Evaluating drivers of recent large whale strandings on the East Coast of the United States.

Anthropogenic stressors threaten large whales globally. Effective management requires an understanding of where, when, and why threats are occurring. Strandings data provide key information on geographic hotspots of risk and the relative importance of various threats. There is currently considerable public interest in the increased frequency of large whale strandings occurring along the US East Coast of the United States since 2016. Interest is accentuated due to a purported link with offshore wind energy development. We reviewed spatiotemporal patterns of strandings, mortalities, and serious injuries of humpback whales (Megaptera novaeangliae), the species most frequently involved, for which the US government has declared an "unusual mortality event" (UME). Our analysis highlights the role of vessel strikes, exacerbated by recent changes in humpback whale distribution and vessel traffic.  Humpback whales have expanded into new foraging grounds in recent years. Mortalities due to vessel strikes have increased significantly in these newly occupied regions, which show high vessel traffic that also increased markedly during the UME. Surface feeding and feeding in shallow waters may have been contributing factors. We found no evidence that offshore wind development contributed to strandings or mortalities. This work highlights the need to consider behavioral, ecological, and anthropogenic factors to determine the drivers of mortality and serious injury in large whales and to provide informed guidance to decision-makers.

Análisis de las causantes de los recientes varamientos de ballenas en la costa este de los Estados Unidos Resumen El estrés antropogénico amenaza a las ballenas en todo el mundo. El manejo efectivo requiere comprender en dónde, cuándo y por qué ocurren las amenazas. Los datos de varamientos proporcionan información clave sobre los puntos críticos geográficos de riesgo y la importancia relativa de varias amenazas. Actualmente existe un interés público considerable por el incremento en la frecuencia de varamientos de ballenas que ocurren en la costa este de los Estados Unidos desde 2016, al cual el gobierno nacional ha denominado un "evento inusual de mortalidad" (EIM). El interés se acentúa debido a la supuesta conexión con el desarrollo de la energía eólica marina. Revisamos los patrones espaciotemporales de los varamientos, mortandad y lesiones graves de las ballenas jorobadas (Megaptera novaeangliae), la especie involucrada con mayor frecuencia. Nuestro análisis resalta el papel de las colisiones con navíos, agudizados por los cambios recientes en la distribución de la especie, y el tráfico de navíos. Las ballenas jorobadas se han expandido hacia nuevas áreas de forrajeo y los años recientes. La mortandad causada por las colisiones con navíos ha incrementado significativamente en estas regiones ocupadas recientemente, las cuales también muestran un tráfico elevado de navíos que también incrementó durante el EIM. La alimentación superficial y en áreas someras podrían ser factores contribuyentes. No encontramos evidencia de que la energía eólica marina contribuya a los varamientos o a la mortandad. Este trabajo resalta la necesidad de considerar los factores ecológicos, antropogénicos y de comportamiento para determinar las causas de la mortalidad y las lesiones graves en las ballenas y de proporcionar orientación informada para quienes toman las decisiones.

Fatigue Analysis of a Jacket-Supported Offshore Wind Turbine at Block Island Wind Farm.

Offshore wind-turbine (OWT) support structures are subjected to cyclic dynamic loads with variations in loadings from wind and waves as well as the rotation of blades throughout their lifetime. The magnitude and extent of the cyclic loading can create a fatigue limit state controlling the design of support structures. In this paper, the remaining fatigue life of the support structure for a GE Haliade 6 MW fixed-bottom jacket offshore wind turbine within the Block Island Wind Farm (BIWF) is assessed. The fatigue damage to the tower and the jacket support structure using stress time histories at instrumented and non-instrumented locations are processed. Two validated finite-element models are utilized for assessing the stress cycles. The modal expansion method and a simplified approach using static calculations of the responses are employed to estimate the stress at the non-instrumented locations-known as virtual sensors. It is found that the hotspots at the base of the tower have longer service lives than the jacket. The fatigue damage to the jacket leg joints is less than 20% and 40% of its fatigue capacity during the 25-year design lifetime of the BIWF OWT, using the modal expansion method and the simplified static approach, respectively.

Inspection of Floating Offshore Wind Turbines Using Multi-Rotor Unmanned Aerial Vehicles: Literature Review and Trends.

