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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]

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]

Currently, most studies on the optimization of wind farm layouts on flat terrain employ a discrete grid-based arrangement method and result in irregular layouts that may damage the visual appeal of wind farms. To meet the practical requirements of wind farms, a two-step optimization method called "grid–coordinate" based on a genetic algorithm is proposed in this paper. The core idea is to initially determine the number of wind turbines and their initial positions using a grid-based approach, followed by a fine-tuning of the wind farm layout by moving the turbines in a row/column manner. This two-step process not only achieves an aesthetically pleasing arrangement but also maximizes power generation. This algorithm is conducted to optimize a 2 km × 2 km wind farm under three classic wind conditions, one improved wind condition, and a real wind condition employing both the Jensen and Gaussian wake models. To validate the effectiveness of the proposed method, the optimization of configurations based on different wake models was conducted, yielding results including the efficiency, total power output, number of wind turbines, and unit cost of electricity generation. These results were compared and analyzed against the classical literature. The findings indicate that the unit cost of electricity generation using the two-step optimization approach with the Gaussian wake model is higher than that of the initial grid optimization method. Additionally, varying the number of wind turbines can lead to instances of high power generation coupled with low efficiency. This phenomenon should be carefully considered in the wind farm layout optimization process. [ABSTRACT FROM AUTHOR]

This paper investigates grid export constraints applicable to photovoltaic (PV) and wind farm (WF) installations, both with and without behind-the-meter storage, aimed at enhancing grid hosting capacity. The study focuses on static output power limitations, i.e., simple export constraints that are preventively imposed on renewable energy source (RES) plants regardless of the prevailing network congestion conditions. These constraints are easy to apply, implemented ex ante and out of market, and do not require additional investments in energy storage or advanced devices. They also yield a measurable increase in hosting capacity and grid utilization, with their impact on RES plant operation and return of investment straightforwardly calculable. Analysis defines the level and shape of these constraints assuming an indicative acceptable curtailment level of 5% for each RES technology attributed to the preventing action of the imposed limitations, while the respective implications for RES energy yield and investment viability are explored. The findings indicate that an export power limitation of ca. 68% is effective for stand-alone PVs, while a stepwise static limitation is necessary for stand-alone WFs and WFs with integrated storage to manage midday solar generation peaks. PV plants tightly coupled with storage facilities can handle static limitations as low as 35% with minimal impact on the economic feasibility of the investments. [ABSTRACT FROM AUTHOR]

In accordance with South Korea's recent 2030 Carbon Neutral Plan, an 8GW offshore wind farm is planned for construction in the South-west Sea. Therefore, it is expected that large-scale wind turbines will be installed, and these turbines must operate stably, even when there are instantaneous voltage fluctuations in the power system. The grid code is described for the low-voltage-ride-through (LVRT) and high-voltage-ride-through (HVRT) functions, and a test facility that can perform both LVRT and HVRT tests is essential. In the case of LVRT/HVRT test facilities developed by the existing RLC (impedance component) method, it may be difficult to test large-scale wind turbines due to problems such as power quality, frequent failures and narrow short-circuit capacity ranges. Therefore, to solve such problems, this paper proposes an LVRT/HVRT test facility of the autotransformer type, which is capable of outputting the desired voltage range by changing the wiring method and tap position. Specifically, in order to implement the test facility of the autotransformer type, which is able to output the desired voltage range by changing the wiring method and tap according to the LVRT/HVRT test status, this paper presents an impedance determination algorithm (two-step layer impedance determination algorithm) of auto-transformer based on the fault-current analysis and operation strategy at a real LVRT/HVRT testing evaluation facility. [ABSTRACT FROM AUTHOR]

In an era of big data, organizations increasingly aim to adopt data-driven decision-making processes to enhance their performance. This paper investigates the data-driven decision-making process by developing a framework tailored for application in the energy sector. The proposed framework integrates interdisciplinary approaches to comprehensively address the "data, information, knowledge" triad, applying it to both operational and maintenance decision-making. Designed to be managerially focused rather than technically oriented, the framework aims to engage all employees, including those without technical backgrounds, enabling them to effectively contribute to the decision-making process from their respective roles. To demonstrate the practical application of the proposed framework, this paper presents a case study of an energy organization managing a wind farm project, which implemented the framework to improve its decision-making process. The case study examines how the organization identified its objectives and information needs, formulated key performance questions for each stakeholder, explicitly defined and measured the key performance indicators, employed data collection and organization methods, managed the progression from data to information to knowledge, and transformed the acquired knowledge into informed decisions. By adopting this pragmatic framework, energy organizations are anticipated to solve problems, predict trends, and discover new opportunities, thereby enhancing their efficiency and predictability. [ABSTRACT FROM AUTHOR]

Offshore wind power has attracted significant attention due to its high potential, capability for large-scale farms, and high capacity factor. However, it faces high investment costs and issues with subsea power transmission. Conventional high-voltage AC (HVAC) methods are limited by charging current, while high-voltage DC (HVDC) methods suffer from the high cost of power conversion stations. The low-frequency AC (LFAC) method mitigates the charging current through low-frequency operation and can reduce power conversion station costs. This paper aims to identify the economically optimal frequency by comparing the investment costs of LFAC systems at various frequencies. The components of LFAC, including transformers, offshore platforms, and cables, exhibit frequency-dependent characteristics. Lower frequencies result in an increased size and volume of transformers, leading to higher investment costs for offshore platforms. In contrast, cable charging currents and losses are proportional to frequency, causing the total cost to reach a minimum at a specific frequency. To determine the optimal frequency, simulations of investment costs for varying capacities and distances were conducted. [ABSTRACT FROM AUTHOR]

In large-scale wind farms, the voltage fluctuations caused by the uncertainty of wind speed at the turbine terminals pose a pressing challenge. This article presents a localized voltage control strategy tailored toward rapid adjustments in turbine terminal voltage in wind turbine generators. Based on relative voltage observation, this strategy achieves voltage coordination between the high and low ends of the transformer in wind turbine generators. Firstly, the overall structure of the wind farm and the characteristics of terminal voltage are analyzed. Secondly, the principles and feasibility of the relative voltage control strategy are examined. Finally, the effectiveness of the proposed control strategy is validated through simulation results from a specific wind farm. The results demonstrate its capability to achieve a fast and stable voltage dynamic response within the wind farm based on local information, thus mitigating the risk of voltage out of limit. [ABSTRACT FROM AUTHOR]

