Search Results (141)

To maintain power system stability and supply quality when integrating doubly fed induction generator (DFIG)-based wind energy conversion systems (DFIG-WECSs), regulators regularly update grid codes specifying low voltage ride-through (LVRT) requirements. This paper presents a systematic literature review (SLR) on the use of STATCOMs to enhance LVRT capability in DFIG-WECSs. Objectives included a structured literature search, bibliographic analysis, thematic synthesis, trend identification, and proposing future research directions. A PRISMA-based methodology guided the review, utilising PRISMA 2020 for Abstracts in the development of the abstract. The final search was conducted on Scopus (31 March 2025). Eligible studies were primary research in English (2009–2014) where STATCOM was central to LVRT enhancement; exclusions included non-English studies, duplicates, reviews, and studies without a STATCOM focus. Quality was assessed using an adapted Critical Appraisal Skills Programme (CASP) tool. No automation or machine learning tools were used. Thirty-eight studies met the criteria and were synthesised under four themes: operational contexts, STATCOM-based schemes, control strategies, and optimisation techniques. Unlike prior reviews, this study critically evaluates merits, limitations, and practical challenges. Trend analysis shows evolution from hardware-based fault survival strategies to advanced optimisation and coordinated control schemes, emphasising holistic grid stability and renewable integration. Identified gaps include cyber-physical security, techno-economic assessments, and multi-objective optimisation. Actionable research directions are proposed. By combining technical evaluation with systematic trend analysis, this review clarifies the state of STATCOM-assisted LVRT strategies and outlines pathways for future innovation in DFIG-WECS integration. Full article

During voltage dips, wind turbines must remain connected to the electrical grid and contribute to voltage stabilization. This study analyzes the impact of voltage dips arising from grid faults on Doubly Fed Induction Generator (DFIG) based Wind Energy Conversion Systems (WECSs). This paper presents a review of the technical regulations for integrating the Algerian electricity grid with the Low Voltage Ride Through (LVRT) system, along with specific requirements for renewable power generation installations. Additionally, the modeling and control strategy of DFIG based WECS has been outlined. Voltage dips can induce excessive currents that threaten the DFIG rotor and may cause harmful peak oscillations in the DC-link voltage, and can lead to turbine speed increase due to the sudden imbalance between the mechanical input torque and the reduced electromagnetic torque. To counter this, a modified vector control and crowbar protection mechanism were integrated. Its role is to mitigate these risks, thereby ensuring the system remains stable and operational through grid faults. The proposed system successfully meets the stringent Algerian LVRT requirements, with voltage dipping to zero for 0.3 s and recovering gradually. Simulations confirm that rotor and stator currents remain within safe limits (peak rotor current at 0.93 $\mathrm{p}\mathrm{u}$, and peak stator current at 1.36 $\mathrm{p}\mathrm{u}$). The DC-link voltage, despite a transient rise due to the continued power conversion from the rotor-side converter during the grid fault, was effectively stabilized and maintained within safe operating margins (with less than 14% overshoot). This stability was achieved as the crowbar ensured power balance by managing active and reactive power. Notably, the turbine rotor speed demonstrated stability, peaking at 1.28 $\mathrm{p}\mathrm{u}$ within mechanical limits. Full article

All grid faults can cause significant problems within the power grid, including disconnection or malfunctions of wind energy conversion systems (WECSs) connected to the power grid. This study proposes a comparative analysis of the fault ride-through capability of a WECS-based permanent magnet synchronous generator (PMSG) system. To overcome these issues, active crowbar and capacitive bridge fault current limiter-based machine learning algorithm protection methods are implemented within the WECS system, both separately and in a hybrid. The regression approach is applied for the machine-side converter (MSC) and the grid side converter (GSC) controllers, which involve numerical data. The classification method is employed for protection system controllers, which work with data in distinct classes. These approaches are trained on historical data to predict the optimal control characteristics of the wind turbine system in real time, taking into account both fault and normal operating conditions. The neural network trilayered model has the lowest root mean squared error and mean squared error values, and it has the highest R-squared values. Therefore, the neural network trilayered model can accurately model the nonlinear relationships between its variables and demonstrates the best performance. The neural network trilayered model is selected for the MSC control system in this study. On the other hand, support vector machine regression is selected for the GSC controller due to its superior results. The simulation results demonstrate that the proposed machine learning algorithm performance for WECS based on a PMSG is robustly utilized under different operating conditions during all grid faults. Full article

