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In electrical power system engineering, the economic load dispatch (ELD) problem is a critical issue for fuel cost minimization. This ELD problem is often characterized by non-convexity and subject to multiple constraints. These constraints include valve-point loading effects (VPLEs), generator limits, emissions, and wind power integration. In this study, both emission constraints and wind power are incorporated into the ELD problem formulation, with the influence of wind power quantified using the incomplete gamma function (IGF). This study proposes a novel metaheuristic algorithm, the modified moth flame optimization (MMFO), which improves the traditional moth flame optimization (MFO) algorithm through an innovative flame selection process and adaptive adjustment of the spiral length. MMFO is a population-based technique that leverages the intelligent behavior of flames to effectively search for the global optimum, making it particularly suited for solving the ELD problem. To demonstrate the efficacy of MMFO in addressing the ELD problem, the algorithm is applied to four well-known test systems. Results show that MMFO outperforms other methods in terms of solution quality, speed, minimum fuel cost, and convergence rate. Furthermore, statistical analysis validates the reliability, robustness, and consistency of the proposed optimizer, as evidenced by the consistently low fitness values across iterations. [ABSTRACT FROM AUTHOR]

With the load center's continuous expansion and development of the AC power grid's scale and construction, the recipient grid under the multi-feed DC environment is facing severe challenges of DC commutation failure and bipolar blocking due to the high strength of AC-DC coupling and the low level of system inertia, which brings many complexities and uncertainties to economic scheduling. In addition, the large-scale grid integration of wind power, photovoltaic, and other intermittent energy sources makes the ultra-high-voltage (UHV) DC channel operation state randomized. The deterministic scenario-based timing power simulation is no longer suitable for the current complex and changeable grid operation state. In this paper, we first start with the description and analysis of the uncertainty in renewable energy (RE) sources, such as wind and solar, and reconstruct the time-sequence power model by using the stochastic differential equation model. Then, a carbon emission trading cost (CET) model is constructed based on the CET mechanism, and the two-stage locating and capacity optimization model for the UHV DC receiving end is proposed under the constraint of dispatch safety and stability. Among them, the first stage starts with the objective of maximizing the carrying capacity of the UHV DC receiving end grid; the second stage checks its dynamic safety under the basic and fault modes according to the results of the first stage and corrects the drop point and capacity of the UHV DC line with the objective of achieving safe and stable UHV DC operation at the lowest economic investment. In addition, the two-stage model innovatively proposes UHV DC relative inertia constraints, peak adjustment margin constraints, transient voltage support constraints under commutation failure conditions, and frequency support constraints under a DC blocking state. In addition, to address the problem that the probabilistic constraints of the scheduling model are difficult to solve, the discrete step-size transformation and convolution sequence operation methods are proposed to transform the chance-constrained planning into mixed-integer linear planning for solving. Finally, the proposed model is validated with a UHV DC channel in 2023, and the results confirm the feasibility and effectiveness of the model. [ABSTRACT FROM AUTHOR]

This paper proposes a method based on Computational Fluid Dynamics (CFD) and the detection of Wind Energy Extraction Latency for a given wind turbine (WT) designed for ultra-short-term (UST) wind energy forecasting over complex terrain. The core of the suggested modeling approach is the Wind Spatial Extrapolation model (WiSpEx). Measured vertical wind profile data are used as the inlet for stationary CFD simulations to reconstruct the wind flow over a wind farm (WF). This wind field reconstruction helps operators obtain the wind speed and available wind energy at the hub height of the installed WTs, enabling the estimation of their energy production. WT power output is calculated by accounting for the average time it takes for the turbine to adjust its power output in response to changes in wind speed. The proposed method is evaluated with data from two WTs (E40-500, NM 750/48). The wind speed dataset used for this study contains ramp events and wind speeds that range in magnitude from 3 m/s to 18 m/s. The results show that the proposed method can achieve a Symmetric Mean Absolute Percentage Error (SMAPE) of 8.44% for E40-500 and 9.26% for NM 750/48, even with significant simplifications, while the SMAPE of the persistence model is above 15.03% for E40-500 and 16.12% for NM 750/48. Each forecast requires less than two minutes of computational time on a low-cost commercial platform. This performance is comparable to state-of-the-art methods and significantly faster than time-dependent simulations. Such simulations necessitate excessive computational resources, making them impractical for online forecasting. [ABSTRACT FROM AUTHOR]

Aimed at the information loss problem of using discrete indicators in wind power output characteristics analysis, a self-organizing map neural network-based clustering method is proposed in this study. By identifying the appropriate representativeness and topological structure of the competition layer, cluster analysis of the wind power output process in four seasons is realized. The output characteristics are evaluated through multiple evaluation indicators. Taking the wind power output of the Hunan power grid as a case study, the results underscore that the 1 × 3-dimensional competition layer structure had the highest representativeness (72.9%), and the wind power output processes of each season were divided into three categories, with a robust and stable topology structure. Summer and winter were the most representative seasons. Summer had strong volatility and small wind power outputs, which required the utilization of other power sources to balance power supply and load demand. Winter featured low volatility and large wind power outputs, necessitating cooperation with peak-shaving power sources to enhance the power grid's absorbability to wind power. The seasonal clustering analysis of wind power outputs will be helpful to analyze the seasonality of wind power outputs and can provide scientific and technical support for guiding the power grid's operation and management. [ABSTRACT FROM AUTHOR]

In this study, an in-depth analysis is presented on forecasting aggregated wind power production at the regional level, using advanced Machine-Learning (ML) techniques and feature-selection methods. The main problem consists of selecting the wind speed measuring points within a large region, as the wind plant locations are assumed to be unknown. For this purpose, the main cities (province capitals) are considered as possible features and four feature-selection methods are explored: Pearson correlation, Spearman correlation, mutual information, and Chi-squared test with Fisher score. The results demonstrate that proper feature selection significantly improves prediction performance, particularly when dealing with high-dimensional data and regional forecasting challenges. Additionally, the performance of five prominent machine-learning models is analyzed: Long Short-Term Memory (LSTM) networks, Artificial Neural Networks (ANNs), Support Vector Machines (SVMs), Convolutional Neural Networks (CNNs), and Extreme-Learning Machines (ELMs). Through rigorous testing, LSTM is identified as the most effective model for the case study in northern Italy. This study offers valuable insights into optimizing wind power forecasting models and underscores the importance of feature selection in achieving reliable and accurate predictions. [ABSTRACT FROM AUTHOR]

The text discusses the recent development and future perspectives of wind power generation, highlighting the rapid growth of wind energy globally. It covers topics such as wind potential assessment, wind power forecasting, wind power under climate change, socioeconomic and environmental factors of wind energy expansion, and wind turbine design development. The document emphasizes the need for improvements in research and the application of multidisciplinary approaches to address key challenges in wind energy utilization. The Special Issue 'Recent Development and Future Perspective of Wind Power Generation' provides valuable insights into these areas, closing some research gaps. [Extracted from the article]