In recent trends, a rising demand for renewable energy has driven wind turbines to larger proportions, where lighter blade designs are often adopted to reduce the costs associated with logistics and production. This causes modern utility-scale wind turbine blades to be inherently more flexible, and their amplified aeroelastic sensitivity results in complex multi-physics reactions to variant atmospheric conditions, including dynamic patterns of aerodynamic loading at the rotor and vortex structure evolutions within the wake. In this paper, we analyze the influence of inflow variance for wind turbines with large, flexible rotors through simulations of the National Rotor Testbed (NRT) turbine, located at Sandia National Labs' Scaled Wind Farm Technology (SWiFT) facility in Lubbock, Texas. The Common Ordinary Differential Equation Framework (CODEF) modeling suite is used to simulate wind turbine aeroelastic oscillatory behavior and wind farm vortex wake interactions for a range of flexible NRT blade variations, operating in differing conditions of variant atmospheric flow. CODEF solutions of turbine operation in Steady-In-The-Average (SITA) wind conditions are compared to SITA wind conditions featuring a controlled gust-like pulse overimposed, to isolate the effects of typical wind fluctuations. Finally, simulations of realistic time-varying wind conditions from SWiFT meteorological tower measurements are compared to the solutions of SITA wind conditions. These increasingly complex atmospheric inflow variations are tested to show the differing effects evoked by various patterns of spatiotemporal atmospheric flow fluctuations. An analysis is presented for solutions of wind turbine aeroelastic response and vortex wake evolution, to elucidate the consequences of variant inflow, which pertain to wind turbine dynamics at an individual and farm-collective scale. The comparisons of simulated farm flow for SITA and measured fluctuating wind conditions show that certain regions of the wake contain up to a 12% difference in normalized axial velocity, due to the introduction of wind fluctuations. The findings of this study prove valuable for practical applications in wind farm control and optimization strategies, with particular significance for modern utility-scale wind power plants operating in variant atmospheric conditions. [ABSTRACT FROM AUTHOR]

Subsynchronous oscillations have occurred in wind farms due to the high penetration of converter-based technology in power systems and may potentially lead to grid instability. As an effective solution, synchronous condensers, with their ability to control voltage and inject reactive power in the power system, are increasingly being adopted, as they can lead to the mitigation of such oscillations in weak grid conditions. However, the impact of synchronous condensers' power ratings on system stability is a topic that requires further investigation. In fact, an improper selection of a synchronous condenser's rating will not extinguish existing subsynchronous oscillations and may even cause the emergence of new oscillatory phenomena. This paper presents a novel examination of the impact that the synchronous condenser's power rating has on the small-signal stability of a wind farm with existing subsynchronous oscillations while being connected to a weak grid. The wind farm's model is developed using state-space modeling, centering on grid interconnection and incorporating the state-space submodel of a synchronous condenser to show its impact on subsynchronous oscillation mitigation. The stability analysis determines the optimal synchronous condenser's power ratings for suppressing these oscillations in the wind farm model. The findings are corroborated through time domain simulations and fast-Fourier transformation (FFT) analysis, which further validate the stability effects of a synchronous condenser's rating. [ABSTRACT FROM AUTHOR]

Scouring around the fixed foundations of offshore wind turbines (OWTs) remains a pressing concern within the offshore wind industry, significantly jeopardizing OWT safety. Despite previous efforts, the current understanding of this phenomenon remains incomplete, as various factors related to offshore wind farms and OWT operations can exert intricate influences. To further explore this matter, this paper undertakes a new study to further understand the interplay between monopile vibrations, tidal currents, and sea waves, elucidating their combined impact on scour surrounding an OWT's foundation. It was found that, besides pile vibration amplitude and frequency, the pile vibration direction can also notably influence the scour around the monopile. Specifically, the most pronounced scour mostly transpires when the monopile undergoes vibrations along the 135° direction relative to the inflow direction. The mildest scour mostly occurs when the pile vibrates along the 90° direction. Additionally, this study reveals that different types of waves, indicated by the ratio of water depth, H, to wavelength, L, also engender varying scour around the monopile. The influence of waves on scour increases with the decrease in the H/L ratio, implying that OWT foundations are more threatened by shallow water waves than by deep water waves. [ABSTRACT FROM AUTHOR]

Offshore wind farms are great options for addressing the world's energy and climate change challenges, as well as meeting rising energy demand while taking environmental and economic impacts into account. Floating wind turbines, in specific, depict the next horizon in the sustainable renewable energy industry. In this study, a life-cycle cost analysis for floating offshore wind turbines is developed by combining the most recent data and parametric formulas from databases and relevant papers. The cost analysis models focused on cost minimization with special emphasis on Operation and Maintenance Cost (OPEX), Decommissioning Cost (DECOM), and Levelized Cost of Energy (LCOE), which are important factors in wind power economy. Given that floating wind energy is still developing, the presented scenarios should be beneficial in making future decisions. The cost analysis scenarios include on-site and off-site maintenance scenarios for OPEX. In addition, four alternative scenarios for DECOM have been examined: mechanical recycling, mechanical-incineration, incineration processes, and landfill. According to the findings of these scenarios, OPEX varies from 16.89 to 19.93 £/MWh and DECOM between 3.47 and 3.65 £/MWh, whilst the total LCOE varied from 50.67 to 66.73 £/MWh. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach for optimizing wind farm control through the utilization of a combined model predictive control method. In contrast to conventional methods of controlling active and reactive power in wind farms, the suggested approach integrates a wind power prediction model driven by a neural network and a state-space model for wind turbines. This combination facilitates a more precise forecast of active power, thereby enabling the dynamic prediction of the range of reactive power output from the wind turbines. When combined with the equation of state in wind farm space, it is possible to accurately optimize the reactive power of a wind farm. Furthermore, the impact of active power on voltage fluctuations in the wind farm collector system was examined. The utilization of model predictive control enhances voltage regulation, optimizes system redundancy, and increases the reactive capacity. Sensitivity coefficients were calculated using analytical methods to enhance computational efficiency and to resolve issues related to convergence. In order to validate the proposed methodology and control scheme, a wind farm simulation model comprising 20 turbines was developed to assess the feasibility of the scheme. [ABSTRACT FROM AUTHOR]