Wind energy has become a cornerstone of sustainable electricity generation, yet the reliable integration of wind energy conversion systems (WECSs) into modern grids remains challenged by dynamic variations in wind speed and stringent fault ride-through (FRT) requirements. Among the available technologies, the Doubly Fed Induction Generator (DFIG) and the Permanent Magnet Synchronous Generator (PMSG) dominate commercial applications; however, a comprehensive comparative assessment under diverse grid and fault scenarios is still limited. This study addresses this gap by systematically evaluating the performance of DFIG- and PMSG-based WECSs across three operating stages: (i) normal operation at constant speed, (ii) variable wind speed operation, and (iii) grid fault conditions including single-line-to-ground, line-to-line, and three-phase faults. To enhance fault resilience, a DC-link Braking Chopper is integrated into both systems, ensuring a fair evaluation of transient stability and compliance with low-voltage ride-through (LVRT) requirements. The analysis, performed using MATLAB/Simulink, focuses on active and reactive power, rotor speed, pitch angle, and DC-link voltage dynamics. The results reveal that PMSG exhibits smoother transient responses and lower overshoot compared to DFIG. Under fault conditions, the DC-link Braking Chopper effectively suppresses voltage spikes in both systems, with DFIG achieving faster reactive power recovery in line with grid code requirements, while PMSG ensures more stable rotor dynamics with lower oscillations. The findings highlight the complementary strengths of both technologies and provide useful insights for selecting appropriate WECS configurations to improve grid integration and fault ride-through capability. Full article

Extreme Operational Gusts (EOGs) are critical for assessing the effects of extreme winds on Wind Energy Conversion Systems (WECSs). In regions like La Ventosa, Oaxaca, Mexico—characterized by strong and frequent gusts—the performance and reliability of low-power WECSs can be severely impacted. Traditionally, EOG effects have been analyzed using mathematical models from the IEC 61400-2 standard, which assumes a symmetric gust taxonomy. However, field data have revealed inconsistencies with this model, leading to the development of new asymmetrical taxonomies, such as Manwell’s. This study presents a taxonomic characterization of EOGs in La Ventosa using 1 Hz wind speed data collected over one year (December 2017–November 2018), during which 1655 events were detected. A dedicated detection method was implemented to capture gusts with amplitudes and durations exceeding the IEC range, allowing systematic classification of previously unrecognized patterns. Based on these results, a new taxonomy and a mathematical model were developed to simulate any identified gust. These tools provide more realistic simulations for improving WECS protection under extreme conditions. The analysis shows that Manwell’s taxonomy represents 50.39% of events, the proposed classification 37.04%, and IEC 61400-2 only 12.57%, underscoring its limited applicability to high-wind sites like La Ventosa. Full article

Fault-tolerant strategies have received increasing attention recently, as reliability requirements have become more stringent. This has drawn significant attention to multiphase machines, due to their inherent fault-tolerance capabilities. Although multiphase machines have been extensively studied as motors since the late 1960s, their use as generators is still in its infancy. Moreover, research on their fault-tolerant capabilities and impact on the power grid remains very limited. With the global expansion of the wind energy sector, the continuous increase in turbine capacities, and the shift in wind energy markets toward offshore wind farms, there is a growing need for studies that investigate the integration of multiphase machines with fault-tolerant strategies and that evaluate their performance and impact on the grid. Therefore, this paper aims to investigate a wind energy conversion system (WECS) based on a five-phase permanent magnet synchronous generator (PMSG) and to evaluate its performance under two fault scenarios: a single-phase open-circuit fault and a double-phase open-circuit fault. A fault-tolerant control strategy is applied in both cases to evaluate its effectiveness under varying wind speeds. The study is carried out using simulation tools developed in MATLAB/Simulink. Full article