An auxiliary structure can significantly improve the wind-trapping capacity of the Savonius wind turbine. In this study, a novel auxiliary structure called a wind energy gathering structure (WEGS) is proposed, and its five parameters, namely the lengths of the shrinkage and diffusion tubes, the length of the centerboard, the length of the throat, the length of the wind board, and the shrinkage and diffusion angles, are investigated using computational fluid dynamics (CFD) and Taguchi's method. Meanwhile, Taguchi's method and ANOVA reveal that among the studied parameters, the shrinkage and diffusion angles, the length of the centerboard, and the lengths of the shrinkage and diffusion tubes have a more significant influence on the performance of the WEGS. At a tip speed ratio (TSR) value of 1 and a wind speed of 7 m/s, the optimized combination of the WEGS parameters obtained by Taguchi's method improves the mean torque coefficient of the turbine by 42.1%. Moreover, at other TSRs (0.6–1.2), the turbine with the WEGS also outperforms an open turbine in terms of aerodynamic (increases of 20.1–53%) and lifetime performance. [ABSTRACT FROM AUTHOR]

A comparison and evaluation of the AEP(Annual Energy Production) of a wind farm were conducted in this study with a feasibility study and using the actual operation data from the S wind farm on Jeju Island from January 2020 to December 2022. The free wind speed data were selected from the data measured from a nacelle anemometer, the correlation equation between wind speed and AEP was obtained, and the annual average wind speed for the past 20 years was predicted using the MCP method. As a result, comparing the AEP from the operation data with that estimated in the feasibility study, we found that the AEP was reduced by approximately 2.40% in 2020 and 12.14% in 2021, and increased by 6.76% in 2022. The wind speeds over the 20-year lifetimes of the wind turbines were obtained, and the AEP that could be generated at the S wind farm indicated that it could be used for operation. In the future, the S wind farm will operate at between 25% and 30% availability for the remaining 17 years of operation. If the availability falls below 25%, there will be a need to check the reasons for the deterioration of wind turbine performance and the frequency of failures. [ABSTRACT FROM AUTHOR]

Over the past few decades, wind energy has expanded to become a widespread, clean, and sustainable energy source. However, integrating offshore wind energy with the onshore AC grids presents many stability and control challenges that hinder the reliability and resilience of AC grids, particularly during faults. To address this issue, current grid codes require offshore wind farms (OWFs) to remain connected during and after faults. This requirement is challenging because, depending on the fault location and power flow direction, DC link over- or under-voltage can occur, potentially leading to the shutdown of converter stations. Therefore, this necessitates the proper understanding of key technical concepts associated with the integration of OWFs. To help fill the gap, this article performs an in-depth investigation of existing alternating current fault ride through (ACFRT) techniques of modular multilevel converter-based high-voltage direct current (MMC-HVDC) for OWFs. These techniques include the use of AC/DC choppers, flywheel energy storage devices (FESDs), power reduction strategies for OWFs, and energy optimization of the MMC. This article covers both scenarios of onshore and offshore AC faults. Given the importance of wind turbines (WTs) in transforming wind energy into mechanical energy, this article also presents an overview of four WT topologies. In addition, this article explores the advanced converter topologies employed in HVDC systems to transform three-phase AC voltages to DC voltages and vice versa at each terminal of the DC link. Finally, this article explores the key stability and control concepts, such as small signal stability and large disturbance stability, followed by future research trends in the development of converter topologies for HVDC transmission such as hybrid HVDC systems, which combine current source converters (CSCs) and voltage source converters (VSCs) and diode rectifier-based HVDC (DR-HVDC) systems. [ABSTRACT FROM AUTHOR]

This research developed smart integrated hybrid renewable systems for small energy communities and applied them to a real system to achieve energy self-sufficiency and promote sustainable decentralized energy generation. It compares stand-alone (SA) and grid-connected (GC) configurations using a developed optimized mathematical model and data-driven optimization, with economic analysis of various renewable combinations (PV, Wind, PHS, BESS, and Grid) to search for the optimal solution. Four cases were developed: two stand-alone (SA1: PV + Wind + PHS, SA2: PV + Wind + PHS + BESS) and two grid-connected (GC1: PV + PHS + Grid, GC2: Wind + PHS + Grid). GC2 shows the most economical with stable cash flow (−€123.2 annually), low CO2 costs (€367.2), and 91.7% of grid independence, requiring 125 kW of installed power. While GC options had lower initial investments (between €157k to €205k), the SA configurations provided lower levelized costs of energy (LCOE) ranging from €0.039 to €0.044/kWh. The integration of pumped hydropower storage enhances energy independence, supporting peak loads for up to two days with a storage capacity of 2.17 MWh. [ABSTRACT FROM AUTHOR]

Multi-rotor system (MRS) wind turbines can provide a competitive alternative to large-scale wind turbines due to their significant advantages in reducing capital, transportation, and operating costs. The main challenges of MRS wind turbines include the complexity of the supporting structure, mathematical modeling of the aerodynamic interaction between the rotors, and the yaw control mechanism. In this work, MATLAB 2018b/Simulink® software was used to model and simulate a twin-rotor wind turbine (TRWT), and an NREL 5 MW wind turbine was used to verify the model outputs. Different random signals of wind velocities and directions were used as inputs to each rotor to generate different thrust loads, inducing twisting moments on the main tower. A yaw controller system was adapted to ensure that the turbine constantly faced the wind to maximize the power output. A DC motor was used as the mechanism's actuator. The goal was to achieve a compromise between aligning the rotors with the wind direction and reducing the torque induced on the main tower. A comparison between linear and nonlinear controllers was performed to test the yaw system actuator's response at different wind speeds and directions. Sliding mode control (SMC) was chosen, as it was suitable for the nonlinearity of the system, and its performance showed a faster response compared with the PID controller, with a settling time of 0.17 sec and a very low overshoot. The controller used the transfer function of the motor to generate a sliding surface. The dynamic responses of the controlled angle are shown and discussed. The controller showed promising results, with a suitable response and low chattering signals. [ABSTRACT FROM AUTHOR]

The integration of wind and solar energy with green hydrogen technologies represents an innovative approach toward achieving sustainable energy solutions. This review examines state-of-the-art strategies for synthesizing renewable energy sources, aimed at improving the efficiency of hydrogen (H2) generation, storage, and utilization. The complementary characteristics of solar and wind energy, where solar power typically peaks during daylight hours while wind energy becomes more accessible at night or during overcast conditions, facilitate more reliable and stable hydrogen production. Quantitatively, hybrid systems can realize a reduction in the levelized cost of hydrogen (LCOH) ranging from EUR 3.5 to EUR 8.9 per kilogram, thereby maximizing the use of renewable resources but also minimizing the overall H2 production and infrastructure costs. Furthermore, advancements such as enhanced electrolysis technologies, with overall efficiencies rising from 6% in 2008 to over 20% in the near future, illustrate significant progress in this domain. The review also addresses operational challenges, including intermittency and scalability, and introduces system topologies that enhance both efficiency and performance. However, it is essential to consider these challenges carefully, because they can significantly impact the overall effectiveness of hydrogen production systems. By providing a comprehensive assessment of these hybrid systems (which are gaining traction), this study highlights their potential to address the increasing global energy demands. However, it also aims to support the transition toward a carbon-neutral future. This potential is significant, because it aligns with both environmental goals and energy requirements. Although challenges remain, the promise of these systems is evident. [ABSTRACT FROM AUTHOR]

