Search Results (136)

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

In this article, we propose, for the first time, to apply the flux-switching permanent magnet (OR-FSPM) generator to the oscillating water column wave energy conversion (OWC-WEC), and a novel dual three-phase 24-slot/46-pole OR-FSPM generator for OWC-WEC is designed and analyzed. The feasible phase-shift angle (PH-Angle) between the two sets of windings, namely 0°, 30° and 60°, is analyzed. The electromagnetic performance of the generator under three winding configurations is investigated, including PM flux linkage, back electromotive force (EMF), open-circuit rectified voltage, inductance, cogging torque, electromagnetic torque and unbalanced magnetic force (UMF). The prototype is manufactured, and the experimental results are consistent with that of the finite-element analysis (FEA) results. The generator with 0° and 60° PH-Angle winding configuration has stronger fault tolerance. When the 30° PH-Angle winding configuration is adopted, it has the maximum back-EMF fundamental amplitude, maximum average electromagnetic torque and the minimum torque ripple, and there is no UMF when a single set of windings is running. Therefore, the proposed novel OR-FSPM generator with 30° PH-Angle winding configuration is more suitable for OWC-WEC. 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

Integrating renewable energy sources into power systems is crucial for achieving global decarbonization goals, with wind energy experiencing the most growth due to technological advances and cost reductions. However, large-scale wind farm integration presents challenges in balancing power generation and demand, mainly due to wind variability and the reduced system inertia from conventional generators. This review offers a comprehensive analysis of the current literature on wind power forecasting and frequency control techniques to support grid-friendly wind energy integration. It covers strategies for enhancing wind power management, focusing on forecasting models, frequency control systems, and the role of energy storage systems (ESSs). Machine learning techniques are widely used for power forecasting, with supervised machine learning (SML) being the most effective for short-term predictions. Approximately 33% of studies on wind energy forecasting utilize SML. Hybrid frequency control methods, combining various strategies with or without ESS, have emerged as the most promising for power systems with high wind penetration. In wind energy conversion systems (WECSs), inertial control combined with primary frequency control is prevalent, leveraging the kinetic energy stored in wind turbines. The review highlights a trend toward combining fast frequency response and primary control, with a focus on forecasting methods for frequency regulation in WECS. These findings emphasize the ongoing need for advanced forecasting and control methods to ensure the stability and reliability of future power grids. Full article

This paper introduces a robust system designed to effectively manage and enhance the electrical output of a Wind Energy Conversion System (WECS) using a Cascaded Doubly Fed Induction Generator (CDFIG) connected to a power grid. The solution that was investigated is the use of a CDFIG that is based on a variable-speed wind power conversion chain. It comprises the electrical and mechanical connection of two DFIGs through their rotors. The originality of this paper lies in the innovative application of a fuzzy logic controller (FLC) in combination with a CDFIG for a WECS. To demonstrate that this novel configuration enhances control precision and performance in WECSs, we conducted a comparison of three different controllers: a proportional–integral (PI) controller, a fractional PID (FPID) controller, and a fuzzy logic controller (FLC). The results highlight the potential of the proposed system in optimizing power generation and improving overall system stability. It turns out that, according to the first results, the FLC performed optimally in terms of tracking and rejecting disturbances. In terms of peak overshoot for power and torque, the findings indicate that the proposed FLC-based technique (3.8639% and 6.9401%) outperforms that of the FOPID (11.2458% and 10.9654%) and PI controllers (11.4219% and 11.0712%), respectively. These results demonstrate the superior performance of the FLC in reducing overshoot, providing better control stability for both power and torque. In terms of rise time, the findings show that all controllers perform similarly for both power and torque. However, the FLC demonstrates superior performance with a rise time of 0.0016 s for both power and torque, compared to the FOPID (1.9999 s and 1.9999 s) and PI (0.0250 s and 0.0247 s) controllers. This highlights the FLC’s enhanced responsiveness in controlling power and torque. In terms of settling time, all three controllers have almost the same performance of 1.9999. An examination of total harmonic distortion (THD) was also employed to validate the superiority of the FLC. In terms of power quality, the findings prove that a WECS based on an FLC (0.93%) has a smaller total harmonic distortion (THD) compared to that of the FOPID (1.21%) and PI (1.51%) controllers. This system solves the problem by removing the requirement for sliding ring–brush contact. Through the utilization of the MATLAB/Simulink environment, the effectiveness of this control and energy management approach was evaluated, thereby demonstrating its capacity to fulfill the objectives that were set. Full article

