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The paper describes a new method for determining the energy efficiency of the life cycles of wind farms by the aggregated data of energy costs. The rationale for the use of aggregated data to determine energy costs during the life cycle of the wind farms is given. The classification of wind turbines and wind farms elements by the parameters and technical characteristics of the elements with subsequent division into groups for which aggregated data of energy costs are determined is given. Within the framework of the method have been developed an algorithm for determining energy costs on the production of elements of wind turbines and wind farms and formulas for their calculation during the life cycle of wind farms. In order to test the method, energy cost was calculated during the life cycle for two wind farms with wind turbines that differ parameters and technical characteristics of the elements and their energy efficiency was determined. It has been shown that the use of a hydrogen storage unit as part of a wind turbine makes it possible to efficiently use energy during down periods and increase the efficiency of the installation by 25–30%. It is noteworthy that a wind-hydrogen farm allows not only to accumulate excess energy during lean periods, but also to save the resource of wind turbines. When the energy reserve in the hydrogen battery reaches close to full, part of the wind turbines of the wind-hydrogen farm can be automatically temporarily stopped in a given order. This technology can provide an extension of the warranty service life for each wind turbine. [ABSTRACT FROM AUTHOR]

The joint probability density function of wind speed and wind direction serves as the mathematical basis for directional wind energy assessment. In this study, a nonparametric joint probability estimation system for wind velocity and direction based on copulas is proposed and empirically investigated in Inner Mongolia, China. Optimal bandwidth algorithms and transformation techniques are used to determine the nonparametric copula method. Various parameter copula models and models without considering dependency relationships are introduced and compared with this approach. The results indicate a significant advantage of employing the nonparametric copula model for fitting joint probability distributions of both wind speed and wind direction, as well as conducting correlation analyses. By utilizing the proposed KDE-COP-CV model, it becomes possible to accurately and reliably analyze how wind power density fluctuates in relation to wind direction. This study reveals the researched region possesses abundant wind resources, with the highest wind power density being highly dependent on wind direction at maximum speeds. Wind resources in selected regions of Inner Mongolia are predominantly concentrated in the northwest and west directions. These findings can contribute to improving the accuracy of micro-siting for wind farms, as well as optimizing the design and capacity of wind turbine generators. [ABSTRACT FROM AUTHOR]

The Wind Farms (WFs) are located far away from the load centres, with the resultant equivalent reactance being more than near the load. It results in a weak grid due to high power transferred in the transmission lines that affect the low frequency of oscillations, and the system exists with undamped functions. The transmission line has to be compensated to transmit wind power effectively. The Static Synchronous Series Compensator (SSSC) connects WF and the load centre. This work demonstrates a Power Oscillation Damper (POD) to WFs and SSSC for transmission lines and their combination. The eigenvalue of the damping ratio and frequency of oscillations are considered objective functions for particle swarm optimization and formulated based on stability to optimize the controller parameter for improving stability. The coordination between the POD and SSSC has been conducted using a Fuzzy Logic Controller (FLC) to further enhance system performance. The small signal and transient stability examinations use eigenvalue analysis and time-domain simulation. It is analysed by varying the length (km) of the transmission line between the WF and the load centre, along with variation in wind penetration. The study observed that small signal stability damped the oscillatory modes most effectively. It is also revealed that the controller's combination with FLC intensifies the capability under extreme disturbances and detects an improvement in the system's transient stability. The proposed approaches' effectiveness is evaluated on an IEEE-11 bus two-area test system with optimized controller gain parameters and controller coordinated FLC through a Real-Time Digital Simulator. [ABSTRACT FROM AUTHOR]

In a wind farm, the grounding circuit is a complex electrical system made up of several interconnected groundings. Its role is very important for the protection of the electrical equipment during a direct lightning strike. To contribute to the optimization of the conception of this complex grounding system in his real configuration (wind turbine towers, grounding grids, and several hundred meters of buried conductor wires ...), we propose in this paper a realistic modeling. Realistic because, to model in all rigors using an electromagnetic field formalism a problem of propagation of electromagnetic transients in electrical device of large geometrical dimensions where the main environment (soil) is not homogeneous does not bring an appreciable advantage and consumes a very high calculation time. Also, the ideal for the engineer is to have a model that is easy to understand, accessible in its theory and obviously preserving the accuracy of the results and with very low computation time. In this work, to study the lightning surges in a wind farm, mainly to know the Ground Potential Rise and the distribution of the currents in the conductors, we use a modeling based on the transmission line equations. Our modeling is carried out by considering the effect of the frequency on the electrical characteristics (resistivity and dielectric permittivity) of the soil; the results we obtain are without loss of precision and with a very short calculation time. [ABSTRACT FROM AUTHOR]

The occurrence of Sub-Synchronous Resonance (SSR) phenomena can be attributed to the interaction that takes place between wind turbine generators and series-compensated transmission lines. The Doubly-Fed Induction Generator (DFIG) is widely recognized as a prevalent generator form employed in wind energy conversion systems. The present paper commences with an extensive exposition on modal analysis techniques employed in a series of compensated wind farms featuring Doubly Fed Induction Generators (DFIGs). The system model encompasses various components, including the aerodynamics of a wind turbine, an induction generator characterized by a sixth-order model, a secondorder two-mass shaft system, a series compensated transmission line described by a fourth-order model, controllers for the Rotor-Side Converter (RSC) and the Grid-Side Converter (GSC) represented by an eighth-order model, and a first-order DC-link model. The technique of eigenvalue-based SSR analysis is extensively utilized in various academic and research domains. The eigenvalue technique depends on the initial conditions of state variables to yield an accurate outcome. The non-iterative approach, previously employed for the computation of initial values of the state variables, has exhibited issues with convergence, lack of accuracy, and excessive computational time. The comparative study evaluates the time-domain simulation outcomes under different wind speeds and compensation levels, along side the eigenvalue analysis conducted using both the suggested and non-iterative methods. This comparative analysis is conducted to illustrate the proposed approach efficacy and precision. The results indicate that the eigenvalue analysis conducted using the proposed technique exhibits more accuracy, as it aligns with the findings of the simulations across all of the investigated instances. The process of validation is executed with the MATLAB program. Within the context of the investigation, it has been found that increasing compensation levels while simultaneously decreasing wind speed leads to system instability. Therefore, modifying the compensation level by the current wind speed is advisable. [ABSTRACT FROM AUTHOR]

With global shifts towards sustainable energy models, the urgency to address rising fossil fuel prices, military conflicts, and climate change concerns has become evident. The article aims to identify the development of wind energy in Poland. This study introduces an integrated methodology for enhancing renewable energy capacities by selecting new construction sites for onshore wind farms across Poland. The proposed methodology utilises a hybrid model incorporating multiple criteria decision-making methods, such as the Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), alongside the semiautomated spatial analysis method using QGiS software (v. 3.32 Lima). The model considers economic, social, and environmental criteria and limitations, offering a comprehensive approach to the decision-making process. It was found that wind farms occupy 460.7 km2 in Poland, with a 250 m buffer around each turbine and a total power capacity of 5818 MW. The results show that an additional 7555.91 km2 of selected areas, 2.34% of the country's area, theoretically offer significant opportunities for wind energy development. The spatial analysis identifies potential sites with promising opportunities for domestic and international renewable energy investors. The study's findings contribute towards achieving national and EU renewable energy targets while offering a replicable framework for informed spatial planning decisions in other regions. [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]