When using the Transformer model for wind power prediction, the presence of noise in wind power data and the model's final layer relying solely on a simple linear output reduces the model's ability to capture nonlinear relationships, leading to a decrease in prediction accuracy. To address these issues, this paper proposes an ultrashort-term wind power prediction model based on exponential weighted moving average (EWMA) data processing and Kolmogorov–Arnold Network (KAN)-Transformer. First, multiple variable features are smoothed using EWMA, which suppresses noise while preserving the original data trends. Then, the EWMA-processed data is input into the Encoder and Decoder modules of the Transformer model to extract features. The output from the Decoder layer is then passed through the KAN layer, built using a cubic B-spline function, to enhance the model's ability to capture nonlinear relationships, thereby improving the prediction accuracy of the Transformer model for wind power. Finally, experimental analysis is conducted, and it shows that the proposed model achieves the highest prediction accuracy, with a mean absolute error of 4.38 MW, a root mean squared error of 7.37 MW, and a coefficient of determination of 98.73%. [ABSTRACT FROM AUTHOR]

This paper presents an optimization method for hybrid energy systems based on Model Predictive Control (MPC), Long Short-Term Memory (LSTM) networks, and Kolmogorov–Arnold Networks (KANs). The proposed method is applied to a high-altitude wind energy work umbrella control system, where it aims to enhance the stability and efficiency of energy utilization. The work umbrella system integrates wind and solar energy sources, with energy stored in a battery and used to control the umbrella's operations. The MPC framework is employed to optimize control actions by solving a finite-horizon optimization problem, ensuring the battery State of Charge (SOC) remains within an optimal range. The LSTM network provides accurate predictions of environmental conditions, including wind speed and solar irradiance, which are essential for MPC's decision-making process. To address complex nonlinearities in the system, the KAN is utilized to model and approximate these dynamics, refining the LSTM predictions. The integration of these advanced control strategies enables the system to handle varying operational conditions and maintain optimal performance. The case study demonstrates the effectiveness of the MPC-LSTM-KAN approach, revealing improvements in the SOC stability, energy efficiency, and operational endurance of the high-altitude wind energy work umbrella system. The results indicate that this hybrid optimization method offers a robust solution for managing hybrid energy systems in dynamic environments. [ABSTRACT FROM AUTHOR]

At present, the safe operation of integrated energy systems is significantly affected by the considerable uncertainty inherent to wind and photovoltaic power generation. Based on this, this paper proposes an optimal scheduling model for integrated electricity, heat, and hydrogen-based energy systems on distributed robust optimization (DRO). Firstly, a combined heat and power microgrid system considering hydrogen energy systems was constructed based on the thermoelectric cogeneration characteristics of fuel cells and electrolyzers. Then, a data-driven two-stage distribution robust optimization scheduling model is built by combining typical historical data of wind power output, photovoltaic power output, and load. The results show that the distributed robust method reduces the running cost by 6% compared to the deterministic method. The proposed method and model are capable of meeting the demand for thermoelectric loads within the microgrid in a more cost-effective manner, thereby achieving stable and independent operation of the system. [ABSTRACT FROM AUTHOR]

Constructing isolated industrial microgrids with wind power is beneficial for improving the economic benefits of high-energy-consuming production, such as the electrolytic aluminum industry. Due to the specialized structure of industrial microgrids and the unique characteristics of the electrolytic aluminum load (EAL), the common emergency frequency control methods do not apply to the specific operational requirements of isolated industrial microgrids. Since EALs have huge regulating capacities and fast responses, this paper proposes a coordinated emergency frequency control scheme to deal with power disturbances in isolated industrial microgrids. The coordinated frequency control model of an industrial microgrid considering demand-side participation is derived. With the help of output regulation theory, a practical, feasible coordinated frequency controller is designed by introducing frequency deviation and power disturbance as feedback control signals. The proposed control scheme achieves reserve power distribution between the generation and demand sides. The microgrid frequency can be maintained within a permitted range in the presence of large power imbalances. The simulation results conducted in an actual isolated industrial microgrid validate the effectiveness and dynamic performance of the proposed control scheme. [ABSTRACT FROM AUTHOR]

Offshore wind-to-hydrogen production is an effective means of solving the problems of large-scale grid-connected consumption and high power transmission costs of offshore wind power. Site selection is a core component in planning offshore wind-to-hydrogen facilities, involving careful consideration of multiple factors, and is a classic multi-criteria decision-making problem. Therefore, this study proposes a multi-criteria decision-making method based on the two-dimensional linguistic cloud model to optimize site selection for offshore wind-to-hydrogen bases. Firstly, the alternative schemes are evaluated using two-dimensional linguistic information, and a new model for transforming two-dimensional linguistic information into a normal cloud is constructed. Then, the cloud area overlap degree is defined to calculate the interaction factor between decision-makers, and a multi-objective programming model based on maximum deviation-minimum correlation is established. Following this, the Pareto solution of criteria weights is solved using the non-dominated sorting genetic algorithm II, and the alternatives are sorted and selected through the cloud-weighted average operator. Finally, an index system was constructed in terms of resource conditions, planning conditions, external conditions, and other dimensions, and a case study was conducted using the location of offshore wind-to-hydrogen production bases in Shanghai. The method proposed in this study demonstrates strong robustness and can provide a basis for these multi-criteria decision-making problems with solid qualitative characteristics. [ABSTRACT FROM AUTHOR]

As renewable energy sources like wind and solar power increasingly replace traditional energy sources and are integrated into the power grid, the issue of insufficient system inertia is becoming more apparent. This paper presents an online adaptive time window inertia constant identification method based on ambient measurements to identify the equivalent inertia constant of the time-varying inertia at Point of Interface (POI) level. The proposed method takes advantage of the online inertia estimation and the data-driven equivalent inertia constant identification techniques to simultaneously achieve online tracking and accuracy. With this regard, this paper first describes the inertia providers in modern system. Then, based on the frequency and power data measured by the Phasor Measurement Unit (PMU), this paper provides an improved data-driven equivalent inertia constant identification method. Subsequently, the paper proposes an ambient data smoothing method to cope with the numerical errors and provides, as a byproduct, an adaptive time window inertia constant identification. The adaptive time window is designed to enhance the accuracy of the method. Finally, the feasibility and accuracy of the proposed method of tracking synthetic inertia are validated by the simulation tests based on a grid in northwest China with high renewable energy penetration and a Virtual Power Plant (VPP). The experimental results show that the accuracy of this method is within 5 % . [ABSTRACT FROM AUTHOR]