The integration of wind energy into power systems has intensified as a result of the urgency for global energy transition. This requires more accurate forecasting techniques that can capture the variability of the wind resource to achieve better operative performance of power systems. This paper presents an exhaustive review of the state-of-the-art of wind-speed and -power forecasting models for wind turbines located in different segments of power systems, i.e., in large wind farms, distributed generation, microgrids, and micro-wind turbines installed in residences and buildings. This review covers forecasting models based on statistical and physical, artificial intelligence, and hybrid methods, with deterministic or probabilistic approaches. The literature review is carried out through a bibliometric analysis using VOSviewer and Pajek software. A discussion of the results is carried out, taking as the main approach the forecast time horizon of the models to identify their applications. The trends indicate a predominance of hybrid forecast models for the analysis of power systems, especially for those with high penetration of wind power. Finally, it is determined that most of the papers analyzed belong to the very short-term horizon, which indicates that the interest of researchers is in this time horizon. [ABSTRACT FROM AUTHOR]

Predicting the output power of wind generators is essential to improve grid flexibility, which is vulnerable to power supply variability and uncertainty. Digital twins can help predict the output of a wind turbine using a variety of environmental data generated by real-world systems. This paper dealt with the development of a physics-based output prediction model (P-bOPM) for a 10 MW floating offshore wind turbine (FOWT) for a digital twin. The wind power generator dealt with in this paper was modeled considering the NREL 5 MW standard wind turbine with a semi-submersible structure. A P-bOPM of a 10 MW FOWT for a digital twin was designed and simulated using ANSYS Twin Builder. By connecting the P-bOPM developed for the digital twin implementation with an external sensor through TCP/IP communication, it was possible to calculate the output of the wind turbine using real-time field data. As a result of evaluating the P-bOPM for various marine environments, it showed good accuracy. The digital twin equipped with the P-bOPM, which accurately reflects the variability of the offshore wind farm and can predict the output in real time, will be a great help in improving the flexibility of the power system in the future. [ABSTRACT FROM AUTHOR]

A new primary frequency controller in power grids undergoing massive wind power penetration is the focus of this paper. The inescapable problem in a largely wind penetrated power grid is to ensure the maintenance of its frequency in the nominal band prescribed by the power system operator (PSO). However, with the massive arrival of wind farms with conventional control schemes, the operation of maintaining and restoring the frequency to the regulatory regimes remains very complicated. In order to overcome the above problem, this paper proposes a new strategy for primary frequency control in power grids using model predictive control (MPC) for a multi-cluster doubly-fed induction generator (DFIG)-based wind farm (WF), with a main objective of reducing the frequency nadir (FN), eliminating the second frequency dip (SFD), and providing the optimal support during wind speed variations. In this approach, a rolling prediction and optimization control strategy is developed based on the dynamic power system model to ideally predict the additional power to be provided. Moreover, in order to avoid second frequency dips, the wind turbines (WTs) are not allocated to extract additional power from the grid during the frequency event, the rotor speeds are not recovered to the maximum power point tracking (MPPT) operating points during the primary frequency control. The performance of the proposed controller was evaluated using a two-zone electrical system in MATLAB/Simulink®. The obtained results disclose that the frequency nadir is enhanced with more than 6.1% compared to the conventional schemes. In addition, the frequency response settling time has been improved with more than 10.51 s. [ABSTRACT FROM AUTHOR]

Offshore wind energy is becoming an increasingly important element in the decarbonisation of energy systems. This study aims to estimate the technical potential for offshore wind energy in the Polish exclusive economic zone (EZZ) of the Baltic Sea. Such estimates are necessary to plan the expansion of energy infrastructure. This paper proposes a multi-criteria analysis for the estimation of offshore wind potential and site selection using QGIS software (QGIS Desktop 3.28.6). The criteria include wind velocity, water depth, distance from nature conservation areas, distance from submarine cables and gas pipelines, distance from shipping routes, distance from fishing areas, distance from shipwrecks, and distance from the coastline. The best sites are identified through the Analytic Hierarchy Process (AHP). The results show that the total suitable marine area of 16,218.67 square kilometres can be divided into three parts, in which the highly suitable area for offshore wind farms accounts for 17.55%, the moderately suitable area accounts for 48.56%, and the marginally suitable area accounts for 10.26%. Two different wind turbine placement configurations are being considered, in which wind turbines with a nominal capacity of 15 MW are laid out: 2.5 km and 2 km apart from each other. The corresponding overall electrical capacities only in highly suitable areas equal ca. 9 GW and 15 GW, respectively. If this area is extended to also include the moderately suitable parts, these values increase to ca. 31 GW and 50 GW. The results indicate that the technical potential of offshore wind in the Polish EEZ is significant and should be taken into account when designing the future electricity generation mix. [ABSTRACT FROM AUTHOR]

Despite the widespread usage of high-voltage alternating current (HVAC) for the connection of offshore wind farms (OWF), its use to power-from-shore (PFS) offshore oil and gas (O&G) production sites is often not feasible. Its limitations for long-distance subsea transmission are usually found at 50–70 km from shore and might be even shorter when compared commercially to a direct-current (DC) alternative or conventional generation. Therefore, this research paper aims to address the standardization of offshore transmission with a particular focus on the high-voltage direct current (HVDC) alternative. While the distance is typically not a limiting factor when using DC, and the voltages used are rather standard, the concept of power envelopes can be quite useful in addressing the high variability of offshore site power requirements and setting a design baseline that would lead to improved lead time. In this article, a full back and front-end genetic optioneering model purposely built from the ground up in Python language is used to #1 define up to three DC power envelopes that would cater to most of the candidate's requirements and #2 provide the lowest cost variance. The results will demonstrate that this can be achieved at a minor overall cost expense. [ABSTRACT FROM AUTHOR]