The integration of renewable energy sources into power systems has increased significantly in recent years. Among various types of renewable energy, the use of wind energy is growing rapidly due to its low operating cost, wide distribution worldwide, and no greenhouse gas emissions. However, power systems integrated with wind energy may face stability and reliability issues due to the intermittent nature of wind power. Therefore, in power systems connected to wind farms, it is usually required to use some compensators such as static synchronous series compensator (SSSC) to increase the system performance under abnormal conditions. On the other hand, for an SSSC to be effective in improving the system performance, it must be equipped with a suitable controller. In this paper, a fuzzy logic controller (FLC) is used for the SSSC because of its advantages over conventional controllers. Extensive research has been conducted in power systems with wind turbines in which SSSC or FLC has been used; however, their simultaneous application in such systems has received less attention. Therefore, this article aims to fill this gap. The proposed method is implemented on two power systems and the simulation results are analyzed. In both systems, the dynamic behavior of three different wind farms is examined. In the first and second wind farms, either a squirrel cage induction generator (SCIG) or doubly-fed induction generator (DFIG) are used, whereas in the third one which is a combined wind farm (CWF), an equal number of SCIG and DFIG are employed. In wind farms with SCIG or DFIG, an SSSC is also utilized. Furthermore, an FLC is employed for the SSSC to improve its efficacy. A proportional integral (PI) controller is also considered for the SSSC, and its results are compared with FLC results. The simulation results confirm the superiority of FLC over PI controller. [ABSTRACT FROM AUTHOR]

The development of offshore wind farms requires robust bonding solutions that can withstand harsh marine conditions for the easy integration of secondary structures. This paper investigates the durability performance of two adhesives: Sikadur 30 epoxy resin and Loctite UK 1351 B25 urethane-based adhesive for use in offshore wind environments. Tensile tests on adhesive samples and accelerated aging tests were carried out under a variety of temperatures and environmental conditions, including both dry and wet conditions. The long-term effects of aging on adhesive integrity are investigated by simulating the operational life of offshore installations. The evolution of mechanical properties, studied under accelerated aging conditions, provides an important indication of the longevity of structures under normal conditions. The results show significant differences in performance between the two adhesives, highlighting their suitability for specific operating parameters. It should also be noted that for both adhesives, their exposure to different environments (seawater, distilled water, humid climate) over a prolonged period showed that (i) Loctite adhesive has a slightly faster initial uptake than Sikadur adhesive, but the latter reaches an asymptotic plateau with a lower maximum absorption rate than Loctite adhesive; and (ii) a progressive deterioration in the tensile properties occurred following an exponential function. Therefore, aging behavior results showed a clear correlation with the Arrhenius law, providing a predictive tool for the aging process and the aging process of the two adhesives followed Arrhenius kinetics. Ultimately, the knowledge gained from this study is intended to inform best practice in the use of adhesives, thereby improving the reliability and sustainability of the offshore renewable energy infrastructure. [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]

Wind energy in the atmospheric boundary layer serves as the primary source for energy absorption and structural load on wind turbines. However, the impact of turbulent coherent structures on the aerodynamic performance and wake characteristics of wind turbines has not been comprehensively evaluated. In this study, the proper orthogonal decomposition (POD) method is employed to assess the influence of turbulent coherent structures of varying scales on the aerodynamic performance and wake characteristics of wind turbines in the neutral atmospheric boundary layer. The results show that turbulent coherent structures are the main factor that determines the wind velocity fluctuation, aerodynamic performance and wake characteristics of wind turbine in the atmospheric boundary layer. When considering the 13th or lower order POD mode, the wind velocity fluctuation increases with the increase of energy content (more POD modes) of the turbulent coherent structures. When considering the first 19 POD modes, the dynamic loads and power of wind turbine fluctuate with high frequencies, the thrust fluctuates in an amplitude range between 2.4 % and 13.9 % around the mean value, and the power fluctuates from 4.5 % to 28.6 % of the mean value. When considering the first 40 POD modes, the average power generation of the wind turbine increases by 26 % compared to the case with no turbulent structures considered. The study of turbine wake shows that turbulent coherent structures can expand the wind turbine wake approximately to a width of 2.5 D and a height of 3 D (D is the diameter of the wind turbine), offset the wake approximately to 2 D , and move forward the position of the wake vortex beginning to dissipation approximately to 7 D behind the wind turbine. In addition, turbulent coherent structures can accelerate the wake velocity recovery by increasing the momentum exchange between the atmospheric boundary layer and wind turbine wake. • A POD-based inflow generation method is established for wind turbine simulation. • Study into the coherent structures with various energy contributions on wind turbine performance. • Obtained the most influence energy contribution of coherent structures in the ABL. • Unveil the influence of coherent structures on the expansion and deflection of wind turbine wakes. [ABSTRACT FROM AUTHOR]

This study aims to conduct resource assessments at five offshore locations (L1–L5) in the Gulf of South Suez for possible development of wind farms. For this purpose, the hourly mean wind speed and direction data at 100 m above mean sea level (AMSL) and other meteorological data at near water surface from ERA5 (fifth-generation reanalysis for the global climate weather) is used. Statistical analyses, wind power, energy estimation, plant capacity factor, etc., have been performed using Windographer software. The cost of energy and greenhouse gas emissions are conducted based on international installation cost per kW and emissions factor per kWh from the literature. The data covers 43 years, between 1979 and 2021. The results show that at L1 to L5 locations, the long-term mean wind speed (WS) and wind power density (WPD) values are 8.678 m/s and 533 W/m2, 4.371 m/s and 78 W/m2, 8.917 m/s and 587 W/m2, 7.856 m/s and 406 W/m2, 8.072 m/s and 453 W/m2, and 7.876 m/s and 406 W/m2 at 100 m ASL, respectively. Based on the site-specific parameters (WS, WPD, WPC, MWVI, MWSI, AWVI, AWSI, minimum zero power, maximum rated power, PCF, COE, and maximum wind duration), values of 8.917 m/s, 587 W/m2, 1.125, 34.92, 0.358, 101.9, 6.26%, 5.76%, 54.04%, 0.007 USD/kWh, and 91%; L2 are identified as the most relevant area for wind farm development among the studied locations. At L2 site, the wind turbine WT2 can deliver annually 21.266 GWh of energy at respective plant capacity factors of 48.55%. [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]