The ocean offers abundant wind and wave energy resources. This paper proposes an integrated concept that co-locates a semi-submersible floating wind platform with wave energy converters (WECs) to exploit the geographical consistency of these resources. By sharing the platform foundation and power transmission infrastructure, this integrated system enhances the utilization efficiency of marine space and renewable energy. Inspired by the principles of the Tuned Mass Damper (TMD) and leveraging mature hydraulic technologies from wave energy conversion and offshore drilling heave compensation systems, this study introduces a novel scheme. This scheme integrates a heave plate with a hydraulic Power Take-Off (PTO) system, functionally acting as a wave energy converter, to the floating platform. The primary objective is to mitigate the platform’s motion response while simultaneously generating electricity. The research investigates the motion performance improvement of this integrated platform under South China Sea conditions. The results demonstrate that the proposed WEC–PTO system not only improves the platform’s wave resistance and adaptability to deep-sea environments but also increases the overall efficiency of marine energy equipment deployment. Full article

This study assesses the feasibility and profitability of marine hybrid clusters, combining wave energy converters (WECs) and offshore wind turbines (OWTs) to power households and marine aquaculture. Researchers analyzed two coastal sites: La Serena, Chile, with high and consistent wave energy resources, and Ensenada, Mexico, with moderate and more variable wave power. Two WEC technologies, Wave Dragon (WD) and Pelamis (PEL), were evaluated alongside lithium-ion battery storage and green hydrogen production for surplus energy storage. Results show that La Serena’s high wave power (26.05 kW/m) requires less hybridization than Ensenada’s (13.88 kW/m). The WD device in La Serena achieved the highest energy production, while PEL arrays in Ensenada were more effective. The PEL-OWT cluster proved the most cost-effective in Ensenada, whereas the WD-OWT performed better in La Serena. Supplying electricity for seaweed aquaculture, particularly in La Serena, proves more profitable than for households. Ensenada’s clusters generate more surplus electricity, suitable for the electricity market or hydrogen conversion. This study emphasizes the importance of tailoring emerging WEC systems to local conditions, optimizing hybridization strategies, and integrating consolidated industries, such as aquaculture, to enhance both economic and environmental benefits. Full article

This paper presents a robust and computationally efficient fault classification framework for wind energy conversion systems (WECS), built upon a Robust Random Vector Functional Link Network (Robust-RVFLN) and validated through real-time simulations on a Real-Time Digital Simulator (RTDS). Unlike existing studies that depend on high-dimensional feature extraction or purely data-driven deep learning models, our approach leverages a compact set of five statistically significant and physically interpretable features derived from rotor torque, phase current, DC-link voltage, and dq-axis current components. This reduced feature set ensures both high discriminative power and low computational overhead, enabling effective deployment in resource-constrained edge devices and large-scale wind farms. A synthesized dataset representing seven representative fault scenarios—including converter, generator, gearbox, and grid faults—was employed to evaluate the model. Comparative analysis shows that the Robust-RVFLN consistently outperforms conventional classifiers (SVM, ELM) and deep models (CNN, LSTM), delivering accuracy rates of up to 99.85% for grid-side line-to-ground faults and 99.81% for generator faults. Beyond accuracy, evaluation metrics such as precision, recall, and F1-score further validate its robustness under transient operating conditions. By uniting interpretability, scalability, and real-time performance, the proposed framework addresses critical challenges in condition monitoring and predictive maintenance, offering a practical and transferable solution for next-generation renewable energy infrastructures. Full article