The European Union's climate policy aims to reduce greenhouse gas emissions by 55% by 2030 and to achieve climate neutrality by 2050. One of the instruments for achieving these climate goals is the development of offshore wind energy. Unfortunately, Poland, as one of the few European Union countries with access to the sea, does not have offshore wind farms yet. The purpose of this article is to determine the importance of offshore wind energy for the development of Poland based on the example of two sea regions: the West Pomeranian and Pomeranian Voivodeships. This article uses the input–output method to determine the economic effects of offshore wind power. The region's share in the supply chain was determined based on the location of the offshore wind energy sector. A comparative analysis with the Saint-Brieuc offshore wind farm in France made it possible to show the differences between the studied locations. The supply chain share of the regions surveyed was 2.28% and 6.00% in the CAPEX phase and 5.98% and 8.23% in the OPEX phase. The annual average global value in the CAPEX phase at the country level was EUR 2793 million, and at the regional level, EUR 243 million and EUR 663 million. In the OPEX phase, the corresponding values are EUR 2106 million, EUR 223 million and EUR 663 million. The average annual employment in the CAPEX phase at the national level amounted to 26,323 jobs and at the regional level, 1953 and 5804. In the OPEX phase, employment amounted to 4790, 558 and 751 jobs, respectively. On the other hand, the average annual value added in the CAPEX phase at the national level was EUR 1221 million, and at the regional level, it was EUR 106 million and EUR 290 million. In the OPEX phase, it was EUR 920 million, EUR 97 million and EUR 239 million, respectively. While not all of the findings are conclusive, in general, the domestic offshore wind industry has weaker economic linkages and lower wage levels than the location adopted for comparison. It uses more labour-intensive economic sectors with lower OPEX value added. The results of the analyses presented in this paper are of crucial importance not only for Poland, as their advantage is the possibility to present, from an economic point of view, the profitability of this type of investment in general. [ABSTRACT FROM AUTHOR]

This paper presents a life cycle assessment (LCA) of the International Energy Agency (IEA) 15 MW Reference Wind Turbine (RWT), on floating platforms, deployed in commercial-scale arrays at multiple locations around Scotland in the ScotWind leasing round. Site-specific energy production and vessel operations are provided by a dedicated offshore wind farm operations and maintenance (O&M) model, COMPASS, allowing service operation vessel (SOV) O&M impacts to be assessed with increased confidence. For climate change, the median global warming impact varied from 17.4 to 26.3 gCO2eq/kWh across the four sites within a 95% confidence interval using an uncertainty assessment of both foreground and background data. As is common with other offshore renewable energy systems, materials and manufacture account for 71% to 79% of global warming impact, while O&M comprise between 9% and 16% of the global warming impacts. High-voltage direct current (HVDC) export cables, floating platforms, and composite blades are significant contributors to the environmental impacts of these arrays (by mass and material choice), while the contributions from ballast, vessel transportation emissions, and power-train components are lower. The results suggest that material efficiencies, circularity, and decarbonizing material supply inventories should be a priority for the Scottish floating wind sector, followed by minimizing vessel operations and the decarbonization of vessel propulsion, while avoiding burden shifting to other impact categories. [ABSTRACT FROM AUTHOR]

As large-scale wind turbines are connected to the grid, modeling studies of wind farms are essential to the power system dynamic research. Due to the large number of wind turbines in the wind farm, detailed modeling of each wind turbine leads to high model complexity and low simulation efficiency. An equivalent modeling method for the wind farm is needed to reduce the complexity. For wind farms with widely used doubly-fed induction generators (DFIGs), the existing equivalent studies mainly focus on such continuous control parts as electrical control. These methods are unsuitable for the low voltage ride through (LVRT) part which is discontinuous due to switching control. Based on particle swarm optimization (PSO) and density-based spatial clustering of applications (DBSCAN), this paper proposes an equivalent method for LVRT characteristics of wind farms. Firstly, the multi-turbine equivalent model of the wind farm is established. Each wind turbine in the model represents a cluster of wind turbines with similar voltage variation characteristics. A single equivalent transmission line connects all wind turbines to the power grid. By changing the terminal voltage threshold to enter LVRT, each equivalent turbine can be in different LVRT states. Secondly, an LVRT parameter optimization method based on PSO is used to obtain the dynamic parameters of the equivalent wind turbines. This method of parameter optimization is applicable to the equivalent of LVRT parameters. Thirdly, a clustering method based on DBSCAN is used to obtain suitable clusters of wind turbines. This clustering method can classify wind turbines with similar electrical distances into the same cluster. Finally, two examples are set up to verify the proposed method. [ABSTRACT FROM AUTHOR]

As grid-connected wind farms become more common in the modern power system, the question of how to maximize wind power generation while limiting downtime has been a common issue for researchers around the world. Due to the complexity of wind turbine systems and the difficulty to predict varying wind speeds, artificial intelligence (AI) and machine learning (ML) algorithms have become key components when developing controllers and control schemes. Although, in recent years, several review papers on these topics have been published, there are no comprehensive review papers that pertain to both AI and ML in wind turbine control systems available in the literature, especially with respect to the most recently published control techniques. To overcome the drawbacks of the existing literature, an in-depth overview of ML and AI in wind turbine systems is presented in this paper. This paper analyzes the following reviews: (i) why optimizing wind farm power generation is important; (ii) the challenges associated with designing an efficient control scheme for wind farms; (iii) a breakdown of the different types of AI and ML algorithms used in wind farm controllers and control schemes; (iv) AI and ML for wind speed prediction; (v) AI and ML for wind power prediction; (vi) AI and ML for mechanical component monitoring and fault detection; and (vii) AI and ML for electrical fault prevention and detection. This paper will offer researchers and engineers in the wind energy generation field a comprehensive review of the application of AI and ML in the control methodology of offshore and onshore wind farms so that more efficient and robust control schemes can be designed for future wind turbine controllers. [ABSTRACT FROM AUTHOR]