The development of green technology in the world is progressing extremely rapidly. New possibilities for obtaining energy from renewable sources are constantly being sought and existing solutions are being improved. The multifaceted potential of the seas and oceans is an important aspect being taken into account in the development of the energy systems of a number of economies. One dimension of action in this area is the orientation towards offshore wind energy and the construction of offshore wind farms for this purpose. The purpose of this article is to analyse the importance of offshore wind farms in Poland's energy system and to assess public perception of the changes taking place in this dimension. The article is based on research and critical analysis of the available literature, legal regulations and industry reports, as well as on the results of our own surveys, the scientific findings of which were developed with the application of statistical instruments using PQstat software, ensuring the expected quality of results. The findings of the article indicate the significant importance of offshore wind farms in the creation of Poland's energy mix, with differing public attitudes towards their construction. Furthermore, the results of the research indicate a differentiated attitude of society towards the construction of offshore wind farms. The main motivation for majority support of the measure in question are economic reasons, which are connected with the expectation of a real price reduction per 1 kW of energy, as well as increased attractiveness of the region due to investments in this area. The main concern with the measure relates to environmental aspects, with concerns about the functioning of ecosystems in light of the construction and subsequent operation of wind farms. Negative public opinion is also signalled in relation to the potential risk of landscape change in a direction that is undesirable for the studied developed coastal tourist region in Poland. [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]

The energy produced from renewable sources (solar, wind, hydro, geothermal, and biomass) provides direct access to clean and safe energy. Offshore wind energy, generated through wind farms, has traditionally relied on fixed structures, whereas innovative floating structures have been commercially applied since 2017. This study investigates offshore areas in Montenegro suitable for wind farm construction. Research on average annual wind speeds has successfully identified a surface area deemed suitable for constructing a wind farm in the Montenegrin part of the Adriatic Sea. Analysis of available bathymetric databases has pinpointed technical solutions for the supporting structures of wind turbines required to construct an offshore wind farm. Applying an assessment method to the defined surface of Montenegrin waters, seven blocks have been identified as suitable for wind farm construction. The research results indicate that wind farms can be built in Montenegrin waters with a technical potential corresponding to a total capacity of 2299.794 MW, which includes 2034.48 MW for floating structures, 126.759 MW for fixed structures, and 138.555 MW for jacket-fixed structures. [ABSTRACT FROM AUTHOR]

As the adoption of wind energy as a key renewable energy source accelerates, precise power flow analysis becomes crucial for accurate power delivery forecasting. This paper addresses the inherent uncertainties in wind speed data at different wind farm locations by conducting a sensitivity analysis to assess wind farm pairs. The analysis accommodates various data sizes, namely, short, medium, and large, and diverse spatial relationships between wind farms. By leveraging National Renewable Energy Laboratory wind speed data from nine distinct wind farms, the dependence structure between wind farm pairs is modeled using copulas. This modeling takes both the wind speed knowledge level and the various spatial interplays among the wind farm pairs into consideration. The findings indicate an inverse proportionality between the strength of dependence and the distance separating the wind farm pairs. [ABSTRACT FROM AUTHOR]

With increasing number and proximity of wind farms, it becomes crucial to consider wind farm effects (WFEs) in the numerical weather prediction (NWP) models used to forecast power production. Furthermore, these WFEs are also expected to affect other weather-related parameters at least locally. Thus, we implement the explicit wake parameterization (EWP) in the NWP model HARMONIE–AROME (hereafter HARMONIE) along-side the existing wind farm parameterization (WFP) by (FITCH). We evaluate and compare the two WFPs against research flight measurements as well as against similar simulations performed with the Weather Research and Forecasting (WRF) model using case studies. The case studies include a case for WFEs above a wind farm as well as two cases for WFEs at hub height in the wake of farms. The results show that EWP and FITCH have been correctly implemented in HARMONIE. For the simulated cases, EWP underestimates the WFEs on wind speed and strongly underestimates the effect on turbulent kinetic energy (TKE). FITCH agrees better with the observations, and WFEs on TKE are particularly well captured by HARMONIE–FITCH. After this successful evaluation, simulations with all wind turbines in Europe will be performed with HARMONIE and presented in the second part of this paper series. [ABSTRACT FROM AUTHOR]

Unexploded ordnance (UXO), often deployed in WWI and WWII, are still present on the seabed posing a risk to seabed construction. UXO surveys identify potential UXO targets which are then investigated and removed where necessary; however, approximately 96 per cent of targets investigated on projects included in this study were non-UXO (false positives). Here we investigate methods of improving statistical confidence in targets picked through the improved classification of magnetic response, utilizing simulation methods and historic data. A simulation of the induced magnetism of UXO was developed to model the most likely dimensions and orientation of a given source item. Modelling results and measured variables were combined in an optimization algorithm, hereon referred to as 'the classifier'. We document the results of integrating the magnetic responses of 3027 targets from 18 offshore wind projects into the classifier. Five of these projects were performed as tests in which the target results were unknown during classification. Finally, the classifier was deployed on a live project, Hollandse Kust Zuid 3 and 4 Offshore Wind Farm, in which it enabled the removal of 67 targets from the from the 1200-target investigation list. The classifier proved to be a valuable additional tool to assist the target rationalization process, reliably and repeatably distinguishing UXO from other items, thereby reducing false positives and repeatably demonstrating no threshold UXO false negatives. Assumptions and limitations of this methodology were highlighted, which must be understood and considered when integrating this approach on future projects. [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]

Wind profiling within operating wind farms is important for both wind resource assessment and wind power prediction. With increasing wind turbine size, it is getting difficult to obtain wind profiles covering the turbine-affecting area due to the limited height of wind towers. In this study, a stepwise quality control and optimizing process for deriving high-quality near-surface wind profiles within wind farms is proposed. The method is based on the radial wind speed obtained by the Doppler Wind Lidar velocity-azimuth display (VAD) technique. The method is used to obtain the whole wind profile from ground level to the height affected by wind turbines within a utility-scale onshore wind farm, in northern China. Compared with the traditional carrier-to-noise ratio (CNR) filter-based quality control method, the proposed data processing method can significantly improve the accuracy of the derived wind. For a 10 m wind speed, an increase in coefficient of determination (R2) from 0.826 to 0.932, and a decrease in mean absolute error (MAE) from 1.231% to 0.927% are obtained; while for 70 m wind speed, R2 increased from 0.926 to 0.958, and MAE decreased from 1.023% to 0.771%. For wind direction, R2 increased from 0.978 to 0.992 at 10 m, and increased from 0.983 to 0.995 at 70 m. The optimized method also presents advantages in improving the accuracy of derived wind under complex wind environments, e.g., inside a wind farm, and increasing the data availability during clear nights. The proposed method could be used to derive wind profiles from below the minimum range of a vertically operating scanning Doppler Lidar to a height affected by wind turbines. Combined with Doppler beam-swinging (DBS) scanning data, the method could be used to obtain the complete wind profile in the boundary layer. These wind profiles could be further used to predict wind power and evaluate the climate and environmental effects of wind farms. [ABSTRACT FROM AUTHOR]