One of the most important and efficient sources of green electricity is catching air currents through wind turbine technology. Wind power plants are located in areas where the energy potential of the wind is high but it varies. The time variation of the wind generates fluctuations in the power produced by the wind farms that is injected into the grid. This elevates, depending on the intensity, problems of network stability and the need for balancing energy, thus raising both technical and cost issues. The present paper analyzes the behavior of a wind turbine (WT) over time in varying wind speed conditions, highlighting that without automation algorithms, a WT is far from the operation at the maximum power point (MPP). However, even when it is brought to operate at MPP, there are still significant variations in the power injected into the network. These power variations can be compensated if the wind system has energy storage facilities for the captured wind. All of these assumptions are analyzed using improved mathematical models and processed in simulations, with experimental data used as input from a wind turbine with an installed power of 2.5 [MW] in operation on the Romanian Black Sea coastal area. Consequently, the paper demonstrates that during an operation in the optimal area, from an energy perspective, the wind turbine's maximum power point requires a storage system for the captured wind energy. [ABSTRACT FROM AUTHOR]

While the wind turbine industry has been primarily dominated by horizontal-axis wind turbines, the forefront of knowledge of these turbines has revealed significant challenges in various aspects, including manufacturing, structural design, cost, and maintenance. On the other hand, the advantages associated with Darrieus vertical-axis wind turbines (VAWTs) demonstrate significant potential that can address the existing challenges of the wind turbine industry. Current work aims to investigate the practicality of this potential for the wind energy sector. To this end, the benefits of employing Darrieus turbines for domestic and industrial applications, isolated operation, and on/offshore windfarm applications have been explored. It is apparent that Darrieus VAWTs are better suited to a wide range of environments, whether they are deployed in isolation or integrated systems, and whether they are utilized on a small or large scale. Darrieus VAWTs are adaptable to urban unsteady variable wind, are less expensive on large scales, provide higher power density at the windfarm level, and provide stability for offshore platforms. Nevertheless, challenges remain in fully harnessing VAWT potential rooted in their complex aerodynamics. This serves as a primary challenge for VAWTs to address the challenges of the wind turbine industry in line with the 2050 roadmap. [ABSTRACT FROM AUTHOR]

Accurate ultra-short-term power prediction for wind farms is challenging under rapid wind speed fluctuations, complicating production planning and power balancing. This paper proposes a new method considering spatial and temporal correlations of wind fluctuations among adjacent wind farms. The method first calculates the time difference between power fluctuations based on wind speed, direction, and relative positions, determining the prior information period. The variational Bayesian model is then used to extract implicit relationships between power fluctuations of adjacent wind farms, enabling power prediction during the prior information period. Finally, the non-prior information period is predicted to complete the ultra-short-term power prediction. Using measured data from three wind farms in Fujian Province, compared to other models, the method demonstrates improved accuracy by effectively leveraging the power fluctuation characteristics of adjacent wind farms, and it has a certain amount of generalizability. [ABSTRACT FROM AUTHOR]

Assessing market power in the presence of different production technologies such as renewable energies, including wind and solar power, is crucial for electric market analysis and operation. This paper investigates structural market power by incorporating wind farms and solar generation over a short-term period. The study examines the issue of market concentration boundaries to assess structural market power by calculating the minimum and maximum market concentration index values in the day-ahead market. It models the technical specifications of power plants, such as the maximum and minimum production limits, ramp-up and ramp-down rates, and minimum required up and down times. By extracting the spatiotemporal correlation of wind power generation from real data, the uncertainty of renewable power generation is represented through a set of scenarios. The analysis explores the correlation effects of wind farms, solar generation, and wind penetration levels under different ownership structures. Simulation results using a modified PJM five-bus system illustrate the effectiveness of the developed method. Our results indicate that integrating renewable energy can reduce the Herfindahl–Hirschman Index (HHI) by up to 30% as wind penetration levels rise from 0% to 40%, fostering a more competitive market structure. However, the correlation between wind farms also increases market volatility, with the standard deviation of the HHI rising by about 25% during peak load periods. These findings demonstrate the practical applicability of the developed methodology for assessing market dynamics in the presence of renewable energy sources. [ABSTRACT FROM AUTHOR]

Hydropower as a flexible regulation resource is a rare choice to suppress the ever-increasing penetration of wind power in electrical power systems. The complementary characteristics and performance improvement of a hydro–wind hybrid power system based on a mathematical model of the hybrid power system is studied in this paper. This established model takes into account the stochastic variation in wind speeds in the wind power subsystem and the hydraulic–mechanical–electrical coupling characteristics of the hydropower subsystem. The complementary analysis is conducted based on the evaluation variables outputted by the established model, such as the wind power, hydro-regulation power, hydraulic power, and frequency. To make full use of the regulation capability of the hydropower system, the optimization of parameter settings is also carried out to improve complementary performances of the hybrid power system. The results from the complementary analysis show the detailed characteristics of hydro–wind coordinated operation under different types of real wind speeds. Here, 95% of installed hydro-capacity is used to complement the power shortage of the intermittent wind energy under the low wind speed. Alternatively, only around 66% of the installed hydro-capacity can be utilized to cope with the fluctuation in wind power under the medium and high wind speeds before the optimization of parameter settings. The recommended values and change rules of the control, hydraulic, and electrical parameters for the hydropower system are subsequently revealed from the analysis of parameter settings to contribute to a stable and safe hybrid power system. The results show that the optimized parameter can increase the maximal regulating capacity of the hydropower system by nearly 9 MW, approximately a sixth of the total installed hydropower capacity. The method and results obtained in this paper provide theoretical and technical guidance for the safe and economical operation of power stations. [ABSTRACT FROM AUTHOR]

The mechanical multiplier gearbox is one of the most important parts for wind power generation efficiency. Modern epicyclic gearboxes are compact, lightweight builds capable of high power ratings with coaxial input and output shafts. To achieve this, it is very important to select the proper internal gearbox layout and other relevant parameters in the early design stages as the wrong choices will result in a suboptimal solution. Parametric optimization was applied to select the optimal gearbox solution for a wind turbine application, while taking into account both two-carrier and three-carrier solutions. The large number of possible solutions has resulted in the development of the 2-SPEED software to conduct systematic analysis and comparison. The best five two-carrier solutions and the one best three-carrier solution have been selected from the solution pool, with the selection being based on the criteria of maximum efficiency, minimum weight, and minimal greater-ring diameter size. One optimal two-carrier solution was then selected from the five and compared to the three-carrier solution. Recommendations for the selection of either two-carrier and three-carrier gear train solutions according to the application demands have been deducted and provided. This will result in lighter, more efficient designs with smaller radial dimensions. [ABSTRACT FROM AUTHOR]