Operations and maintenance (O&M) of floating offshore wind turbines (FOWTs) require regular inspection activities to predict, detect, and troubleshoot faults at high altitudes and in harsh environments such as strong winds, waves, and tides. Their costs typically account for more than 30% of the lifetime cost due to high labor costs and long downtime. Different inspection methods, including manual inspection, permanent sensors, climbing robots, remotely operated vehicles (ROVs), and unmanned aerial vehicles (UAVs), can be employed to fulfill O&M missions. The UAVs, as an enabling technology, can deal with time and space constraints easily and complete tasks in a cost-effective and efficient manner, which have been widely used in different industries in recent years. This study provides valuable insights into the existing applications of UAVs in FOWT inspection, highlighting their potential to reduce the inspection cost and thereby reduce the cost of energy production. The article introduces the rationale for applying UAVs to FOWT inspection and examines the current technical status, research gaps, and future directions in this field by conducting a comprehensive literature review over the past 10 years. This paper will also include a review of UAVs' applications in other infrastructure inspections, such as onshore wind turbines, bridges, power lines, solar power plants, and offshore oil and gas fields, since FOWTs are still in the early stages of development. Finally, the trends of UAV technology and its application in FOWTs inspection are discussed, leading to our future research direction.

Ultra-Short-Term Offshore Wind Power Prediction Based on PCA-SSA-VMD and BiLSTM.

In order to realize the economic dispatch and safety stability of offshore wind farms, and to address the problems of strong randomness and strong time correlation in offshore wind power forecasting, this paper proposes a combined model of principal component analysis (PCA), sparrow algorithm (SSA), variational modal decomposition (VMD), and bidirectional long- and short-term memory neural network (BiLSTM). Firstly, the multivariate time series data were screened using the principal component analysis algorithm (PCA) to reduce the data dimensionality. Secondly, the variable modal decomposition (VMD) optimized by the SSA algorithm was applied to adaptively decompose the wind power time series data into a collection of different frequency components to eliminate the noise signals in the original data; on this basis, the hyperparameters of the BiLSTM model were optimized by integrating SSA algorithm, and the final power prediction value was obtained. Ultimately, the verification was conducted through simulation experiments; the results show that the model proposed in this paper effectively improves the prediction accuracy and verifies the effectiveness of the prediction model.

Phased Array Ultrasonic Method for Robotic Preload Measurement in Offshore Wind Turbine Bolted Connections.

This paper presents a novel approach for preload measurement of bolted connections, specifically tailored for offshore wind applications. The proposed method combines robotics, Phased Array Ultrasonic Testing (PAUT), nonlinear acoustoelasticity, and Finite Element Analysis (FEA). Acceptable defects, below a pre-defined size, are shown to have an impact on preload measurement, and therefore conducting simultaneous defect detection and preload measurement is discussed in this paper. The study demonstrates that even slight changes in the orientation of the ultrasonic transducer, the non-automated approach, can introduce a significant error of up to 140 MPa in bolt stress measurement and therefore a robotic approach is employed to achieve consistent and accurate measurements. Additionally, the study emphasises the significance of considering average preload for comparison with ultrasonic data, which is achieved through FEA simulations. The advantages of the proposed robotic PAUT method over single-element approaches are discussed, including the incorporation of nonlinearity, simultaneous defect detection and stress measurement, hardware and software adaptability, and notably, a substantial improvement in measurement accuracy. Based on the findings, the paper strongly recommends the adoption of the robotic PAUT approach for preload measurement, whilst acknowledging the required investment in hardware, software, and skilled personnel.

Vibration-Based SHM in the Synthetic Mooring Lines of the Semisubmersible OO-Star Wind Floater under Varying Environmental and Operational Conditions.

As the industry transitions toward Floating Offshore Wind Turbines (FOWT) in greater depths, conventional chain mooring lines become impractical, prompting the adoption of synthetic fiber ropes. Despite their advantages, these mooring lines present challenges in inspection due to their exterior jacket, which prevents visual assessment. The current study focuses on vibration-based Structural Health Monitoring (SHM) in FOWT synthetic mooring lines under uncertainty arising from varying Environmental and Operational Conditions (EOCs). Six damage detection methods are assessed, utilizing either multiple models or a single functional model. The methods are based on Vector Autoregressive (VAR) or Transmittance Function Autoregressive with exogenous input (TF-ARX) models. All methods are evaluated through a Monte Carlo study involving 1100 simulations, utilizing acceleration signals generated from a finite element model of the OO-Star Wind Floater Semi 10 MW wind turbine. With signals from only two measuring positions, the methods demonstrate excellent results, detecting the stiffness reduction of a mooring line at levels 10% through 50%. The methods are also tested for healthy cases, with those utilizing TF-ARX models achieving zero false alarms, even for EOCs not encountered in the training data.