Planning logistical processes supports the managerial processes of an enterprise, including investments such as wind farm construction. The aim of the article is to analyze and assess the time determinant in the logistical process of wind farm planning. The research method involves the analysis of a case study on the investment planning of a wind farm (WF) in Poland from 2008 to 2020. The Critical Path Method (CPM) was applied to the planning and scheduling of projects and logistical planning processes at WF Barwice. As a result of the research efforts, which included the identification of stages, time frames, critical paths, and construction conditions, the outcome is a concept for optimizing the logistical process of wind farm planning. The main problem associated with the planning of this investment was the analysis and evaluation of the environmental factors that would impact upon a positive assessment of the construction of WF Barwice. The outcome is the optimization of the time determinant in the logistical process of wind farm planning from 14 years to 10; however, legal, administrative, and environmental constraints have influenced the achieved result. [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]

As an important migratory bird habitat along the East Asian-Australasian route, the coastal wetlands along the Yellow Sea have experienced significant human losses and threats due to the impact of wind farms. In this study, the radar data was adopted to examine and analyse the spatial and temporal changes of the human-made characteristic areas that caused the change of the migration route of birds in the Yellow Sea from 2015 to 2022. The results show that the areas of impact zones in the study area on water of the Yellow Sea, during the last 8 years, increased 14 times, from 35.7 km2 to 506.3 km2. The areas of impact zones in the study area on land, during the last 8 years, increased almost two times, from 303.4 km2 to 544.2 km2, which also has a serious impact on the number of migratory birds. Therefore, China should carefully evaluate the impact and potential threat of domestic wind farms under operation and construction on birds and other wildlife, and provide scientific solutions for the site selection of new wind farms. [ABSTRACT FROM AUTHOR]

There is an urgent need to develop accurate predictions of power production, wake losses and array–array interactions from multi-GW offshore wind farms in order to enable developments that maximize power benefits, minimize levelized cost of energy and reduce investment uncertainty. New, climatologically representative simulations with the Weather Research and Forecasting (WRF) model are presented and analyzed to address these research needs with a specific focus on offshore wind energy lease areas along the U.S. east coast. These, uniquely detailed, simulations are designed to quantify important sources of wake-loss projection uncertainty. They sample across different wind turbine deployment scenarios and thus span the range of plausible installed capacity densities (ICDs) and also include two wind farm parameterizations (WFPs; Fitch and explicit wake parameterization (EWP)) and consider the precise WRF model release used. System-wide mean capacity factors for ICDs of 3.5 to 6.0 MWkm−2 range from 39 to 45% based on output from Fitch and 50 to 55% from EWP. Wake losses are 27–37% (Fitch) and 11–19% (EWP). The discrepancy in CF and wake losses from the two WFPs derives from two linked effects. First, EWP generates a weaker 'deep array effect' within the largest wind farm cluster (area of 3675 km2), though both parameterizations indicate substantial within-array wake losses. If 15 MW wind turbines are deployed at an ICD of 6 MWkm−2 the most heavily waked wind turbines generate an average of only 32–35% of the power of those that experience the freestream (undisturbed) flow. Nevertheless, there is no evidence for saturation of the resource. The wind power density (electrical power generation per unit of surface area) increases with ICD and lies between 2 and 3 Wm−2. Second, EWP also systematically generates smaller whole wind farm wakes. Sampling across all offshore wind energy lease areas and the range of ICD considered, the whole wind farm wake extent for a velocity deficit of 5% is 1.18 to 1.38 times larger in simulations with Fitch. Over three-quarters of the variability in normalized wake extents is attributable to variations in freestream wind speeds, turbulent kinetic energy and boundary layer depth. These dependencies on meteorological parameters allow for the development of computationally efficient emulators of wake extents from Fitch and EWP. [ABSTRACT FROM AUTHOR]

It is observed that the number of onshore wind farms that reach the end of their service life is continually increasing. The decision-making process that defines the future of the farm is a challenge for the owners. This systematic review aimed to identify which factors influence the decision-making process at the end-of-life cycle of onshore wind farms. In accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol, a research strategy was developed and used the Scopus, Web of Science and EMBASE databases. Initially, 2767 articles were identified, but, after double-blind screening, 26 articles were analyzed in full. The scarcity of studies on this topic and little elucidation are limitations of this review. The results include (i) a systematization of six options for decision making, (ii) thirteen factors influencing the decision-making process associated with categories of external factors (logistics and infrastructure aspects, regulatory aspects and public policies, national energy guidelines, the technological development of the sector); and internal factors (economic/financial, operational and environmental aspects). It is concluded that most of the publications consist of simulations and theoretical studies highlighting a bottleneck in experiences and feasible data to support decisions at the end of service life. It is highlighted that most of the studies showed that partial decommissioning with partial repowering, as well as total decommissioning, were the most feasible options for the end-of-life cycle, with aspects related to public policies and regulatory aspects, as well as environmental, operational and economic/financial aspects, being the most influential, especially due to the wake effect, operation and maintenance costs (OPEX) and the protection of guarantees and incentives for operation in a new operating cycle. [ABSTRACT FROM AUTHOR]

This paper proposes a virtual inertia control strategy for wind farms based on auto disturbance rejection controller with artificial bee colony (ABC) algorithm. First, based on the system frequency dynamic response equation, an active disturbance rejection controller is designed according to the non‐linear feedback control law and the extended state observer to improve the anti‐interference capability of the virtual inertia control system. Second, in order to solve the problem of difficulty in tuning the parameters of the active disturbance rejection control (ADRC), an ABC algorithm based on nectar collection behaviour was proposed to iteratively optimize the parameters of ADRC. Finally, the proposed control method is effectively verified based on Matlab/Simulink. The simulation results show that compared with traditional algorithms, the proposed ABC‐ADRC can effectively control the rotor speed to adjust the frequency of the power grid system, achieve power sharing and adaptive noise elimination, reduce the complexity of parameter settings, not only improve anti‐interference ability, but also enhance the robustness of the system. [ABSTRACT FROM AUTHOR]

Far distant wind farms are integrated nowadays with the help of Voltage Source Converter (VSC)-based HVDC grids. Rapid fault current is very common in VSC-based HVDC grids and, therefore, quick fault detection and fast executing protection methods are critical for the existence of the HVDC grids. This paper proposes a rise time-based fault detection method using local measurement data and Travelling Wave (TW) characteristics of incoming fault TW. Dominating frequency of the primary wavefront is computed by the rise time of incoming fault TW. With the help of auto-updating transmission line parameters and the dominating frequency of incoming TW, the fault location is identified. The performance of the proposed method has been observed in PSCAD Simulation with a 4-Terminal HVDC test grid in multiple scenarios and compared with the existing fault detection methods on multiple levels. The results show that the proposed method is very fast, and accurate and can complete the whole Fault Location process within a few microseconds just after the Inception of the fault. [ABSTRACT FROM AUTHOR]

Wind power is commonly used to reduce greenhouse gas emissions but often has negative effects on biodiversity. In this study, I investigated the effects of wind farm and power line construction on the territory status of the Eurasian goshawk Accipiter gentilis, whether fledglings were produced or not, and the number of fledglings. Included were 55 goshawk territories investigated before and after the construction period. I found that the territory status declined significantly in the influence area within 3 km from the disturbance compared to the control area more than 7 km away. Interestingly, the decline in territory status was similar in the distance categories 0–1 km, 1–2 km, and 2–3 km, while there was nearly no change in territory status in the control area, thus indicating that the influence area from this kind of disturbance was minimum 3 km from the nest. The number of breeding pairs declined significantly during the construction period only in the influence area. Possible reasons might be higher mortality caused by collisions with power lines, desertion, avoidance of the areas with noise and disturbance from the constructions, and possible indirect effects caused by reductions in prey species. I found no effects of the construction on the number of fledglings. [ABSTRACT FROM AUTHOR]