In this paper, a nonlinear power transfer matrix model is presented for power control of Permanent Magnet Synchronous Generator (PMSG) wind turbines, incorporating the DC link dynamics to account for transient stability, thereby clarifying the technical aspect and purpose. The rising penetration of wind turbines (WTs) into the power grid necessitates that they remain connected during and after faults to ensure system reliability. During voltage dips, the stator and grid-side converter (GSC) of a permanent magnet synchronous generator (PMSG) system are directly impacted by the sudden voltage changes. These disturbances can induce large transient voltages and currents in the stator, which in turn may lead to uncontrolled current flow in the rotor circuit and stress the converter components. Moreover, Low Voltage Ride-Through (LVRT) is a critical requirement for grid connection to Wind Energy Conversion Systems (WECS). It ensures that WTs remain connected and operational during short periods of grid voltage dips (faults), instead of disconnecting immediately. This capability is essential for maintaining grid stability. However, in this paper, the authors propose an LVRT scheme for a grid-connected PMSG-based WECS. A sequence of attempts was performed to validate the effectiveness of the proposed control scheme under fault conditions and to improve its overall performance. Full article

Wave energy is a highly concentrated energy resource with five times higher energy density than wind and at least ten times the power density of solar energy. It is expected to make a major contribution to addressing climate change and to help end our dependency on fossil fuels. Many ingenious wave energy conversion methods have been put forward, and a large number of wave energy converters (WECs) have been developed. However, to date, wave energy conversion technology is still in the demonstration application stage. Key issues such as survivability, reliability, and efficient conversion still need to be solved. The major hurdle is the fact that ocean waves provide a slow-moving, high-magnitude force, whereas most electric generators operate at high rotary speed and low torque. Coupling the slow-moving, high-magnitude force of ocean waves normally requires conversion to a high-speed, low-magnitude force as an intermediate step before a rotary generator is applied. This, in general, tends to severely limit the overall efficiency and reliability of the converter and drives the capital cost of the converter well above an acceptable commercial target. Magnetohydrodynamic (MHD) wave energy conversion makes use of MHD generators in which a conducting fluid passes through a very strong magnetic field to produce an electric current. In contrast to alternatives, the relatively slow speed at which the fluid traverses the magnetic field makes it possible to directly couple to ocean waves with a high-magnitude, slowly moving force. The MHD generator provides an excellent match to the mechanical impedance of an ocean wave, and therefore, an MHD WEC has no rotating mechanical parts with high speeds, no complex control process, and has good response to low sea states and high efficiency under all working conditions. This review introduces the system composition, working process, and technical features of WECs based on MHD generators first. Then, the research development, key points, and issues of wave energy conversion technology based on MHD generators are presented in detail. Finally, the problems to be solved and the future research directions of wave energy conversion based on MHD generators are pointed out. Full article

Fault diagnosis is crucial for ensuring the reliability and safety of wind energy conversion systems (WECSs). However, existing methods are often specific to components or specific types of wind turbines and face challenges, such as difficulty in threshold setting and low accuracy in diagnosing faults at early stages. To address these challenges, this paper proposes a novel fault diagnosis method based on self-organizing neural networks (SONNs) and probability density functions (PDFs). First, an improved set-valued observer (ISVO) is designed to accurately estimate the states of WECSs, considering the time delay and unknown nonlinearity of overall model. Then, the PDF is derived by fitting the estimation error data to characterize three common multiplicative faults of the pitch system actuators. Two types of SONNs are developed to cluster the parameter sets of the PDF. Finally, the PDFs of the estimation error are reconstructed based on the clustering results, thereby designing fault diagnosis strategies that enable a rapid and highly accurate diagnosis of early-stage faults. Simulation results demonstrate that the proposed strategies achieved an early fault diagnosis accuracy rate of over 90%, with the fastest diagnosis time being approximately 0.11 s. Under the same fault conditions, the diagnosis time is 1 s faster than that of a k-means-based fault diagnosis strategy. This study provides a threshold-free, high-accuracy, and rapid fault diagnosis strategy for early fault diagnosis in WECS. By combining neural networks, the proposed method addresses the issue of threshold dependency in fault diagnosis, with potential applications in improving the reliability and safety of wind power generation. Full article