Bidding against the wind: A choice experiment in green energy, green jobs and offshore views in North Carolina, USA.

Offshore wind development is in its nascent stages in the United States. Recent research indicates that the visual impacts of offshore wind farms are viewed negatively by the general population. This North Carolina application is the first US-focused discrete choice experiment that explicitly asks respondents to consider the positive local and global benefits from offshore wind development, such as job creation and greenhouse gas emission reductions, simultaneously with their visual impacts. We find significant willingness to pay (WTP) for reducing the visual impacts of offshore wind farms, and that the extent of disamenity varies in the population and with placement along developed tourist towns (as much as $783/year for three years) or preserved coastlines (as much as $451/year for three years). We also find that some preference classes value projects that create permanent jobs and reduce carbon emissions. We use our estimates of preferences for the positive and negative attributes to explore specific wind farm configurations and locations that could achieve positive consensus in a heterogenous population.

Developing expert scientific consensus on the environmental and societal effects of marine artificial structures prior to decommissioning.

Thousands of artificial ('human-made') structures are present in the marine environment, many at or approaching end-of-life and requiring urgent decisions regarding their decommissioning. No consensus has been reached on which decommissioning option(s) result in optimal environmental and societal outcomes, in part, owing to a paucity of evidence from real-world decommissioning case studies. To address this significant challenge, we asked a worldwide panel of scientists to provide their expert opinion. They were asked to identify and characterise the ecosystem effects of artificial structures in the sea, their causes and consequences, and to identify which, if any, should be retained following decommissioning. Experts considered that most of the pressures driving ecological and societal effects from marine artificial structures (MAS) were of medium severity, occur frequently, and are dependent on spatial scale with local-scale effects of greater magnitude than regional effects. The duration of many effects following decommissioning were considered to be relatively short, in the order of days. Overall, environmental effects of structures were considered marginally undesirable, while societal effects marginally desirable. Experts therefore indicated that any decision to leave MAS in place at end-of-life to be more beneficial to society than the natural environment. However, some individual environmental effects were considered desirable and worthy of retention, especially in certain geographic locations, where structures can support improved trophic linkages, increases in tourism, habitat provision, and population size, and provide stability in population dynamics. The expert analysis consensus that the effects of MAS are both negative and positive for the environment and society, gives no strong support for policy change whether removal or retention is favoured until further empirical evidence is available to justify change to the status quo. The combination of desirable and undesirable effects associated with MAS present a significant challenge for policy- and decision-makers in their justification to implement decommissioning options. Decisions may need to be decided on a case-by-case basis accounting for the trade-off in costs and benefits at a local level.

To what extent can decommissioning options for marine artificial structures move us toward environmental targets?

Switching from fossil fuels to renewable energy is key to international energy transition efforts and the move toward net zero. For many nations, this requires decommissioning of hundreds of oil and gas infrastructure in the marine environment. Current international, regional and national legislation largely dictates that structures must be completely removed at end-of-life although, increasingly, alternative decommissioning options are being promoted and implemented. Yet, a paucity of real-world case studies describing the impacts of decommissioning on the environment make decision-making with respect to which option(s) might be optimal for meeting international and regional strategic environmental targets challenging. To address this gap, we draw together international expertise and judgment from marine environmental scientists on marine artificial structures as an alternative source of evidence that explores how different decommissioning options might ameliorate pressures that drive environmental status toward (or away) from environmental objectives. Synthesis reveals that for 37 United Nations and Oslo-Paris Commissions (OSPAR) global and regional environmental targets, experts consider repurposing or abandoning individual structures, or abandoning multiple structures across a region, as the options that would most strongly contribute toward targets. This collective view suggests complete removal may not be best for the environment or society. However, different decommissioning options act in different ways and make variable contributions toward environmental targets, such that policy makers and managers would likely need to prioritise some targets over others considering political, social, economic, and ecological contexts. Current policy may not result in optimal outcomes for the environment or society.

Risk assessment of deep-sea floating offshore wind power projects based on hesitant fuzzy linguistic term set considering trust relationship among experts.