Offshore wind farms (OWFs) are a key part of efforts to mitigate the impacts of climate change. However, they have the potential to negatively impact seabird species through collisions with turbine blades, displacement from preferred foraging habitat and the perception of wind farms as a barrier to migrating or foraging birds. Whilst the data available to model these impacts are increasing, many data gaps remain, particularly in relation to the impacts of barrier effects. We analyse the movements of Sandwich terns in relation to an offshore wind farm cluster using data collected as part of a multi-year GPS tracking study. Over the course of the study, two additional wind farms were built within the home range of the breeding colony. The construction of these wind farms coincided with a change in the foraging and commuting areas used by breeding terns. Whilst birds entered OWFs when foraging, they appeared to avoid them when commuting, driving an apparent 'funnelling' effect to important feeding locations. We discuss if this could be driven by changes to the prey base, subsequent displacement and potentially altered routes reflecting new favourable airflow patterns following OWF construction. Our results suggest that behavioural responses of birds to OWFs may be the result of a complex series of ecological and environmental interactions, as opposed to simplistic assumptions around the perception of the OWF as a barrier to movement. [ABSTRACT FROM AUTHOR]

Stability-dependent far-field offshore wind-farm wakes are detected in Supervisory Control and Data Acquisition (SCADA) wind power records from wind farms located in the North Sea. The results are used to assess the strengths and weaknesses of the Openwind engineering model, which in turn enables understanding of the wake signal captured by the SCADA data. Two experimental model set-ups are evaluated, the current standard set-up considering a neutral atmosphere and extended for stable conditions, and the other using a new atmospheric stability implementation called the far-wake atmospheric stability model (ASM) previously reported in Energies. The ASM approach enables the identification within wind power records of wakes of length at least 30 km depending on the atmospheric stability. The ASM approach would be useful for assessing which neighboring wind farms are likely to affect the wind turbine power output and to what extent the power output is affected by stability. [ABSTRACT FROM AUTHOR]

Existing fault localization methods for power lines are not applicable to the collector line in onshore wind farms due to the dense access of complex power supplies. Therefore, a fault localization method based on equivalent zero‐sequence injection current (ZIC) is proposed for asymmetric phase‐to‐ground faults on collector lines. Firstly, the idea of load shifting is adopted to generalize the theory of equivalent injection current (EIC) to multi‐terminal and meshed lines. Then, considering features of the zero‐sequence network of wind farms, the EIC theory on two‐terminal and multi‐terminal lines is applied to zero‐sequence networks, and thus faulty areas, faulty sub‐lines, and fault distance can be determined. Attractively, the element correlation in node impedance matrices of zero‐sequence networks is derived from the network branch‐addition process, and the numerical characteristic of matrix elements is further revealed from the particularity of wind farms, based on which root‐mean‐square (RMS) calculation of ZIC can be improved to enable the localization without phasor measurement. Verification results prove that this proposed method can accurately realize the fault localization independent of wind turbine generators with a few measurement points, and the applicability of collector lines with line branches is also considered; additionally, only voltage RMS needs to be measured. [ABSTRACT FROM AUTHOR]

Despite the promising outlook, the numerous economic and environmental benefits of offshore wind energy are still compromised by its high Operations and Maintenance (O&M) expenditures. On one hand, offshore-specific challenges such as site remoteness, harsh weather, transportation requirements, and production losses, significantly inflate the O&M costs relative to land-based wind farms. On the other hand, the uncertainties in weather conditions, asset degradation, and electricity prices largely constrain the farm operator's ability to identify the time windows at which maintenance is possible, let alone optimal. In response, we propose STOCHOS, short for the stochastic holistic opportunistic scheduler—a maintenance scheduling approach tailored to address the unique challenges and uncertainties in offshore wind farms. Given probabilistic forecasts of key environmental and operational parameters, STOCHOS optimally schedules the offshore maintenance tasks by harnessing the opportunities that arise due to favorable weather conditions, on-site maintenance resources, and maximal operating revenues. STOCHOS is formulated as a two-stage stochastic mixed-integer linear program, which we solve using a scenario-based rolling horizon algorithm that aligns with the industrial practice. Tested on real-world data from the U.S. North Atlantic where several offshore wind farms are in-development, STOCHOS demonstrates considerable improvements relative to prevalent maintenance benchmarks, across various O&M metrics, including total cost, downtime, resource utilization, and maintenance interruptions. [ABSTRACT FROM AUTHOR]

The article describes the information and logical model (ILM) of the database of accounting and movement of equipment of wind turbines of the Ermentau wind farm in the Akmola region. IFM is implemented in accordance with the IDEF1X methodology. The relationships of entities are shown and analyzed, the types of connections, the use of primary and foreign keys are determined. The application of the IDEF1X methodology used in the development of relational databases is shown, the conditional syntax is specially designed to build a conceptual scheme. The advantages of the IDEF1X methodology are described. [ABSTRACT FROM AUTHOR]

Wind farm design generally relies on the use of historical data and analytical wake models to predict farm quantities, such as annual energy production (AEP). Uncertainty in input wind data that drive these predictions can translate to significant uncertainty in output quantities. We examine two sources of uncertainty stemming from the level of description of the relevant meteorological variables and the source of the data. The former comes from a standard practice of simplifying the representation of the wind conditions in wake models, such as AEP estimates based on averaged turbulence intensity (TI), as opposed to instantaneous. Uncertainty from the data source arises from practical considerations related to the high cost of in situ measurements, especially for offshore wind farms. Instead, numerical weather prediction (NWP) modeling can be used to characterize the more exact location of the proposed site, with the trade-off of an imperfect model form. In the present work, both sources of input uncertainty are analyzed through a study of the site of the future Vineyard Wind 1 offshore wind farm. This site is analyzed using wind data from LiDAR measurements located 25 km from the farm and NWP data located within the farm. Error and uncertainty from the TI and data sources are quantified through forward analysis using an analytical wake model. We find that the impact of TI error on AEP predictions is negligible, while data source uncertainty results in 0.4%–3.7% uncertainty over feasible candidate hub heights for offshore wind farms, which can exceed interannual variability. [ABSTRACT FROM AUTHOR]