This paper presents a groundbreaking power distribution technique that focuses on the loss rate of individual wind turbines. Distinct from conventional methods, our strategy prioritizes seamless integration and adaptability within wind farm management systems. By evaluating power losses in specific branches of a wind farm, our approach enhances overall performance by strategically allocating reactive power to reduce cumulative losses. When compared to traditional uniform distribution and Particle Swarm Optimization (PSO) methods, our innovative approach stands out for its superior efficiency and adaptability. Comprehensive simulations underline the strengths and weaknesses of prevailing methods and underscore the superior efficacy of our proposed technique. [ABSTRACT FROM AUTHOR]

One of the main factors for changes in the structure of the energy mix in Poland is the development of renewable energy sources, in particular wind generation. In 2009–2020, the installed capacity of wind sources in Poland increased more than ninefold. At the same time, new legislation significantly curbed the development of onshore wind farms. Further development of wind energy in Poland will rely largely on offshore wind farms. The current state of development of wind power in Poland allows for analyses of the onshore part of wind energy development in Poland. The paper aims to conduct a detailed analysis of the Polish wind sector from an electric power generation perspective. This article presents a comprehensive discussion of the development of onshore wind generation in Poland. In particular, analyses address the production of electric power from wind. Various time horizons are taken into account, as well as the correlation of wind generation with demand for power in the Polish Power System (PPS). The results of the analysis indicate a high variability of wind generation throughout the month or year. The largest wind generation occurred during the night valley, which makes it difficult to operate the power system. In the winter months, wind generation is much greater than in the summer months. Monthly average values of the capacity factor for onshore wind farms (WFs) vary from 0.14 in August to 0.48 in February. Moreover, the coefficient of determination R2 close to zero shows a lack of correlation between offshore wind power generation and real power demand in the PPS. The studied high variability of wind generation in PPS can be mitigated by the wide use of electricity storage systems. Moreover, the obtained results can be part of a model to describe the energy mix in Poland. [ABSTRACT FROM AUTHOR]

Offshore wind energy has become a hot spot in new-energy development due to its abundant reserves, long power generation time, high unit capacity and low land occupation. In response to the current situation whereby wind energy, and natural and human factors have not been taken into account in the selection of sites for offshore wind-energy-resource development in the traditional "21st Century Maritime Silk Road" region, this paper intends to establish a new risk assessment framework that comprehensively considers the influence of wind resources, the natural environment, and the geopolitical and humanistic environment. The rationality of the new index system and weight determination methods are separately investigated. Some interesting results are obtained by comparing the new framework with traditional frameworks. The results show that the Persian Gulf, the Timor Sea in northern Australia, and the northern part of Sri Lanka in southern India are rich in wind-energy resources and have a low overall risk, making them recommended sites. In addition, unlike the results of previous studies, this paper does not recommend the Somali Sea as a priority area for wind-energy siting due to its high geographic humanity risks. [ABSTRACT FROM AUTHOR]

Author Contributions Formal analysis, P.B. and R.R.-F. and E.Z.; writing - original draft preparation, R.R.-F. and E.Z.; writing - review and editing, R.R.-F. and E.Z. All authors have read and agreed to the published version of the manuscript. 10.3390/en14238117 2 Pinciroli L., Baraldi P., Ballabio G., Compare M., Zio E. Deep Reinforcement Learning Based on Proximal Policy Optimization for the Maintenance of a Wind Farm with Multiple Crews. This Special Issue includes seven extended works that have been selected from papers presented at the ESREL 2020 PSAM 15 Conference, the 30th European Safety and Reliability Conference (ESREL 2020) and the 15th Probabilistic Safety Assessment and Management Conference (PSAM 15), jointly held virtually on 1-5 November 2020 to discuss the second wave of the pandemic breakout. [Extracted from the article]

The constantly growing demand for energy, the need to ensure the security of its supply, and the progressing climate changes related to the emission of carbon dioxide and other pollutants have caused, in recent years, an increase in interest in offshore wind energy. This paper presents all the work that needs to be done to build a wind farm in the Baltic Sea. The work focuses on the description of the equipment and the necessary tests to perform in order to analyze the obtained data. The data will allow for unambiguous interpretation and the selection of a convenient location for the construction of a wind farm. The final product of the work is a cost estimate, in which the costs of undertaking such an undertaking are shown. [ABSTRACT FROM AUTHOR]

This paper deals with the creation, in realistic terms, of an offshore wind farm between the Greek islands of Karpathos and Kassos in the Dodecanese complex. In this context, the terms and conditions for the possible existence of an offshore wind park in Greece are analyzed; the technical components of such a project are described; the offshore wind farm, which was designed by the authors, is presented in detail; and the location selected for its installation is assessed. Moreover, the benefits for the islands of Karpathos and Kassos and for the Greek State, as well as financial data adapted to this specific offshore wind farm and SWOT analysis for the two phases of the project, are presented. The authors conclude that an investment in this project would be viable in economic terms and feasible, despite it being a small-scale project. [ABSTRACT FROM AUTHOR]

One of the main problems associated with the generation of wind energy in offshore wind platforms is the analysis of the behavior of the soil when the pile is driven into the seabed. Nowadays, due to the large dimensions of the foundations (hollow steel piles up to 8 m in diameter and 15–20 cm thickness), there are no scale studies carried out that analyze the mechanical and deformational behavior of soil where piles are driven as well as the material of the pile that supports the motor. This paper presents the results obtained from scale submerged tests in a steel pool to analyze the behavior of sand in the presence of water where piles were installed. These tests use a hydraulic press to carry out the penetration of the steel tube in the sand. The results were compared with three different speeds for three tubes with different diameters and two types of termination at the end of the tested element. The results of the submerged tests were compared with the tests in dry conditions and with the results obtained through the finite element Plaxis program. [ABSTRACT FROM AUTHOR]