The depletion of fossil fuels has become a significant global issue, prompting scientists to explore and refine methods for harnessing alternative energy sources. This study provides a comprehensive review of advancements and emerging technologies in the desalination industry, focusing on technological improvements and economic considerations. The analysis highlights the potential synergies of integrating multiple renewable energy systems to enhance desalination efficiency and minimise environmental consequences. The main areas of focus include aligning developing technologies like membrane distillation, pervaporation and forward osmosis with renewable energy and implementing hybrid renewable energy systems to improve the scalability and economic viability of desalination enterprises. The study also analyses obstacles related to desalination driven by renewable energy, including energy storage, fluctuations in energy supply, and deployment costs. By resolving these obstacles and investigating novel methodologies, the study enhances the understanding of how renewable energy can be used to construct more efficient, sustainable, and economical desalination systems. Thermal desalination technologies require more energy than membrane-based systems due to the significant energy requirements associated with water vaporisation. The photovoltaic-powered reverse osmosis (RO) system had the most economically favourable production cost, while MED powered via a concentrated solar power (CSP) system had the highest production cost. The study aims to guide future research and development efforts, ultimately promoting the worldwide use of renewable energy-powered desalination systems. [ABSTRACT FROM AUTHOR]

This research investigates the application of machine learning models to optimise renewable energy systems and contribute to achieving Net Zero emissions targets. The primary objective is to evaluate how machine learning can improve energy forecasting, grid management, and storage optimisation, thereby enhancing the reliability and efficiency of renewable energy sources. The methodology involved the application of various machine learning models, including Long Short-Term Memory (LSTM), Random Forest, Support Vector Machines (SVMs), and ARIMA, to predict energy generation and demand patterns. These models were evaluated using metrics such as Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). Key findings include a 15% improvement in grid efficiency after optimisation and a 10–20% increase in battery storage efficiency. Random Forest achieved the lowest MAE, reducing prediction error by approximately 8.5%. The study quantified CO2 emission reductions by energy source, with wind power accounting for a 15,000-ton annual reduction, followed by hydropower and solar reducing emissions by 10,000 and 7500 tons, respectively. The research concludes that machine learning can significantly enhance renewable energy system performance, with measurable reductions in errors and emissions. These improvements could help close the "ambition gap" by 20%, supporting global efforts to meet the 1.5 °C Paris Agreement targets. [ABSTRACT FROM AUTHOR]

A third-generation wave model is driven by the synthetic wind field combined with the revised Holland wind and surface wind product from the National Centers for Environmental Prediction (NCEP). The temporal and spatial characteristics of the wind waves and swell during the typhoon are studied, as well as the responses of their wave energy spectra to the source terms. The results show that the typhoon waves have a more complicated asymmetric structure than the wind field, and the maximum significant wave height is always located on the right side of the direction along which the typhoon is moving, where wind waves are dominant, due to the extended fetch. The nonlinear wave–wave interaction helps to redistribute the energy of the wind seas at a high frequency to the remotely generated swells at a low frequency, ensuring that the typhoon wave's energy spectrum remains unimodal. This process occurs in regions without extended fetch, and a similar continued downshift in frequency as the wave–wave interaction occurs for the wind input as well when the waves outrun the typhoon, due to the nonlinear coupling between the wind and growing swells. [ABSTRACT FROM AUTHOR]

Icing is a popular research area in wind energy, and the icing problem of the supercooled droplet–ice crystal mixed-phase condition is one of the new challenges. A numerical method for analyzing the icing characteristics of wind turbine airfoil under mixed-phase conditions is presented. The control equations for the dynamics of supercooled droplets and ice crystals are formulated using the Lagrangian method. Equations for the conservation of mass and energy during the icing process involving supercooled droplets and ice crystals are constructed. The impact of erosion phenomena on the mixed-phase icing process is examined, and methodologies for solving the control equations are introduced. The numerical method is utilized for modeling mixed-phase icing under a range of conditions. The results of these simulations are then compared with data obtained from icing wind tunnel tests to assess the validity of the method. The influence of various mixed-phase conditions on ice shapes is studied. It is found that higher icing temperatures correspond to a larger icing range and amount. The increase in supercooled droplet content, ice crystal content, and ice crystal diameter all contribute to enhanced ice accretion. However, the effects of ice crystal content and diameter are relatively minor. [ABSTRACT FROM AUTHOR]

The diode-rectifier unit (DRU)-based high-voltage direct current (HVDC) transmission system offers an economical solution for offshore wind power transmission. However, this approach requires offshore wind farms to establish a strong grid voltage. To meet this requirement while fulfilling the dynamic characteristics of the DRU, this paper proposes an advanced grid-forming (GFM) control strategy for offshore wind turbines connected to DRU-HVDC. The strategy incorporates a P-U controller and a Q- ω controller based on reactive power synchronization. Furthermore, a novel virtual power-based pre-synchronization method and an adaptive virtual impedance technique are integrated into the proposed GFM control to improve system performance during wind turbine (WT) integration and low-voltage ride-through (LVRT) scenarios. The virtual power-based pre-synchronization method reduces voltage spikes during the integration of new wind turbines, while the adaptive virtual impedance technique effectively suppresses fault currents during low-voltage faults, enabling faster recovery. Simulation results validate the effectiveness of the proposed GFM control strategy, demonstrating improved start-up and LVRT performance through the pre-synchronization and adaptive virtual impedance methods. [ABSTRACT FROM AUTHOR]

The generation of sustainable energy through wind and hydrokinetic turbines, which convert the kinetic energy from fluid flows into mechanical energy, presents an attractive solution for diversifying the country energy matrix in response to climate change. Consequently, numerous studies have investigated the aerodynamic and hydrodynamic behaviors of various wind and hydrokinetic turbines using numerical simulations to understand their interaction with the surrounding fluid flows and enhance their performance. However, to validate these studies and aiming at improving the turbine design, experimental studies on a laboratory scale employing wind tunnels and hydraulic channels are essential. This work addresses the development and implementation of a reliable control system for experimentally evaluating the power coefficient (Cp) versus the tip speed ratio (TSR) curve of wind and hydrokinetic turbines. The control system, based on a DC motor acting as a generator and aligned with a commercial torque sensor, enables a precise control over the experimental setup. By obtaining and comparing the experimental performance curves of Cp versus TSR for both wind and hydrokinetic turbines with numerical results, the effectiveness and accuracy of the developed control system are demonstrated. A satisfactory fit between numerical and experimental results was achieved, underscoring the utility and reliability of the control system for assessing the turbine performance. [ABSTRACT FROM AUTHOR]

The "dual carbon" goal has made it a mainstream trend for new energy stations (NESs) and energy storage stations (ESSs) to jointly participate in market regulation. This paper proposes a multiple time scale distributed optimization method for NESs and ESSs based on the alternate direction multiplier method (ADMM). By first considering the uncertainty of new energy output and the volatility of electricity market prices, a multi time scale revenue model is constructed for day-ahead, intraday, and real-time markets. Then, the objective function is built by maximizing the comprehensive market revenues and is simplified using the synergistic effect of NESs and ESSs. Next, the simplified objective function is solved by the ADMM, and the revenues are maximized while each energy meets the relevant constraints. Lastly, the 33-node network topology is used to illustrate the feasibility of the proposed method. The simulation results show that after optimization, the output of NESs and ESSs can coordinate work in day-ahead, intraday, and real-time markets, while the abandonment power of wind and light is significantly improved. [ABSTRACT FROM AUTHOR]