Static axial induction control and tilt control are two strategies that have the potential to increase power production in wind farms, mitigating wake effects and increasing the available power for downstream turbines. In this study, wind tunnel experiments are performed to evaluate the efficiency of these two techniques. First, the axial induction of upstream turbines in wind farms comprising two, three, and five turbines is modified through the tip-speed ratio. This strategy is found to be ineffective in increasing power extraction. Next, the power extraction and flow through a two-turbine wind farm are evaluated, considering different tilt angles for the upstream turbine, under two levels of incoming flow turbulence intensities and turbine spacing distances. It is shown that forward tilting increases the overall power extraction by deflecting the wake downwards and promoting the entrainment of high-speed fluid in the upper shear layer, regardless of the turbine spacing distance and turbulence intensity level. Also, the wake is seen to recover faster due to the increased shear between the wake and the outer flow. Tilting a turbine backward deflects the wake upwards and pulls low-speed flow from under the turbine into the wake space, increasing the available power for downstream turbines, but it is not enough to increase global power extraction. Moreover, since the wake deflection under backward tilting is not limited by ground blockage, it leads to larger secondary steering compared with forward tilting. Finally, it is demonstrated that the secondary steering of the downstream turbine's wake influences the flow encountered by a turbine positioned farther downstream. [ABSTRACT FROM AUTHOR]

The expansion of offshore wind farms into deeper waters presents economic challenges due to the rising costs of operation and maintenance. To address this issue, the development of targeted opportunistic maintenance strategies for offshore wind farms is crucial. Existing strategies often overlook the interconnections between maintenance activities across wind farms, focusing solely on individual wind farms. However, joint maintenance of wind farms has been acknowledged as an effective approach to reducing maintenance costs at the operational level. This paper introduces an opportunistic maintenance strategy that considers the joint maintenance of two wind farms and establishes reliability thresholds to guide maintenance decisions. Furthermore, the developed maintenance model is improved by incorporating more realistic vessel models and considering various types of maintenance costs. Conclusions can be drawn from a comprehensive analysis of optimization results across multiple scenarios involving maintenance costs, wind farm parameters, and uncertainties. The comparative analysis demonstrates that, in the farthest offshore distance case, the proposed strategy exhibits a reduction in maintenance costs of 15.67% and 4.87% when compared to two traditional strategies, respectively. This effect is further amplified in scenarios where offshore wind farms are located in close proximity to each other and encounter substantial uncertainties. • Developing a novel joint maintenance strategy for two offshore wind farms. • New decision-making structure is established using three decision thresholds. • The strategy is evaluated considering cost, wind farm parameters, and uncertainty. • The proposed strategy saves 15.67% and 4.87% in LCC versus traditional strategies. [ABSTRACT FROM AUTHOR]

Because of the growing demand for floating wind turbines with a limited number of floating prototypes, offshore wind farms require a hybrid arrangement of fixed and floating wind turbines. Studying the wake characteristics of bottom-fixed and floating wind turbines, as well as the layout optimization of hybrid wind farms, is important for utilizing more wind energy through hybrid wind farms. In this study, numerical simulations based on the fully coupled aero-hydro-servo-elastic method and the dynamic wake meandering model were performed to investigate wind turbines arranged in tandem. First, the wake and dynamic aerodynamic characteristics were used to verify the accuracy of FAST.Farm. Subsequently, numerical simulations were conducted on two tandem offshore NREL 5-MW wind turbines under different arrangements to study the differences in wake characteristics, dynamic behavior, and optimized layout between floating and bottom-fixed turbines. The results indicate that compared with bottom-fixed turbines, floating turbines exhibit faster wake recovery, resulting in less impact on downstream wind turbines. Although they possess lower individual power, they ensure higher power for the downstream turbines. In a hybrid arrangement, it is advisable to position the floating turbines upstream to optimize the overall power output. • Research the interactions of tandem wind turbines with different arrangements. • Optimize the arrangement for maximizing the total power of the wind farm. • Analyze the total power variation as spacing changes. [ABSTRACT FROM AUTHOR]

Active yaw control (AYC) is a promising technique to improve the power performance of wind farms. In this work, a novel analytical model for yawed wind turbines, considering the effects of yaw angle, turbulence intensity and thrust coefficient, is developed to predict the velocity deficit and the wake deflection. The model is derived based on the mass and momentum conservation, and the assumption of the cosine distribution for the velocity deficit in turbine wakes. The comparisons with wind-tunnel measurements of different yaw angles and large-eddy simulation (LES) of different atmospheric turbulence levels show that the model predictions are in good agreement with the experimental and numerical results. A wind-farm controller is developed by incorporating the newly developed wake model, the Linear Sum (LS) cumulative wake model and the Serial-Refine power optimization method. The developed controller is applied to the power optimization in the Horns Rev offshore wind farm. It is found that yaw control is not required for the last-row turbines whose wakes do not influence the downstream ones. All turbines are found to yaw in the same direction due to the secondary wake steering, which is favorable to the wind-farm control. Moreover, the AYC technique is more beneficial to the power improvement around the full-wake wind directions associated with shorter turbine spacing. The local maximum of power improvement occurs at the wind angles that slightly deviate from the full-wake ones (± 5 ∘ in the Horns Rev wind farm). • A novel analytical yawed wake model is developed. • The model is validated by wind-tunnel experiments and large-eddy simulations. • An active yaw control (AYC) framework is developed. • The AYC technique is applied to wind-farm power optimization. [ABSTRACT FROM AUTHOR]

This study examines the impact of bias correction on the prediction of offshore wind power ramp events (WPREs) using NOAA's High-Resolution Rapid Refresh (HRRR) model. The analysis focuses on New England's offshore region, using Light Detection and Ranging (LiDAR) wind observations and the power curve derived from the nearby Block Island wind farm as a reference. The study characterizes bias in terms of amplitude and phase, finding a 30-min systematic lag error and a marginal underestimation of high wind speeds. Perfect bias correction treatments including both the amplitude and the phase are applied to HRRR wind speed, and their impact on WPREs is assessed using categorical performance measures. A large discrepancy in the number of cases with HRRR having much fewer cases than the reference is found, which is attributed to the model's temporal and spatial resolution. The results show that the amplitude bias correction has a marginal impact on reducing frequency bias, while the dynamic time warping (DTW) used in the phase bias correction shows promising results but limited performance. The study concludes that phase bias correction can be a feasible option to reduce bias in WPREs in offshore power systems. [ABSTRACT FROM AUTHOR]

• The criterion based on high-frequency inductance difference coefficients is built. • The method can accurately identify varied types of faults at different locations. • The criterion differs by two orders of magnitude for internal and external faults. • The method uses logical information for communication, enabling fast identification. • The method proposed is immune to effects of fault resistance. Conventional protection schemes for wind farm-flexible flexible direct current (DC) system transmission lines are susceptible to malfunctions in external fault scenarios and exhibit limited immunity to fault resistance in internal fault scenarios. In the pursuit of enhancing pilot protection performance, a novel protection method based on high-frequency inductance difference coefficients is proposed. Firstly, the fault transient characteristics of both the wind farm and the flexible DC converter are analyzed, deriving their respective transient models. Subsequently, a high-frequency fault component network comprising inductive impedances is constructed. Then, a protection criterion based on high-frequency inductance difference coefficients is formulated. Finally, the proposed method is subjected to simulation tests on the RT-LAB platform. The results validate its capability to accurately identify the locations of internal and external faults, demonstrating robust immunity to fault resistance. Because it operates independently of synchronous information interaction, it functions rapidly. [ABSTRACT FROM AUTHOR]