Solar photovoltaics (PV) continues to grow rapidly across the world and now accounts for a very considerable proportion of all non-fossil-fuel electricity. With the continuing urgency of greenhouse gas abatement, the growth of solar PV is inevitable. Competition with other land uses and the desire to optimize the efficiency of the panels by making use of water cooling are compelling arguments for offshore floating PV (OFPV), a trend that could also benefit from the existing infrastructure recently built for offshore wind farms. Building on our earlier work, we present a larger dataset (n = 82) located around the globe to assess global yield (dis)advantages while also accounting for a modified form of water cooling of the offshore panels. Using our results regarding the Köppen–Geiger (KG) classification system and using a statistical learning method, we demonstrate that the KG climate classification system has limited validity in predicting the likely gains from OFPV. Finally, we also explore a small subset of sites to demonstrate that economics, alongside geography and technology, impacts the feasibility of locating PV panels offshore. [ABSTRACT FROM AUTHOR]

Wind power generation is one of the mainstream renewable energy resources. Voltage stability is as important as the frequency stability of a power system with a high penetration of wind power generation. The advantages of high-voltage direct current (HVDC) transmission systems become more significant with the increase of both installed capacity and transmission distance in offshore wind farms. Therefore, this study discusses various voltage control methods for wind turbines and HVDC transmission systems. First, various voltage control methods of a wind farm were introduced, and they include QV control and voltage droop control. The reactive power of a wind turbine varies with active power, while the active power from each wind turbine may be different owing to wake effects. Thus, QV and voltage droop control with varying gain values are also discussed in this paper. Next, the voltage control methods for an HVDC transmission system, such as power factor control, voltage control, and Vac-Q control, are also summarized and tested in this study. When a three-phase short circuit fault occurs or a sudden reactive power load increases, the system voltage would drop immediately. Thus, various voltage control methods for wind turbines or HVDC can make the system's transient response more stable. Therefore, this study implemented the simulation scenarios, including a three-phase short circuit fault at the point of common coupling (PCC) or a sudden increase of reactive power load, and adopted various voltage control methods, which aim to verify whether additional voltage control methods are effective to improve the performance of transient voltage. The voltage control method has been implemented in PSCAD/EMTDC, and the simulation results show that the QV control performs better than the droop control. In addition, when applying the voltage control technique during a three-phase fault, transient voltage nadir can be improved through either an HVDC transmission system or an AC transmission system. [ABSTRACT FROM AUTHOR]

This paper conducts a comparative analysis of three wind farm simulators, examining the influence of wake on the local wind speed and power output for downstream turbines using experimental data. The study features experiments in three distinct scenarios, evaluating differences among the simulators by calculating the local wind speed and power for each. Each simulator employs a unique wake model, which substantially affects the local wind speed experienced by downstream turbines. Furthermore, the experiment involves adjusting parameter values for each simulator to assess their respective impacts on wind farm performance. The findings of this research are expected to play an important role in investigations related to power optimization and wake effects in the wind farm control. [ABSTRACT FROM AUTHOR]

The modular multilevel matrix converter (M3C) is the core component in low-frequency AC (LFAC) transmission, which is a competitive scheme for offshore wind power integration. In this paper, the M3C control strategy with the reduced switching frequency SM voltage balancing method is proposed. First, based on the conventional αβ0 and dq transformations, the M3C mathematical model is derived. Then, the dual-loop control structure with outer loop and inner loop controllers commonly used in voltage source converters is applied to the M3C. The inner loop controller consists of the current tracking controller in the dq reference frame and the circulating current suppressing controller in the αβ0 reference frame; the outer loop controller is proposed for the offshore wind farm LFAC integration scenario. Additionally, according to the operating characteristics of full-bridge sub-modules (FBSMs), three characteristic variables are defined and a reduced switching frequency SM voltage balancing method based on the nearest level control (NLC) is proposed. Finally, time-domain simulations in PSCAD/EMTDC demonstrate the feasibility of the proposed control strategy. [ABSTRACT FROM AUTHOR]

Offshore wind farms are a current area of interest in Australia due to their ability to support its transition to renewable energy. Climate reanalysis datasets that provide simulated wind speed data are frequently used to evaluate the potential of proposed offshore wind farm locations. However, there has been a lack of comparative studies of the accuracy of wind speed predictions from different reanalysis datasets for offshore wind farms in Australian waters. This paper assesses wind speed distribution accuracy and compares predictions of offshore wind turbine power output in Australia from three international reanalysis datasets: BARRA, ERA5, and MERRA-2. Pressure level data were used to determine wind speeds and capacity factors were calculated using a turbine bounding curve. Predictions across the datasets show consistent spatial and temporal variations in the predicted plant capacity factors, but the magnitudes differ substantially. Compared to weather station data, wind speed predictions from the BARRA dataset were found to be the most accurate, with a higher correlation and lower average error than ERA5 and MERRA-2. Significant variation was seen in predictions and there was a lack of similarity with weather station measurements, which highlights the need for additional site-based measurements. [ABSTRACT FROM AUTHOR]

This paper provides an H∞ robust control strategy for a permanent magnet synchronous generator (PMSG)-based wind farm to realize subsynchronous resonance suppression (SSR) subject to uncertain system distortions and parameter perturbation. Firstly, an eighth-order state space mathematical model of a PMSG-based wind farm is established, including the grid-side converter (GSC), GSC controller, and phase-locked loop (PLL) model. Secondly, the SSR characteristics of a PMSG-based wind farm are analyzed through eigenvalue analysis. Thirdly, a robust subsynchronous damping controller is designed based on eigenvalue analysis of SSR. Finally, the designed robust subsynchronous damping controller is validated with case studies of wind farms. The results show that the controller can increase the stability of PMSG-based wind farm systems and restrain SSR. [ABSTRACT FROM AUTHOR]

During the last decades, wind energy has been developed from an emerging technique of yielding sustainable energy into a robustly established technology due to its renewable, sustainable, and clean features. In addition, a systematic simulation campaign is carried out to estimate the wind turbine Levelized Cost of Energy and then, based on this, the best substructure is chosen and the convenience of the investment is evaluated. [Extracted from the article]