This paper proposes a correction technique for bad data and high-precision analysis based on micro-phasor measurement unit (μPMU) data for a stable and reliable smart substation. First, a high-precision wide-area monitoring system (WAMS) with 35 μPMUs installed at Korea's Yeonggwang substation, which is connected to renewable energy sources (RESs), is introduced. Time-synchronized μPMU data are collected through the phasor data concentrator (PDC). A pre-processing program is implemented and utilized to integrate the raw data of each μPMU into a single comma-separated values (CSV) snapshot file based on the Timetag. After presenting the technique for identification and correction of event, duplicate, and spike bad data of μPMU, causal relationships are confirmed through the voltage and current fluctuations for a total of five states, such as T/L fault, tap-up, tap-down, generation, and generation shutdown. Additionally, the difference in active power between the T/L and the secondary side of the M.Tr is compared, and the fault ride through (FRT) regulations, when the fault in wind power generation (WP), etc., occurred, is analyzed. Finally, a statistical analysis, such as boxplot and kernel density, based on the instantaneous voltage fluctuation rate (IVFR) is conducted. As a result of the simulation evaluation, the proposed correction technique and precise analysis can accurately identify various phenomena in substations and reliably estimate causal relationships. [ABSTRACT FROM AUTHOR]

The wind power exchange system (WECS) covered in this paper consists of a voltage source inverter (VSI), a DSSB regulator, and an uncontrolled rectifier. An AC grid or a heavy inductive or resistive load (RL) can be supplied by this system. The DSSB is a recently developed DC-DC regulator consisting of an improved single-ended primary inductance regulator (SEPIC) followed by a buck regulator. It has a peak efficiency of 95–98% and a voltage gain of ( D   (1 + D) / (1 − D) . where D is the regulator transistor's on-to-off switching ratio. The proposed regulator improves the voltage stability and MPPT strategy (optimal or maximum power-point tracking). The combination of the DSSB and the proposed regulator improves the efficiency of the system and increases the power output of the wind turbine by reducing the harmonics of the system voltages and current. This method also reduces the influence of air density as well as wind speed variations on the MPPT strategy. Classical proportional–integral (PI) controllers are used in conjunction with a vector-controlled voltage source inverter, which adheres to the suggested DSSB regulator, to control the PMSM speed and d-q axis currents and to correct for current error. In addition to the vector-controlled voltage source inverter (which follows the recommended DSSB regulator), classical proportional–integral controllers are used to regulate the PMSM speed and d-q axis currents, and to correct current errors. In addition, a model Predictive Controller (PPC) is used with the pitch angle control (PAC) of WECS. This is done to show how well the proposed WECS (WECS with DSSB regulator) enhances voltage stability. A software-based simulation (MATLAB/Simulink) evaluates the results for ideal and unoptimized parameters of the WT and WECS under a variety of conditions. The results of the simulation show an increase in MPPT precision and output power performance. [ABSTRACT FROM AUTHOR]

The primary objective of this study is to evaluate the accuracy of different forecasting models for monthly wind farm electricity production. This study compares the effectiveness of three forecasting models: Autoregressive Integrated Moving Average (ARIMA), Seasonal ARIMA (SARIMA), and Support Vector Regression (SVR). This study utilizes data from two wind farms located in Poland—'Gizałki' and 'Łęki Dukielskie'—to exclude the possibility of biased results due to specific characteristics of a single farm and to allow for a more comprehensive comparison of the effectiveness of both time series analysis methods. Model parameterization was optimized through a grid search based on the Mean Absolute Percentage Error (MAPE). The performance of the best models was evaluated using Mean Bias Error (MBE), MAPE, Mean Absolute Error (MAE), and R2Score. For the Gizałki farm, the ARIMA model outperformed SARIMA and SVR, while for the Łęki Dukielskie farm, SARIMA proved to be the most accurate, highlighting the importance of optimizing seasonal parameters. The SVR method demonstrated the lowest effectiveness for both datasets. The results indicate that the ARIMA and SARIMA models are effective for forecasting wind farm energy production. However, their performance is influenced by the specificity of the data and seasonal patterns. The study provides an in-depth analysis of the results and offers suggestions for future research, such as extending the data to include multidimensional time series. Our findings have practical implications for enhancing the accuracy of wind farm energy forecasts, which can significantly improve operational efficiency and planning. [ABSTRACT FROM AUTHOR]

The large-scale integration of wind power significantly alters the voltage dynamic characteristics of power systems. Wind turbines have a weak ability to withstand grid disturbances and have difficulty in providing effective reactive power support during transient periods. The sensitivity of wind turbines to the grid voltage significantly increases the probability of large-scale, cascading off-grid events. This paper proposes a coordinated control strategy to enhance the transient reactive power support capability of doubly fed wind farms. The additional stator current demagnetization control reduces the risk of a crowbar protection action after a fault and ensures that the unit power is controllable. Based on the voltage–reactive power coupling relationship, each unit can produce reactive power according to the voltage–reactive power sensitivity matrix during the transient period. After the reactive power output of the unit reaches the limit, transient active and reactive combined control is further adopted to reduce the active power output of the unit to a certain extent and improve the reactive power support capability. Finally, two cases are built in the PSCAD to verify the effectiveness of the proposed control strategy. The results show that the proposed control strategy can enable the wind farm to output more reactive power to the grid during the transient period, effectively supporting the system voltage during the transient process and avoiding further deterioration of the fault. [ABSTRACT FROM AUTHOR]

Offshore wind farms connected in series, with each wind turbine connected in series with one another, enhance the coupling between them. Significant differences in wind speeds between neighboring DC wind turbines (DCWTs) might result in a substantial disparity in the output voltage, hence posing a risk of overvoltage. Nevertheless, implementing voltage-limiting configurations for DCWTs might lead to the dissipation of wind energy, thereby diminishing the wind farm's capacity to deliver electricity. This work introduces a half-bridge voltage balancing circuit (HVBC) topology as a solution to the issue of DCWT output voltage changes affecting the stable operation of wind farms. The proposed HVBC topology is designed specifically for large-capacity series-connected all-DC wind farms where wind speed variations occur. This design achieves power decoupling for series-connected all-DC wind farms by providing current compensation to the series-connected DCWTs. A control strategy is devised by examining the decoupling principle and operational characteristics of the HVBC. A 60 kV/48 MW tandem-type all-DC wind farm model consisting of six DCWTs in series is built in Matlab/Simulink. The model is then simulated to evaluate its performance under conditions of unequal wind speed, rapid changes in wind speed, and wind turbine failure shutdown. This research verifies the feasibility of the HVBC topology and improves the stability of the series-type all-DC wind farm. [ABSTRACT FROM AUTHOR]