The development of deep-sea floating offshore wind power (FOWP) is the key to fully utilizing water resources to enhance wind resources in the years ahead, and then the project is still in its initial stage, and identifying risks is a crucial step before promoting a significant undertaking. This paper proposes a framework for identifying risks in deep-sea FOWP projects. First, this paper identifies 16 risk criteria and divides them into 5 groups to establish a criteria system. Second, hesitant fuzzy linguistic term set (HFLTS) and triangular fuzzy number (TFN) are utilized to gather and describe the criterion data to ensure the robustness and completeness of the criterion data. Third, extending the method for removal effects of criteria (MEREC) to the HFLTS environment through the conversion of TFNs, under the influence of subjective preference and objective fairness, a weighting method combining analytic network process (ANP) and MEREC is utilized to calculate criteria weights, and the trust relationship and consistency between experts are used to calculate the expert weights to avoid the subjective weighting given by experts arbitrariness. Fourth, the study's findings indicated that the overall risk level of the deep-sea FOWP projects is "medium." Fifth, sensitivity and comparative analyses were conducted to test the reliability of the assessment outcomes. lastly, this research proposes risk management measures for the deep-sea FOWP project's establishment from economic, policy, technology, environment, and management aspects.

Ecological impacts of the expansion of offshore wind farms on trophic level species of marine food chain.

The global demand for renewable energy has resulted in a rapid expansion of offshore wind farms (OWFs) and increased attention to the ecological impacts of OWFs on the marine ecosystem. Previous reviews mainly focused on the OWFs' impacts on individual species like birds, bats, or mammals. This review collected numerous field-measured data and simulated results to summarize the ecological impacts on phytoplankton, zooplankton, zoobenthos, fishes, and mammals from each trophic level and also analyze their interactions in the marine food chain. Phytoplankton and zooplankton are positively or adversely affected by the 'wave effect', 'shading effect', oxygen depletion and predation pressure, leading to a ± 10% fluctuation of primary production. Although zoobenthos are threatened transiently by habitat destruction with a reduction of around 60% in biomass in the construction stage, their abundance exhibited an over 90% increase, dominated by sessile species, due to the 'reef effect' in the operation stage. Marine fishes and mammals are to endure the interferences of noise and electromagnetic, but they are also aggregated around OWFs by the 'reef effect' and 'reserve effect'. Furthermore, the complexity of marine ecosystem would increase with a promotion of the total system biomass by 40% through trophic cascade effects strengthen and resource partitioning alternation triggered by the proliferation of filter-feeders. The suitable site selection, long-term monitoring, and life-cycle-assessment of ecological impacts of OWFs that are lacking in current literature have been described in this review, as well as the carbon emission and deposition.

Offshore Wind Energy and Marine Biodiversity in the North Sea: Life Cycle Impact Assessment for Benthic Communities.

Large-scale offshore wind energy developments represent a major player in the energy transition but are likely to have (negative or positive) impacts on marine biodiversity. Wind turbine foundations and sour protection often replace soft sediment with hard substrates, creating artificial reefs for sessile dwellers. Offshore wind farm (OWF) furthermore leads to a decrease in (and even a cessation of) bottom trawling, as this activity is prohibited in many OWFs. The long-term cumulative impacts of these changes on marine biodiversity remain largely unknown. This study integrates such impacts into characterization factors for life cycle assessment based on the North Sea and illustrates its application. Our results suggest that there are no net adverse impacts during OWF operation on benthic communities inhabiting the original sand bottom within OWFs. Artificial reefs could lead to a doubling of species richness and a two-order-of-magnitude increase of species abundance. Seabed occupation will also incur in minor biodiversity losses in the soft sediment. Our results were not conclusive concerning the trawling avoidance benefits. The developed characterization factors quantifying biodiversity-related impacts from OWF operation provide a stepping stone toward a better representation of biodiversity in life cycle assessment.

Small-Signal Stability Analysis and MOSMA-Based Optimization Control Strategy of OWF with MMC-HVDC Grid Connection.

