start resources may not be ready for operation. Offshore wind farms (OWFs), with their large capacity and fast controllers, have potential as innovative black‐start units, thus, the need for a new design for OWFs. Here, challenges and possible solutions in integrating black start services into offshore wind farms will be presented. The first challenge is represented by the self‐start capability. The self‐start unit should be capable of forming the wind farm power island and withstanding transient phenomena due to the equipment energisation. The investigated solution comprises grid‐forming (GFM) converters in the wind farm design, which could be battery energy storage systems (BESSs) to also increase the service availability. The challenges are analysed using simulations on a wind farm, and the proposed solutions are discussed. It can be concluded that a hybrid system comprised of a BESS and an OWF, with GFM control, applying soft‐charging, etc., represents a good proposal to provide black start services by OWFs.

Under the background of marine strategy and clean energy strategy, China has carried out large-scale construction around marine ranching and offshore wind farms and made great achievements. However, the problems such as high project cost, the fragmentation of marine habitats and maritime conflict are becoming increasingly prominent, which have led to the test and exploration of integrated development of offshore wind farms and marine ranching at home and abroad. Based on the analysis of relevant research and test work at home and abroad, suggestions are put forward for the current situation of integrated development of offshore wind and animal husbandry, as well as the difficulties and challenges in economic and policy feasibility, site selection and planning, fish species selection, supporting equipment development, ecological impact assessment (noise, electromagnetic field, base interference, heavy metal migration, etc.), etc.

Constructing offshore wind turbines on artificial islands is considered a viable option, but negative skin friction (NSF) is a significant adverse factor that cannot be ignored. The NSF adversely affects the bearing capacity of pile foundations. Currently, design methods for studying the impact of NSF group effects mainly rely on empirical approaches. Moreover, existing experimental studies do not simulate the NSF experienced by offshore wind turbine pile groups on artificial islands. In order to further explore the impact of pile group effects on NSF experienced by offshore wind turbine pile foundations on artificial islands, this study conducted indoor model tests on single piles and 3 × 3 rectangular pile groups in sandy soil under uniformly distributed loading on surrounding soil. The experiment measured the settlement of piles at various positions within single piles and rectangular pile groups, as well as the settlement of the soil surrounding the piles and the NSF. Through calculations, the experiment determined the neutral points and NSF group effect coefficients for each pile. The results indicate that densely spaced pile groups are advantageous in reducing settlement of the surrounding soil, thereby mitigating the adverse effects of NSF. Due to the influence of pile group effects, different positions within the group experience varying degrees of NSF. Consequently, in practical engineering applications, settlement of both the pile groups and the surrounding soil should be calculated separately. Furthermore, design considerations for the uplift forces and neutral points of piles at different positions within the pile group should adhere to distinct standards.

This study introduces a novel multi-channel predictive deconvolution method enhanced by Shearlet-based sparse regularization, aimed at improving the accuracy and stability of subsurface seismic imaging, particularly in offshore wind farm site assessments. Traditional multi-channel predictive deconvolution techniques often struggle with noise interference, limiting their effectiveness. By integrating Shearlet transform into the multi-channel predictive framework, our approach leverages its directional and multiscale properties to enhance sparsity and directionality in seismic data representation. Tests on both synthetic and field data demonstrate that our method not only provides more accurate seismic images but also shows significant resilience to noise, compared to conventional methods. These findings suggest that the proposed technique can substantially improve geological feature identification and has great potential for enhancing the efficiency of seabed surveys in marine renewable energy development.

The development of offshore wind farms is an important step toward increasing the share of green energy in Poland’s energy mix, offering promising prospects for the energy industry. However, in addition to numerous benefits, such investments also carry potential risks for the marine environment, including the risk of spills of hazardous substances such as gear oils, hydraulic oils, and lubricants. This paper analyses the potential impact of oil spills from offshore wind farms on the marine ecosystems of the Baltic Sea, taking into account hydrometeorological factors, particularly protected areas (such as Natura 2000 sites) and the intensity of ship traffic in the area of the planned farms. Simulations of spill scenarios are also presented to assess the potential extent of pollution and its impact on the environment. This paper emphasises the importance of advanced monitoring and safety systems in minimising the risk of accidents and responding quickly to possible incidents. The development of offshore wind farms in Poland presents itself as a key element in a sustainable energy development strategy, combining advanced technology with environmental concerns.