Active power dispatch of new energy refers to an effective method of ensuring the stable operation and optimal economic benefits of new energy power systems through scientific and rational planning and control of active power output from new energy generation. However, as the proportion of new energy increases, the system's voltage support capacity decreases, leading to potential voltage collapse and oscillation issues. The Multiple Renewable Energy Station Short-Circuit Ratio (MRSCR) is a critical indicator of the system's voltage support capacity for power systems with high new energy penetration. This study aims to introduce MRSCR constraints into the active power dispatch to guarantee sufficient grid integration strength and stable operation. The MRSCR constraints are approximated using the least squares fitting method. Additionally, this study compares the economic benefits and margin of the indicators between wind and thermal power active scheduling models with and without considering MRSCR. Case studies show that the active scheduling model considering MRSCR constraints improves the MRSCR margin with minimal loss of economic benefits. [ABSTRACT FROM AUTHOR]

In this paper, a Takagi–Sugeno fuzzy parallel distributed compensation control (TS-PDCC) is proposed for low-frequency oscillation (LFO) suppression in wind energy-penetrated power systems. Firstly, the fuzzy C-mean algorithm (FCMA) is applied to cluster the daily average wind speed of the wind farm, and the obtained wind speed clustering center is used as the premise variable of TS-PDCC, which increases the freedom of parameter setting of the TS fuzzy model and is closer to the actual working environment. Secondly, based on the TS fuzzy model, the TS-PDCC is designed to adjust the active power output of the wind turbine for LFO suppression. To facilitate the computation of controller parameters, the stability conditions are transformed into a set of Linear Matrix Inequalities (LMIs) via the Schur complement. Subsequently, a Lyapunov function is designed to verify the stability of the wind energy-penetrated power system and obtain the parameter ranges. Simulation cases are conducted to verify the validity and superior performance of the proposed TS-PDCC under different operating conditions. [ABSTRACT FROM AUTHOR]

Undoubtedly, wind turbines are currently one of the most significant contributors to clean energy. Therefore, it is crucial to enhance the capability of wind turbines, which in turn leads to an increase in their dimensions. Nevertheless, only advanced control systems can guarantee the optimal and secure operation of these huge machines. On the other hand, the precise control of these modern wind turbines is only achievable through the use of highly specialised actuators. Despite their importance, actuators have historically been overlooked and seen as secondary components in control systems. However, in modern machines, actuators are required to manipulate multiple tonnes or manage thousands of volts and amperes within short times. Consequently, greater emphasis must be placed on their handling and operation. This study aims to review actuators for modern large wind energy converters from a control engineering perspective, using a tutorial approach. [ABSTRACT FROM AUTHOR]

This contribution examines the control problem for very large wind energy converters during shutdown operation and analyses the most important control approaches. The control methods make use of the built-in conventional control infrastructure, but control system reconfigurations are undertaken in order to meet the demands of the shutdown control operation. Hence, the torque controller as well as the collective pitch controller (CPC) are redesigned from their regulator functions to reference tracking control systems with constraints. In addition, the CPC is combined with a feedforward controller in order to gain responsiveness. Constraints in magnitude and rate are managed by a modified anti-windup mechanism. Simulations of a 20 MW reference wind turbine verify the performance of the approaches. [ABSTRACT FROM AUTHOR]

The primary objective of this study is to develop a simulation model for a liquid cooling plate (LCP) for insulated-gate bipolar transistor (IGBT) modules, with the aim of reducing the operating temperature of wind power converters (WPCs). The initial impetus for this study was the observation that the energy conversion efficiency of a WPC declines when the operating temperature of the IGBT module exceeds a critical threshold. Three LCPs, with and without heat sinks, were modelled under extreme conditions using the finite element simulation method. The effect of the number and height of the fins on the cooling efficacy was evaluated through the simulation and analysis of the LCP model with heat sinks. The results demonstrate that the optimal configuration, comprising five 10 mm fins and 13 10 mm struts, can achieve the following reductions: maximum temperature by 11.4 K, heat dissipation efficiency by 3.33%, pressure drop by 10.6 KPa, and pump power by 31.00%. Moreover, the findings suggest that the number of fins has a significant impact on temperature fluctuations, whereas the height of the fins exerts a markedly significant influence on pressure drop. [ABSTRACT FROM AUTHOR]

The current article elucidates a study centered on the development of an anemometer leveraging an inertial sensor for wind speed measurement in the northeast region of Brazil, focusing on renewable energy generation. The study encompassed a series of experiments aimed at calibrating the anemometer, analyzing the noise generated by the inertial sensor, and scrutinizing the data acquired during wind speed measurement. The calibration process unfolded in three stages: initial noise analysis, subsequent inertial data analysis, and the derivation of calibration curves. The first two stages involved experiments conducted at an average sampling rate of 10 Hz. Simultaneously, the third stage incorporated data collected over a 1 h duration while maintaining the same sampling rate. The outcomes underscore the suitability of the anemometer based on an inertial sensor for wind energy systems and diverse applications. While the wind readings from the prototype exhibit considerable fluctuations, a three-length moving average filter is applied to the prototype's output to mitigate these fluctuations. The calibration surface was established using observational data, and the resultant surface is detailed. Data analysis assumes paramount significance in wind speed measurement, and the K-NN algorithm demonstrated superior efficacy in estimating the correspondence between measured and control data. [ABSTRACT FROM AUTHOR]

The aim of this study was to improve the performances of three-bladed vertical-axis wind turbines with gap distance. For this purpose, turbine design conditions such as a gap ratio between the blades and the addition of blades were changed to provide performance increase, and an aerodynamic performance-enhancing performance setup placed in front of the vertical-axis wind turbine was also used. Therefore, in this study, the effects of gap distance and blade addition on wind turbine performance were investigated, especially by keeping the aspect ratio of the vertical-axis wind turbine constant. The investigation of the effects of turbine design parameters, such as the gap distance and additional blade number, on turbine performance was carried out using the ANSYS Fluent program with a numerical analysis method validated with experimental data. The turbine gap ratio, at which the maximum torque coefficient of a three-bladed vertical-axis wind turbine is obtained, was determined to be 40% without performance setup and 30% with performance setup. It was determined that the average torque coefficient value obtained from the turbine with the addition of turbine blades and with the performance setup increased by approximately 66% compared to the torque coefficient value obtained from the three-bladed turbine without the performance setup. It was also determined that the maximum power coefficient obtained from the vertical-axis wind turbine with optimum turbine design parameters with the performance setup increased by approximately 46% compared to the maximum power coefficient obtained from the version of the turbine without the performance setup. [ABSTRACT FROM AUTHOR]

With the excessive use of fossil fuels, atmospheric carbon dioxide (CO2) concentrations have risen dramatically in recent decades, leading to serious environmental and social issues linked to global climate change. The emergence of renewable energy sources, such as solar, tidal, and wind energy, has created favorable conditions for large-scale electricity production. Recently, significant attention has been drawn to utilizing renewable energy to catalyze the conversion of CO2 into fuels, producing substantial industrial feedstocks. In these CO2 conversion processes, the structure and performance of catalysts are critical. Metal-organic frameworks (MOFs) and their derivatives have emerged as promising electrocatalysts for CO2 reduction, offering advantages such as high surface area, porosity, exceptional functionality, and high conversion efficiency. This article provides a comprehensive review of structural regulation strategies for copper-based MOFs, highlighting innovative mechanisms like synergistic bimetallic catalysis, targeted doping strategies, and the construction of heterostructures. These novel approaches distinguish this review from previous studies, offering new insights into the electrocatalytic performance of copper-based MOFs and proposing future research directions for improved catalyst design. [ABSTRACT FROM AUTHOR]