• The similarities and differences of inertia response between SG and DFIG are analyzed and compared. • An analytical model of DFIG with inertia control is developed for studying frequency dynamics considering aerodynamics and rotor side power of wind turbine. • The virtual inertia function is derived accounting for the differences between SG and DFIG, and the key factors affecting virtual inertia are analyzed. • An optimal design approach of virtual inertia is constructed and solved for improving system frequency trajectory. • The effectiveness and advantages of proposed model are verified through a generic two machine power system and modified IEEE-9 bus test system. Modern power systems are gradually evolving into low-inertia systems due to the integration of high penetration of renewable energy and power electronic equipment. For the natural inertia on the rotor, doubly-fed induction generator (DFIG) based wind farms are expected to provide inertia support for systems. The paper proposed an analytical model of DFIG with df / dt inertia control for studying frequency dynamics, and investigates the optimal design of virtual inertia from wind farms, as well as its equivalent inertia contribution to system. The inertia response differences between DFIG and synchronous generator (SG) are discussed and analyzed for the first time, and then to accurately describe the frequency response with low cost, an analytical model of DFIG with inertia control is developed considering wind turbine aerodynamic characteristics. The explicit expression of virtual inertia provided by DFIG is derived according to the kinetic energy equilibrium, and the key factors that dominate the magnitude of virtual inertia are illustrated. Based on the system frequency response model including wind farms, taking the system frequency nadir (SFN) and the time of reaching nadir (ToN) as targets, a multi-objective optimal configuration model of virtual inertia is constructed and solved through MOPSO. The time domain simulations of a generic two machine four bus system and modified IEEE 9-bus test system are both performed in MATLAB/Simulink, the accuracy and efficiency of our proposed DFIG model on system frequency dynamics research are demonstrated, the pareto frontiers of virtual inertia configuration under different working conditions are optimized and analyzed as well as the impacts of different parameters on inertia evaluation. [ABSTRACT FROM AUTHOR]

• The effect of the internal power-sharing ratio of WTGs on the admittance characteristics of wind farms is investigated. • The identification method of the AOP-admittance model considering frequency-coupling for wind farms is proposed. • This method can identify the AOP-admittance model of wind farms by measurement data of WTGs under several operating points. • The identification method can avoid the dimension disaster in admittance modeling for the wind farm. Admittance identification is an effective tool to solve the issue of black-box admittance modeling in wind farms. However, due to the large operating range of wind farms, it is difficult to accurately identify the admittance model of wind farms under all operating conditions, which limits the research on wideband oscillation caused by the interaction between wind farms and the power grid. This paper analyses the characteristics of the frequency-coupling admittance for wind farms. It is found that the power-sharing ratio of wind turbine generators (WTGs) affects the admittance characteristic of the wind farm, which leads to a huge number of operating points for the wind farm. The all-operating-point (AOP) admittance model of wind farms considering frequency-coupling characteristics is hard to directly identify. Aiming for this problem, this paper proposes to first identify the AOP-admittance model for WTGs. Then, based on the operating points of each WTG and the network structure, the AOP-admittance model of the wind farm is obtained via the admittance aggregation and model reduction method. This proposed method solves the problem of black-box admittance modeling and addresses the problem of dimension disaster in admittance modeling for wind farms. The identified model of the wind farm can be used to accurately assess the stability of the wind power integration system under various operating conditions. Finally, the effectiveness of the proposed method is verified through the admittance measurement and stability analysis of the wind farm. [ABSTRACT FROM AUTHOR]

Yaw optimization control is recognized as the most effective active wake control strategy for enhancing the overall power generation of wind farms. However, the potential adverse effects of yaw optimization control on the fatigue life of wind turbines remain unclear. This study examined the effect of yaw optimization control on the fatigue life of offshore wind turbines using tower bolts. Initially, the yaw misalignment of the wind turbines was optimized using the open-source FLORIS package to maximize wind farm power generation. Subsequently, the time-varying load of the wind turbines was obtained through the OpenFAST software, using the optimal yaw misalignment, wind speed, and turbulence intensity at the hub height as inputs. The fatigue life of the wind turbines was then calculated by integrating the Schmidt–Neuper engineering stress algorithm, rain flow counting method, and Miner-Palmgren fatigue damage accumulation theory. Finally, a case study of the Horns Rev I large-scale offshore wind farm, comprising 80 wind turbines, revealed that yaw optimization control could significantly enhance the annual power generation of the wind farm by approximately 1.818%. However, optimization comes at the cost of reducing the fatigue life of wind turbine tower bolts by approximately 3–9 years. • FLORIS package calculates the optimal yaw misalignment of all wind turbines. • OpenFAST was used to calculate the time series load of the wind turbine tower. • Influence of yaw optimization control on fatigue life of wind turbines studied. • Yaw optimization control can significantly improve annual power generation. • Fatigue life of wind turbines may be reduced by yaw optimization control. [ABSTRACT FROM AUTHOR]

The actuator disc (AD) model combined with the Reynolds-averaged Navier-Stokes (RANS) model has been demonstrated as the most effective approach for simulating wind farm wakes due to its computational efficiency and acceptable accuracy. However, challenges remain in defining the reference inflow wind speed for the AD model and identifying a robust turbulence model for the RANS method. To solve these issues, two strategies for establishing the AD model (AD- up1D model and AD- local model), along with four turbulence models (standard k - ε , SST k - ω , linear pressure-strain RSM and modified RSM), are comprehensively validated here to predict multiple wakes within two representative wind farms. The temporal variability of multiple turbines' power output and the significant impact of wind direction on the power is particularly emphasized. Overall, this study indicates that the proposed AD- local /Mod RSM method facilitates a realistic wake recovery in the cumulated wake flow and agrees well with the field measurements. It consistently performs well, never ranking last in any test cases, with percentage deviations ranging from 1.8% to 9.0%. Most importantly, this study evaluates the strengths and weaknesses of each AD/RANS method and provides recommendations for wind farm design purposes. • Two typical wind farms featuring regular and irregular layouts are investigated. • A systematic evaluation of the AD/RANS method setting approaches are conducted. • The proposed AD- local /Mod RSM method facilitates a realistic cumulated wake effect. • Identify an effective AD/RANS model for predicting multiple wake interactions. • The quality of each turbulence model is highly related to the wind sector angle. [ABSTRACT FROM AUTHOR]

Wind farm layout optimization (WFLO) can reduce the turbulence intensity on the wind turbines while maximizing power generation. To accurately compute turbulence intensity distribution in the wind farm, we utilize the innovative three-dimensional cosine-shaped turbulence intensity (3D-COTI) model. By integrating the three-dimensional cosine-shaped linear entrainment (3DCLE) wake model previously developed by the authors, we introduce a new multiple wind turbine wake model (3DCLE-M). This model considers the wake superposition effect, enabling precise calculation of power generation. Building upon the 3D-COTI and 3DCLE-M models, we propose a multi-objective WFLO approach to maximize power generation and minimize streamwise turbulence intensity in the wind-turbine-swept area. The results indicate that under maximized power generation, this approach significantly reduces turbulence intensity and its non-uniform distribution in the wind-turbine-swept area. In two ideal cases, the maximum turbulence intensity in all wind-turbine-swept areas of the optimized layout is 25 % and 3.8 % lower than that of the selected benchmark layout. By optimizing the layout of the Horns Rev offshore wind farm, a new layout can be obtained with increased total power output by 1.58 % and the reduced total duration of high-fatigue-load wind turbines under high turbulence intensity by 25 % compared to the benchmark. [ABSTRACT FROM AUTHOR]