The recent oscillation events in offshore wind farms (OWFs) connected via a modular multilevel-converter-based HVDC (MMC-HVDC) system are developing towards a wider frequency band, which causes complex a small-signal interaction phenomenon and difficulties in the stability analysis and control. In this paper, the wideband dynamic interaction mechanism is investigated based on the impedance analysis method and an improved control strategy using an optimization algorithm is proposed to improve the small-signal stability and reduce the oscillation risks. First, the detailed impedance models of the grid-connected system are established considering the distribution characteristics of the submarine cable, control delay and frequency coupling effect. Then, combined with the active damping control method, the wideband resonance mechanism is analyzed, and the stability constraints of controller parameters are obtained using the impedance stability criterion. Finally, an improved multi-objective slime mold algorithm (MOSMA)-based coordinated optimization control strategy is proposed to enhance the adaptability of the controller parameters and the wideband damping ability of a grid-connected system, which can improve the wideband stability of the system. The simulation and experimental results verify the proposed control strategy.

Decommissioning of offshore wind farms and its impact on benthic ecology.

At the end of their operational life time offshore wind farms need to be decommissioned. How and to what extent the removal of the underwater structures impairs the ecosystem that developed during the operational phase of the wind farm is not known. So, decision makers face a knowledge gap, making the consideration of such ecological impacts challenging when planning decommissioning. This study evaluates how complete or partial decommissioning of foundation structure and scour protection layer impacts local epibenthic macrofauna biodiversity. We assessed three decommissioning alternatives (one for complete and two for partial removal) regarding their impact on epibenthic macrofauna species richness. The results imply that leaving the scour protection layer in situ will preserve a considerable number of species while cutting of the foundation structure above seabed will be beneficial for the fauna of such foundation structures where no scour protection is installed. These results should be taken with a grain of salt, as the current data base is rather limited. Data need to be improved substantially to allow for reliable statements and sound advice regarding the ecological impact of offshore wind farm decommissioning.

Acoustic monitoring reveals spatiotemporal occurrence of Nathusius' pipistrelle at the southern North Sea during autumn migration.

Seasonal movements between the summer and winter areas are a widespread phenomenon in bats So far, most information on the migration ecology of bats has been obtained by studies in terrestrial habitats, whereas scientific knowledge on migration over sea is scarce. We performed continuous ultrasonic acoustic monitoring at 13 locations in the southern North Sea during four consecutive years (2017-2020) and analysed the spatiotemporal occurrence of Nathusius' pipistrelle Pipistrellus nathusii during autumn migration in relation to weather parameters and lunar phase. Our analysis showed that the main autumn migration of Nathusius' pipistrelle at the southern North Sea occurs from mid-August until late October and most bats within the study area occur off the Noord Holland coast. North Sea crossings frequently last longer than one night; the day is spent roosting at an offshore structure. The strongest migration occurs during nights with tailwinds from the east-northeast, but bats are also recorded offshore with low to moderate headwinds or crosswinds. Bat presence decreased between the full moon and the last quarter and increased just before the new moon. Finally, our observations show that the occurrence of bats at sea was reduced in 2020 in comparison to the previous years. The results of this study show clear spatiotemporal patterns of migratory bat occurrence at the southern North Sea. The spatial distribution can be used in spatial planning of future offshore wind farms, whereas the temporal occurrence and environmental factors that shape offshore migration can be used to develop mitigation measures to reduce the number of bat fatalities.

Decision Support System for Prioritization of Offshore Wind Farm Site by Utilizing Picture Fuzzy Combined Compromise Solution Group Decision Method.

The selection of offshore wind farm site (OWFS) has important strategic significance for vigorously developing offshore new energy and is deemed as a complicated uncertain multicriteria decision-making (MCDM) process. To further promote offshore wind power energy planning and provide decision support, this paper proposes a hybrid picture fuzzy (PF) combined compromise solution (CoCoSo) technique for prioritization of OWFSs. To begin with, a fresh PF similarity measure is proffered to estimate the importance of experts. Next, the novel operational rules for PF numbers based upon the generalized Dombi norms are defined, and four novel generalized Dombi operators are propounded. Afterward, the PF preference selection index (PSI) method and PF stepwise weights assessment ratio analysis (SWARA) model are propounded to identify the objective and subjective weight of criteria, separately. In addition, the enhanced CoCoSo method is proffered via the similarity measure and new operators for ranking OWFSs with PF information. Lastly, the applicability and feasibility of the propounded PF-PSI-SWARA-CoCoSo method are adopted to ascertain the optimal OWFS. The comparison and sensibility investigations are also carried out to validate the robustness and superiority of our methodology. Results manifest that the developed methodology can offer powerful decision support for departments and managers to evaluate and choose the satisfying OWFSs.