The southeastern rock base sea area is the most abundant wind resource area, and it is also the mainstream construction site of offshore wind farms (OWFs) in China. The weathered residual soil is the main seabed component in the rock base area, which is the important bearing stratum of the offshore wind turbine foundation. Previous studies on the mechanical properties of seabed materials and bearing characteristics of the pile foundations in OWFs have mainly focused on the submarine soil-based seabed, resulting in a lack of direct reference for the construction of offshore wind power in the rocky seabed. Therefore, the mechanical properties of weathered residual soil and the bearing behaviors of monopile foundations are mainly investigated in this study. Firstly, dynamic triaxial tests are conducted on the weathered residual soil, and experiments analyze insight into the evolution law of the hysteresis curve, cumulative strain, and stiffness attenuation. Then, the horizontal loading behaviors of monopile foundations in residual soil are analyzed by numerical simulations; more critically, the service performances under wind and wave coupling loads are evaluated, which provide a direct theoretical basis for the construction and design of offshore wind turbine foundations in rock base seabeds. [ABSTRACT FROM AUTHOR]

The global pursuit of renewable energy has significantly accelerated offshore wind energy development. Floating offshore wind turbines (FOWTs) are increasingly in the spotlight as they offer superior capabilities for harnessing abundant wind resources in deep-water areas, outperforming traditional fixed-bottom turbines. The deployment and station-keeping of these floating structures are critically dependent on robust mooring systems and the precise selection of anchoring solutions. This paper provides an overview of various anchors, including driven and suction caissons, torpedo, and drag anchors, and their applications in real-world projects. These commonly used anchors were discussed in relation to mooring types, soil conditions, and expected bearing capacities. Torpedo anchor installation failures have been reported in cases where excessive tilt angles occur during deployment. This motivates us to present an in-depth study on the importance of directional stability during installation of torpedo anchors. The study will utilize computational fluid dynamics Star-CCM+ 2402 to analyze and assess the impact of the center of gravity configuration on stabilization. Additionally, theoretical formulas will be used to estimate the holding capacity that the torpedo anchor can provide. These insights are designed to assist wind energy developers in making informed and effective anchoring decisions for floating wind turbine projects. [ABSTRACT FROM AUTHOR]

The mesoscale interaction between sea surface temperature (SST) and wind is a crucial factor influencing oceanic and atmospheric conditions. To investigate the mesoscale coupling characteristics of the Yellow Sea and East China Sea, we applied a locally weighted regression filtering method to extract mesoscale signals from Quik-SCAT wind field data and AMSR-E SST data and found that the mesoscale coupling intensity is stronger in the Yellow Sea during the spring and winter seasons. We calculated the mesoscale coupling coefficient to be approximately 0.009 N·m−2/°C. Subsequently, the Tikhonov regularization method was used to establish a mesoscale empirical coupling model, and the feedback effect of mesoscale coupling on the ocean was studied. The results show that the mesoscale SST–wind field coupling can lead to the enhancement of upwelling in the offshore area of the East China Sea, a decrease in the upper ocean temperature, and an increase in the eddy kinetic energy in the Yellow Sea. Diagnostic analyses suggested that mesoscale coupling-induced variations in horizontal advection and surface heat flux contribute most to the variation in SST. Moreover, the increase in the wind energy input to the eddy is the main factor explaining the increase in the eddy kinetic energy. [ABSTRACT FROM AUTHOR]

To mitigate accidents in submarine cable construction within the rapidly expanding offshore wind power sector, this study employed the analytic hierarchy process (AHP) and risk matrix method (LS) to assess the risks associated with identified factors. Based on project research and expert consultations, five primary and twenty-two secondary risk factors were identified. AHP was utilized to rank the primary risk factors by severity, probability, and detection difficulty, with the highest risk being the environmental impact, followed by third-party destruction and worker error. LS was applied to rank the secondary risk factors by likelihood and severity, with the highest risks being complex submarine topography, low underwater visibility, and fishing operations. The study proposes risk reduction measures based on these evaluations and offers methodological guidance for improving construction safety in similar enterprises. [ABSTRACT FROM AUTHOR]

Studies demonstrate that the reduced frequency k is influenced by the incoming wind speed U0 and the rotor speed n. As a dimensionless parameter, k characterizes the stability of the flow field, which is a critical factor affecting the performance of vertical-axis wind turbines (VAWTs). This paper investigates the impact of k on the performance of straight-blade vertical-axis wind turbines (H-VAWT). The findings indicate that 0.05 is the critical value of k. The same k results in a similar flow field structure, yet the performance changes vary with different U0. A decrease in n or an increase in U0 leads to an increase in the average value and fluctuation of k, which subsequently reduces the rotor rotation torque Cm and decreases the maximum wind energy utilization rate Cpmax. This reduction in Cpmax weakens the stability of the flow field. Additionally, the high-speed area of the blade's trailing edge velocity trajectory at  θ = 0 ° ,  θ = 120 ° , and  θ = 240 °  expands with increasing range. Velocity dissipation in the high-speed area of the trailing edge affects the stability of the flow field within the rotor. [ABSTRACT FROM AUTHOR]

The transmission end of large-scale wind power generation bases faces challenges such as high AC-DC coupling strength, low system inertia, and weak voltage support capabilities. Deploying distributed synchronous condensers (SCs) within and around wind farms can effectively provide transient reactive power support, enhance grid system inertia at the transmission end, and improve dynamic frequency support capabilities. However, the high investment and maintenance costs of SCs hinder their large-scale deployment, necessitating the investigation of optimal SC configuration strategies at critical nodes in the transmission grid. Initially, a node inertia model was developed to identify weaknesses in dynamic frequency support, and a critical inertia constraint based on node frequency stability was proposed. Subsequently, a multi-timescale reactive power response model was formulated to quantify the impact on short-circuit ratio improvement and transient overvoltage suppression. Finally, a two-stage optimal configuration strategy for distributed SCs at the transmission end was proposed, considering dynamic frequency support and transient voltage stability. In the first stage, the optimal SC configuration aimed to maximize system inertia improvement per unit investment to meet dynamic frequency support requirements. In the second stage, the configuration results from the first stage were adjusted by incorporating constraints for enhancing the multiple renewable short-circuit ratio (MRSCR) and suppressing transient overvoltage. The proposed model was validated using the feeder grid of a large energy base in western China. The results demonstrate that the optimal configuration scheme effectively suppressed transient overvoltage at the generator end and significantly enhanced the system's dynamic frequency support strength. [ABSTRACT FROM AUTHOR]