Availability of reliable and extended datasets of recorded power output from renewables is nowadays seen as one of the key drivers to improve the design and control of smart energy systems. In particular, these datasets are needed to train artificial intelligence methods. Very often, however, datasets can be corrupted due to lack of records connected to failures of the acquisition system, maintenance downtime periods, etc. Several recovery (imputation) methods have been used to guess and replace missing data. In this paper, we exploit the matrix completion approach. The available measures of several variables referring to a real onshore wind farm are organized into a matrix in a daily range and the Singular Value Thresholding method is used to carry out the matrix completion process. Numerical results show that matrix completion is a reliable and parameter-free tuning tool to impute missing data in these applications. [ABSTRACT FROM AUTHOR]

With more and more wind turbines coming into operation, inspecting wind farms has become a challenging task. Currently, the inspection robot has been applied to inspect some essential parts of the wind turbine nacelle. The detection of multiple objects in the wind turbine nacelle is a prerequisite for the condition monitoring of some essential parts of the nacelle by the inspection robot. In this paper, we improve the original YOLOX-Nano model base on the short monitoring time of the inspected object by the inspection robot and the slow inference speed of the original YOLOX-Nano. The accuracy and inference speed of the improved YOLOX-Nano model are enhanced, and especially, the inference speed of the model is improved by 72.8%, and it performs better than other lightweight network models on embedded devices. The improved YOLOX-Nano greatly satisfies the need for a high-precision, low-latency algorithm for multi-object detection in wind turbine nacelle. [ABSTRACT FROM AUTHOR]

Tower cost makes up an important part in the whole wind turbine construction especially for offshore wind farms. The main method to reduce tower cost is to reduce tower weight by optimum design. This paper proposes a two-level optimization criterion method for the optimal design of steel conical tower considering different structural reliability and uncertainty, along with the discreteness of design variables such as tower thickness and bolt type. In the first level, the tower shell geometry can be obtained by section design method; in the second level, bolted connections and flanges are designed based on the results of the first level. Then, summarized analysis and iterative calculation is performed to obtain optimum tower design with constant strength and rigidness. This method will play an important role in offshore customized turbine design. [ABSTRACT FROM AUTHOR]

In recent years, due to the global energy crisis, increasingly more countries have recognized the importance of developing clean energy. Offshore wind energy, as a basic form of clean energy, has become one of the current research priorities. In the future, offshore wind farms will be developed in deep and distant sea areas. In these areas, there is a new trend of floating offshore wind platforms replacing fixed wind power platforms, due to their low cost, ease of installation, and independence from the water depth. However, the stability of offshore floating platforms is poor and their power fluctuations are significant; furthermore, they are more prone to failure because of sea wind, waves, and currents. This paper summarizes and analyzes the current research progress and critical technical issues of offshore floating wind power generation, such as stability control technology, integrated wind storage technology, wind power energy management, and long-distance transmission of electricity for floating wind power generation at sea. Finally, future research directions for key offshore wind power technologies are presented. [ABSTRACT FROM AUTHOR]

In the wind energy industry, the power curve represents the relationship between the "wind speed" at the hub height and the corresponding "active power" to be generated. It is the most versatile condition indicator and of vital importance in several key applications, such as wind turbine selection, capacity factor estimation, wind energy assessment and forecasting, and condition monitoring, among others. Ensuring an effective implementation of the aforementioned applications mostly requires a modeling technique that best approximates the normal properties of an optimal wind turbines operation in a particular wind farm. This challenge has drawn the attention of wind farm operators and researchers towards the "state of the art" in wind energy technology. This paper provides an exhaustive and updated review on power curve based applications, the most common anomaly and fault types including their root-causes, along with data preprocessing and correction schemes (i.e., filtering, clustering, isolation, and others), and modeling techniques (i.e., parametric and non-parametric) which cover a wide range of algorithms. More than 100 references, for the most part selected from recently published journal articles, were carefully compiled to properly assess the past, present, and future research directions in this active domain. [ABSTRACT FROM AUTHOR]

This paper presents the application of multi-criteria decision-making (MCDM) for evaluating what technologies using renewable energy sources (RES) for electricity production have the chance to develop in Poland under the current socio-economic conditions. First, the Analytical Hierarchy Process (AHP) method was used to determine the weights of the optimization criteria. Five main criteria and 30 sub-criteria were identified. Next, the authors modified numerical taxonomy (NT) to rank eight RES technologies (such as onshore and offshore wind farms, photovoltaics, or biogas plants). The results show that offshore wind farms are the RES technology with the greatest development opportunities in Poland. The following three technologies: distributed photovoltaic energy, biogas plants, and biomass power plants, respectively, received a similar rating in the ranking. Hydropower and geothermal were the lowest-ranked technologies. The ranking, which is the result of multi-criteria analysis, in several respects, is significantly different from the directions of activities indicated in the state energy policy. [ABSTRACT FROM AUTHOR]

In turn, this requires the ability to clear overhead line faults, either by means of circuit breakers tailored for HVDC applications, providing adequate breaking current ratings at line voltage [[2]], or by adopting converter topologies intrinsically able to interrupt DC fault currents [[3]], i.e., full-bridge or similar. In [[11]], a different DC breaker architecture based on the superconductive elements' double quench is modeled in the software PSCAD/EMTDC, and the fault current interruption is analyzed for two scenarios, i.e., "larger" and "lower" fault current values. Multiterminal DC (MTDC) systems fault analysis and protection is discussed in several papers, either from the perspective of the system or of its components (i.e., DC breakers) [[5]]. Lacking operational DC circuit breakers, DC cables are the only option for HVDC-VSC transmission, but in some cases, cables might be preferred to overhead lines due to their reduced environmental impact and the rather intricate authorization processes which discourage the realization of new overhead power lines. [Extracted from the article]