This paper presents the application of a proposed hybrid control strategy that is designed to enhance the performance and robustness of a grid-connected wind energy conversion system (WECS) using a Five-Phase Permanent Magnet Synchronous Generator (FP-PMSG). The proposed approach combines the second-order terminal sliding mode control technique (SO-STA) with the super-twisting algorithm (STA), with the main goal of benefitting from both their advantages while addressing their limitations. Indeed, the sole application of the SO-STA ensures rapid convergence and robust performances in nonlinear systems, but it leads to chattering and reduces the whole system’s efficiency. Therefore, by incorporating the STA, the obtained hybrid control can mitigate this issue by ensuring smoother control actions and a superior dynamic response. This designed hybrid control strategy improves the adaptability of the control system to wind fluctuations and enhances the system’s robustness against external disturbances and uncertainties, leading to higher reliability and efficiency in the wind energy conversion system. Furthermore, the proposed hybrid control allows optimizing the power extraction and boosting the WECS’s efficiency. It is worth clarifying that, besides this proposed control, a sliding mode controller is used for the grid side converter (GSC) and DC link voltage to ensure stable power transfer to the grid. The obtained simulation results demonstrate the effectiveness of the proposed strategy in improving the stability, robustness, and efficiency of the studied WECS under dynamic conditions, creating a promising solution for control in renewable energy systems operating under severe conditions. Full article

The significance of the Hybrid Renewable Energy System (HRES) is profound in the current scenario owing to the mounting energy requirements, pressing ecological concerns and the pursuit of transitioning to greener energy alternatives. Thereby, the modeling and design of HRES, encompassing PV–WECS–Battery, which mainly focuses on efficient power conversion and advanced control strategy, is proposed. The voltage gain of the PV system is improved using the Re-lift Luo converter, which offers high efficiency and power density with minimized ripples and power losses. Its voltage lift technique mitigates parasitic effects and delivers improved output voltage for grid synchronization. To control and stabilize the converter output, a Proportional–Integral (PI) controller tuned using a novel hybrid algorithm combining Grey Wolf Optimization (GWO) with Hermit Crab Optimization (HCO) is implemented. GWO follows the hunting and leadership characteristics of grey wolves for improved simplicity and robustness. By simulating the shell selection behavior of hermit crabs, the HCO adds diversity to exploitation. Due to these features, the hybrid GWO–HCO algorithm enhances the PI controller’s capability of handling dynamic non-linear systems, generating better control accuracy, and rapid convergence to optimal solutions. Considering the Wind Energy Conversion System (WECS), the PI controller assures improved stability despite fluctuations in wind. A Recurrent Neural Network (RNN)-based battery management system is also incorporated for accurate monitoring and control of the State of Charge (SoC) and the terminal voltage of battery storage. The simulation is conducted in MATLAB Simulink 2021a, and a lab-scale prototype is implemented for real-time validation. The Re-lift Luo converter achieves an efficiency of 97.5% and a voltage gain of 1:10 with reduced oscillations and faster settling time using a Hybrid GWO–HCO–PI controller. Moreover, the THD is reduced to 1.16%, which indicates high power quality and reduced harmonics. Full article

This paper presents the design and performance evaluation of an experimental platform that emulates the static and dynamic behavior of a 3 kW Wind Energy Conversion System (WECS). The platform includes a wind turbine emulator (WTE) using a separately excited DC motor (SEDCM) as the prime mover, coupled with a grid-connected doubly-fed induction generator (DFIG). This setup enables comprehensive laboratory studies of a WECS without the need for large-scale field installations. A novel inertia compensation strategy is implemented to ensure the SEDCM accurately replicates the power and torque characteristics of a real wind turbine across various wind profiles. The DFIG was chosen for its high efficiency at variable wind speeds and its reduced power converter requirements compared to other generators. The control strategy for the DFIG is detailed, highlighting its performance and seamless integration within the system. Unlike most studies focusing on generators connected to simple loads, this research considers a grid-connected system, which introduces additional challenges and requirements. This study thoroughly investigates the grid-connected converter, addressing specific demands for grid connection and ensuring compliance with grid standards. Experimental results validate the effectiveness of the emulator, demonstrating its potential as a key tool for optimizing wind turbine control strategies and real-time algorithm validation, and enhancing the performance and reliability of renewable energy systems. Full article