Fatigue damage can lead to failures of structural systems. To reduce the failure risk and enhance the reliability of structural systems, inspection and maintenance interventions are required, and it is important to develop an efficient inspection strategy. This study, for the first time, develops a system-level reliability growth model to establish efficient inspection planning. System-level reliability growth is defined as an increase in the percentage of the system reliability index with and without inspection. The probabilistic S-N approach is used to obtain the reliability index without inspection. Moreover, advanced risk analysis and Bayesian inference techniques are used to obtain the reliability index with inspection. The optimal inspection planning is obtained by maximizing system-level reliability growth. This model is applied to an offshore wind farm. The results show that inspection efficiency can be improved by increasing the number of repair objects in response to a ‘detection’ inspection outcome, changing the inspection object for each inspection, and increasing the inspection quality. The maximum system-level reliability growth gained from one additional inspection decreases as the number of inspections increases. This study quantifies the inspection efficiency of offshore wind farms by explicit system-level reliability growth computation, offering valuable insights for promoting sustainable energy solutions.

Scientific monitoring is a fundamental basis of scientific advice. Among others, monitoring aims at contributing towards understanding the influence of anthropogenic use (e.g. fisheries), the health of a stock and individuum and effectiveness of management and conservation measures (e.g. MPAs). Monitoring of demersal and benthic fish communities is often based on invasive methods like bottom trawling, however in some cases less invasive methods might be available. The need for developing alternative and less invasive monitoring methods is supported by an increasing number of Marine Protected Areas and Windfarms where traditional methods such as trawls cannot be deployed due to conservational or technical and safety reasons. To support the development of new monitoring concepts, we conducted a literature review to identify limits and opportunities of methods that are already available. Furthermore, we present a fit-for purpose guide that can help identifying the appropriate method for individual purposes. We defined eight different methods which were analyzed using four different criteria and listed their advantages and disadvantages. We further apply this guide to monitoring in Marine Protected Areas in the Baltic Sea as a case study, indicating that besides traditional bottom trawling, alternative and less invasive methods could be sufficient for specific research purposes. We therefore, encourage scientists and managers to consider alternative data collection methods to minimize environmental impact of scientific sampling. However, our results also indicate that most of the methods still need further refinement especially regarding sampling design, standardization of methods and comparability with established survey methods.

Offshore wind farms (OWFs), built extensively in recent years, induce changes in the surrounding water environment. The changes in the suspended sediment concentration (SSC) and chlorophyll-a concentration (Chl-aC) induced by an OWF in the Yangtze River Estuary were analyzed based on Chinese Gaofen (GF) satellite data. The results show the following: (1) The flow near the wind turbines makes the bottom water surge, driving the sediment to "re-suspend" and be lost, deepening the scour pit around the bottom of the wind turbines, which is known as "self-digging". The interaction between the pillar of a wind turbine and tidal currents makes hydrodynamic factors more complicated. Blocking by wind turbines promoting the scour of the bottom seabed of the OWF results in speeding up the circulation rate of sediment loss and "re-suspension", which contributes to the change in the SSC and Chl-aC. This kind of change in sediment transport in estuarine areas due to human construction affects the balance of the ecological environment. Long-term sediment loss around wind turbines also influences the safety of wind turbines. (2) The SSC and Chl-aC are mainly in the range of 200–600 mg/L and 3–7 μg/L, respectively, in the OWF area, higher than the values obtained in surrounding waters. The SSC and Chl-aC downstream of the OWF are higher than those upstream, with differences of 100–300 mg/L and 0.5–2 μg/L. High SSC and Chl-aC "tails" appear downstream of wind turbines, consistent with the direction of local tidal currents, with lengths in the range of 2–4 km. In addition, the water environment in the vicinity of a wind turbine array, with a roughly 2–5 km scope (within 4 km during flooding and around 2.5 km during ebbing approximately) downstream of the wind turbine array, is impacted by the OWF. (3) In order to solve the problem of "self-digging" induced by OWFs, it is suggested that the distance between two wind turbines should be controlled within 2–3.5 km in the main flow direction, promising that the second row of wind turbines will be placed on the suspended sediment deposition belt induced by the first row. In this way, the problems of ecosystem imbalance and tidal current structure change caused by sediment loss because of local scouring can be reduced. Furthermore, mutual compensation between wind turbines can solve the "self-digging" problem to a certain extent and ensure the safety of OWFs. [ABSTRACT FROM AUTHOR]

New areas for the production of fossil-free renewable offshore energy production are planned in Arctic waters in the Bay of Bothnia, in the very north of the Baltic Sea between Sweden and Finland. These are waters normally covered with 30–60 cm of ice every winter and shipping is carried out with icebreaker assistance. This article suggests the need for research on the wind turbine's effect on ice behavior and ice navigation. Some concepts from previous research are suggested as a solution. [ABSTRACT FROM AUTHOR]