Many new HVAC power cable installations on wind farms, both on- and offshore, have long lengths. In contrast to traditional power cable connections of a few kilometers, the failures of those systems usually result in much higher repair and unsupplied energy costs. To support the quality assurance of newly installed cable systems as well as to create a sound basis for condition-based maintenance, this paper discusses the technical challenges of the field testing of long-length power cable systems using a damped AC testing method and also discusses the best practical applications for the testing and diagnosis of these wind farm HVAC cable systems. [ABSTRACT FROM AUTHOR]

The need for a verification method for aggregation techniques for passive electrical systems is necessary as power systems increase in complexity. Model reduction is crucial to increase the number of simulations necessary to ensure a stable and reliable design of power systems. This paper presents a novel modal domain-based technique to identify the best aggregation technique for a given system and to indicate the validity of the aggregation. This is done by benchmarking different aggregation techniques and using the dominant contribution factor ratio as a validity parameter. The different aggregation techniques are compared via time-domain simulations against the full detailed model. It is found that (1) the power loss aggregation technique is the most precise when it weighs the equivalent impedances of the parallel feeders, (2) unequal current generation does not impact the aggregation accuracy, (3) individual string aggregation provides the best results for dynamic simulations, and (4) the validity of aggregation decreases as frequency or cable length increases. [ABSTRACT FROM AUTHOR]

Offshore wind farms have boomed worldwide due to the sustainability of wind power and ocean resources. Power grid companies should consider the wind power consumption problem with more power generated. Power-flow calculation is the most fundamental tool in energy management. This paper proposes the convex-relaxation-based method for offshore wind farms' power flow. In this method, the traditional equations' problem solving is transferred into standard convex optimization, which can be solved efficiently with unique optimum. Second-order cone relaxations are imposed to describe the quadratic relationship. The exactness of the relaxation is guaranteed with the special definition of the objective function.The superiority of the proposed method is tested on the case study, for which a computational efficiency improvement is shown. Moreover, the reliability of the power-flow results is verified within the precision tolerance. [ABSTRACT FROM AUTHOR]

There are two situations of transmission redundancy and transmission congestion when large-scale offshore wind farms send power out. The energy storage system can store the power blocked by wind power due to insufficient transmission capacity and release it in the period when the wind power output level is low. In this paper, a full-life-cycle cost model is established for energy storage, and a joint planning model for offshore wind power storage and transmission considering carbon emission reduction benefits is established, which integrates power grid transmission benefits, carbon emission reduction benefits, energy storage construction costs, transmission project construction costs and wind abandonment penalty costs. The channel construction and energy storage configuration scheme with the greatest net benefit can be obtained. The relationship between the transmission channel capacity setting and the energy storage parameter configuration under this model is studied, and the combined effect of transmission channel and energy storage system in improving the level of wind power transmission is analyzed. The sensitivity analysis of the influence of the optimal storage and transmission planning scheme of the offshore wind farms is carried out from the perspectives of transmission line engineering cost and transmission channel curve type. [ABSTRACT FROM AUTHOR]

This paper addresses subsea electric cable routing using the application of decision support systems combined with the experts' knowledge. The methodology is successfully applied to a case study on the Spanish coast. The ranking method calculates the multiple criteria weights, and the weighted product method determines the most suitable space. The environmental criteria, with a weight of 61.4%, exceed the significance of other essential criteria in the study based on experts' considerations. These rankings are input into the model to extract the suitable spaces to deploy the underwater cable. The final result accurately highlights an optimal route in alignment with the experts' preferences. [ABSTRACT FROM AUTHOR]

Voltage source converter based high voltage DC system (VSC-HVDC) has become a very promising solution to integrate offshore wind farm. However, the equivalent inertia of the modern power system with large renewable energy integration becomes small, which will arouse some frequency stability problems. To tackle this problem, this paper proposes an improved frequency regulation strategy for VSC-HVDC integrated offshore wind farm. Firstly, in the frequency decrease stage, the rotor kinetic energy of wind turbines (WTs) is used to suppress the decrease of the frequency, and the control parameters are determined to make full use of the mechanical power and rotor kinetic energy of WTs, the frequency nadir is improved. Secondly, in the rotor speed recovery stage, the DC capacitors of VSC-HVDC are used to release power to compensate the deficiency value of wind farm output power and avoid the secondary frequency drop (SFD) problem. Lastly, the simulation is conducted in PSCAD/EMTDC to validate the effectiveness of the proposed coordinated frequency control strategy. [ABSTRACT FROM AUTHOR]

Smooth power injection is one of the possible services that modern wind farms could provide in the not-so-far future, for which energy storage is required. Indeed, this is one among the three possible operations identified by the International Energy Agency (IEA)-Hydrogen Implementing Agreement (HIA) within the Task 24 final report, that may promote their integration into the main grid, in particular when paired to hydrogen-based energy storages. In general, energy storage can mitigate the inherent unpredictability of wind generation, providing that they are deployed with appropriate control algorithms. On the contrary, in the case of no storage, wind farm operations would be strongly affected, as well as their economic performances since the penalty fees wind farm owners/operators incur in case of mismatches between the contracted power and that actually delivered. This paper proposes a Model Predictive Control (MPC) algorithm that operates a Hydrogen-based Energy Storage System (HESS), consisting of one electrolyzer, one fuel cell and one tank, paired to a wind farm committed to smooth power injection into the grid. The MPC relies on Mixed-Logic Dynamic (MLD) models of the electrolyzer and the fuel cell in order to leverage their advanced features and handles appropriate cost functions in order to account for the operating costs, the potential value of hydrogen as a fuel and the penalty fee mechanism that may negatively affect the expected profits generated by the injection of smooth power. Numerical simulations are conducted by considering wind generation profiles from a real wind farm in the center-south of Italy and spot prices according to the corresponding market zone. The results show the impact of each cost term on the performances of the controller and how they can be effectively combined in order to achieve some reasonable trade-off. In particular, it is highlighted that a static choice of the corresponding weights can lead to not very effective handling of the effects given by the combination of the system conditions with the various exogenous', while a dynamic choice may suit the purpose instead. Moreover, the simulations show that the developed models and the set-up mathematical program can be fruitfully leveraged for inferring indications on the devices' sizing. [ABSTRACT FROM AUTHOR]