• Wind farm layout and collector system optimization are integrated in a double-layer joint-optimization framework. • Essential factors are modelled and integrated , including 3D seabed, multiple substations, and wind turbines' fatigue. • Layer-wise design of solving algorithms is implemented to suit the different problem natures. • The effectiveness of proposed method is verified by reducing the leverlized cost of energy on a benchmark offshore wind farm. Offshore wind power is continuously developing for renewable energy generation. Generally, the overall planning work of offshore wind farms (OWFs) is divided into wind farm layout optimization (WFLO) and wind farm collector system optimization (WFCSO), which focus on wind turbines' (WT) micro-siting and sea cables' network design, respectively. Traditionally, the optimizations on these two subproblems are isolated, which lacks the integral consideration of their co-effect on the optimal planning solution. Moreover, the practicability of these optimizations also remains at a low level, with key practical factors being largely overlooked for the sake of model simplicity. To fill these gaps, this article proposes a complete modelling of the joint-optimization problem for OWF planning with a double-layer optimization framework. It not only considers the interplay between WFLO and WFCSO, but also well integrates all the essential and practical parts together, including the impacts of 3D seabed geography, the scalability to multiple offshore substations, the reliability concerns of WTs' fatigue, and the layer-wise selection of solving algorithms to suit the different problem natures. The proposed optimization method is tested on a 50 WTs system through comparative studies, and the results verify the necessity of each designed part in the proposed joint planning model. [ABSTRACT FROM AUTHOR]

• The use of suspended inter-array power cables in floating offshore wind farms is explored. • Several different cable configurations connecting two spar FOWTs are assessed based on Fitness Factors using static and dynamic analyses. • The number of buoys is found to be the main parameter affecting the maximum effective tension and the minimum bending radii of the cables. • The optimum cable configuration found for the two spar FOWTs is employed to connect two semi-submersible FOWTs. • The influence of the floater type on the suspended power cable tension and curvature is found to be negligible. • Analysis of power cable behavior in different offshore wind farm layouts shows that a two-turbine setup with different environmental load directions is representative of the suspended power cables design in entire wind farms. The aim of the present study is to propose an engineering approach of designing suspended inter-array power cable configuration for offshore wind farms. To achieve this, a spar type and a semi-submersible type floating offshore wind turbines (FOWTs) are modeled in the dynamic analysis software OrcaFlex. The accuracy of these models is validated against reference studies. Several different cable configurations connecting two spar FOWTs are assessed based on Fitness Factors using static and dynamic analyses. The non-linear bending behavior and the marine growth effects are considered in the analyses. The number of buoys is found to be the main parameter affecting the maximum effective tension and the minimum bending radii of the cables. The buoy spacing determines whether the cable touches the seabed, floats fully submerged, or floats at the sea surface. The influence of the cable length and the marine growth on the observed cable tensions and curvatures is small for the investigated configurations. The optimum cable configuration found for the two spar FOWTs is employed to connect two semi-submersible FOWTs. The influence of the floater type on the suspended power cable tension and curvature is found to be negligible. Analysis of power cable behavior in an offshore wind farm layout shows that a two-turbine setup with different environmental load directions can be used as a representative case for the suspended power cables design of the entire wind farm. [ABSTRACT FROM AUTHOR]

Offshore wind farms, while strategically positioned to maximise wind energy capture, are exposed to harsh environments, impacting their reliability and accessibility. Low reliability and accessibility in turn translate into high Operation and Maintenance (O&M) costs, which represent approximately 30% of the total lifetime costs of the project. One approach to reduce O&M costs is to improve maintenance planning decisions. The present paper presents a novel O&M scheduling methodology for offshore wind farm operations based on wind and wave forecasts. The methodology forecasts farm yield considering farm wake effects to identify optimal operation schedules, vessel routing, and turbine maintenance sequences that minimise costs and revenue losses due to downtime. Weather forecast uncertainty is modelled and integrated into the decision-making process to minimise weather risks. A case study inspired by the WindFloat Atlantic floating wind project was used to demonstrate the optimisation potential. Results suggest that adopting the proposed methodology over business-as-usual scheduling significantly boosts offshore wind farm operational profits during the forecasted period, with increases ranging from 2% to 24%, depending on the scenario considered. It was found that integrating the wind farm wake losses into the scheduling decisions can improve the optimal scheduling solution and further minimise total operation costs. • A novel O&M planning methodology for offshore wind farm operation is proposed. • Model generates optimal maintenance schedules based on weather forecasts. • Model integrates weather forecast uncertainty and farm wake effects into planning. • The WindFloat Atlantic floating wind project was used as a case study. • Factoring in wake effects enhances maintenance scheduling and reduces energy losses. [ABSTRACT FROM AUTHOR]

This study employs a UAV anemometry system to assess the wind field around a yawed wind turbine, particularly focusing on its wake during operational conditions. The research findings reveal that the evolution of wind turbine wakes follows distinct patterns at various downstream distances. Turbulence intensity notably amplifies within regions characterized by significant fluctuations in mean wind speed. Specifically, in yawed conditions, the areas with the highest turbulence generated by the rotor coincide with zones exhibiting pronounced variations in mean wind speed. The heightened turbulence within the wake region to some extent constrains the safety and economic viability of wind farms. Turbulence intensity increases significantly in the region where the average wind speed changes greatly, that is, under the yaw state of the wind turbine, this region is characterized with the strongest turbulence generated by the rotor. The UAV anemometry system's wind speed assessment closely matches predictions from the Y-3DJGF model, accounting for wake experience coefficient adjustments. Furthermore, in yaw conditions, the wind turbine's wake trajectory exhibits some deviation from the incident flow's direction, with an initial increase in slope followed by gradual stabilization. As the downstream distance increases, the trajectory will eventually establish a consistent trend with the incident flow. The cost-effective and flexible UAV anemometry system enhances wind field measurements, offering an innovative approach for wind energy sector research and engineering. • Development of a UAV-based anemometry system for wake measurement of yawed wind turbines. • Investigation of wake characteristics under yawed conditions, revealing significant reductions in wake wind speed and increased turbulence intensity, especially at 2D downstream. • Experimental validation of wake trajectory deviations under yaw conditions, highlighting changes in slope and eventual alignment with incident flow downstream. • Validation of wind speed measurements using the UAV anemometry system against predicted results from the Y-3DJGF model. • Application of the UAV anemometry system in wind resource assessment, layout optimization, and power generation efficiency forecasting for wind farms. [ABSTRACT FROM AUTHOR]