Environmental Impacts of Global Offshore Wind Energy Development until 2040.

Continuous reduction in the levelized cost of energy is driving the rapid development of offshore wind energy (OWE). It is thus important to evaluate, from an environmental perspective, the implications of expanding OWE capacity on a global scale. Nevertheless, this assessment must take into account various scenarios for the growth of different OWE technologies in the near future. To evaluate the environmental impacts of future OWE development, this paper conducts a prospective life cycle assessment (LCA) including parameterized supply chains with high technology resolution. Results show that OWE-related environmental impacts, including climate change, marine ecotoxicity, marine eutrophication, and metal depletion, are reduced by ∼20% per MWh from 2020 to 2040 due to various developments including size expansion, lifetime extension, and technology innovation. At the global scale, 2.6-3.6 Gt CO2 equiv of greenhouse gas emissions are emitted cumulatively due to OWE deployment from 2020 to 2040. The manufacturing of primary raw materials, such as steel and fibers, is the dominant contributor to impacts. Overall, 6-9% of the cumulative OWE-related environmental impacts could be reduced by end-of-life (EoL) recycling and the substitution of raw materials.

Social amplification of risks and the clean energy transformation: Elaborating on the four attributes of information.

The social amplification of risk framework (SARF) was developed to help comprehend how emerging contributions about the psychological, social, and cultural dimensions of risk could work in unison to impact decision making about risk. The framework proposed that risks are amplified or attenuated by interested parties employing different rhetorical strategies to give information about risk a certain "spin." The original literature identified four "attributes of information." However, despite the longevity of the framework, these have not been explicated in detail. Here we add depth and clarity by examining how amplification stations send risk signals that amplify or attenuate risk by emphasizing these different attributes of information. Drawing on a wealth of qualitative data from two case studies of offshore wind turbine siting off the coasts of Maryland and Delaware and guided by an extensive literature review, we reveal the strategies interested parties are using to influence siting decisions and risk management. The paper explores the usefulness of SARF in organizing qualitative information and sharpening insights on participatory risk governance and the nuances of public responses to a relatively new low-carbon technology. The authors conclude that the framework is valuable for analyzing stakeholder information while also recognizing limitations that may be addressed with some targeted future research.

Modeling Epistemic Uncertainty in Offshore Wind Farm Production Capacity to Reduce Risk.

Financial stakeholders in offshore wind farm projects require predictions of energy production capacity to better manage the risk associated with investment decisions prior to construction. Predictions for early operating life are particularly important due to the dual effects of cash flow discounting and the anticipated performance growth due to experiential learning. We develop a general marked point process model for the times to failure and restoration events of farm subassemblies to capture key uncertainties affecting performance. Sources of epistemic uncertainty are identified in design and manufacturing effectiveness. The model then captures the temporal effects of epistemic and aleatory uncertainties across subassemblies to predict the farm availability-informed relative capacity (maximum generating capacity given the technical state of the equipment). This performance measure enables technical performance uncertainties to be linked to the cost of energy generation. The general modeling approach is contextualized and illustrated for a prospective offshore wind farm. The production capacity uncertainties can be decomposed to assess the contribution of epistemic uncertainty allowing the value of gathering information to reduce risk to be examined.

Review on Monitoring, Operation and Maintenance of Smart Offshore Wind Farms.

In recent years, with the development of wind energy, the number and scale of wind farms have been developing rapidly. Since offshore wind farms have the advantages of stable wind speed, being clean, renewable, non-polluting, and the non-occupation of cultivated land, they have gradually become a new trend in the wind power industry all over the world. The operation and maintenance of offshore wind power has been developing in the direction of digitization and intelligence. It is of great significance to carry out research on the monitoring, operation, and maintenance of offshore wind farms, which will be of benefit for the reduction of the operation and maintenance costs, the improvement of the power generation efficiency, improvement of the stability of offshore wind farm systems, and the building of smart offshore wind farms. This paper will mainly summarize the monitoring, operation, and maintenance of offshore wind farms, with particular focus on the following points: monitoring of "offshore wind power engineering and biological and environment", the monitoring of power equipment, and the operation and maintenance of smart offshore wind farms. Finally, the future research challenges in relation to the monitoring, operation, and maintenance of smart offshore wind farms are proposed, and the future research directions in this field are explored, especially in marine environment monitoring, weather and climate prediction, intelligent monitoring of power equipment, and digital platforms.