This paper presents the design and analysis of an efficient energy management system for a wind lens integrated with a permanent magnet synchronous generator (PMSG) and a zeta converter. The wind lens, a ring-shaped structure encircling the rotor, enhances the turbine’s capability to capture wind energy by increasing the wind influx through the turbine. In the contemporary wind energy sector, PMSGs are extensively employed due to their superior performance characteristics. This study integrates a 1 kW PMSG system with a wind lens to optimize power extraction from the wind energy conversion system (WECS) under varying wind speeds. A comparative analysis of different control strategies for maximum power point tracking (MPPT) is conducted, including the incremental conductance (INC) method and the perturb and observe (P&O) method. The performance of the MPPT controller integrated with the wind lens-based PMSG system is assessed based on output DC voltage and power delivered to the load. To evaluate the overall effectiveness of these control strategies, both steady-state voltage and dynamic response under diverse wind conditions are examined. The system is modeled and simulated using the MATLAB R2023a/Simulink 9.1 software, and the simulation results are validated to demonstrate the efficacy of the proposed energy management system. Full article

This paper presents an innovative scheme to enhance the efficiency of power extraction from wind energy conversion systems (WECSs) under random loads. The study investigates how stochastic load consumption, modeled and predicted using a Markov chain process, impacts WECS efficiency. The suggested approach regulates the rectifier voltage rather than the rotor speed, making it a sensorless and reliable method for small-scale WECSs. Nonlinear WECS dynamics are represented using Takagi–Sugeno (TS) fuzzy modeling. Furthermore, the closed-loop system’s stochastic stability and recursive feasibility are guaranteed regardless of random load changes. The performance of the suggested controller is compared with the traditional perturb-and-observe (P&O) algorithm under varying wind speeds and random load variations. Simulation results show that the proposed approach outperforms the traditional P&O algorithm, demonstrating higher tracking efficiency, rapid convergence to the maximum power point (MPP), reduced steady-state oscillations, and lower error indices. Enhancing WECS efficiency under unpredictable load conditions is the primary contribution, with simulation results indicating that the tracking efficiency increases to $99.93\%$. Full article

The dynamical modeling and power optimization of floating wind–wave platforms, especially in regard to configurations based on constrained floating multi-body systems, lack in-depth systematic investigation. In this study, a floating wind-flap platform consisting of a flap-type wave energy converter and a floating offshore wind turbine is solved in the frequency domain considering the mechanical and hydrodynamic couplings of floating multi-body geometries and a model that suits the constraints of the hinge connection, which can accurately calculate the frequency domain dynamic response of the flap-type WEC. The results are compared with bottom-fixed flap-type wave energy converters in the absence of coupling with a floating wind platform. Moreover, combined with traditional optimization methods of power take-off systems for wave energy conversion, an optimization method is developed to suit the requirements of floating wind-flap platform configurations. The results are drawn for a specific operation site in the South China Sea, whereas a sensitivity analysis of the parameters is performed. It is found that the floating wind-flap platform has better wave energy absorption performance in the low-frequency range than the bottom-fixed flap-type wave energy converter; the average power generation in the low-frequency range can increase by up to 150 kW, mainly due to constructive hydrodynamic interactions, though it significantly fluctuates from the sea waves’ frequency range to the high-frequency range. Based on spectral analysis, operational results are drawn for irregular sea states, and the expected power for both types of flap-type WECs is around 30 kW, which points to a similar wave energy absorption performance when comparing the bottom-fixed flap with the flap within the hybrid configuration. Full article

This study presents the coupling-memory-sampled data control (CMSDC) design for the Takagi–Sugeno (T-S) fuzzy system that solves the stabilization issue of a surface-mounted permanent-magnet synchronous generator (PMSG)-based wind energy conversion system (WECS). A fuzzy CMSDC scheme that includes the sampled data control (SDC) and memory-sampled data control (MSDC) is designed by employing a Bernoulli distribution order. Meanwhile, the membership-function-dependent (MFD) $H_{\infty }$ performance index is presented, mitigating the continuous-time fuzzy system’s disturbances. Then, by using the Lyapunov–Krasovskii functional with the MFD $H_{\infty }$ performance index, the data of the sampling pattern, and a constant signal transmission delay, sufficient conditions are derived. These sufficient conditions are linear matrix inequalities (LMIs), ensuring the global asymptotic stability of a PMSG-based WECS under the designed control technique. The proposed method is demonstrated by a numerical simulation implemented on the PMSG-based WECS. Finally, Rossler’s system demonstrates the effectiveness and superiority of the proposed method. Full article

A modeling technique for a nearshore hybrid wind–wave energy converter system (HWWECS) is presented in this research. The model consists of the buoy, wind system, and generator, allowing simulation of the HWWECS’s behavior in response to varied wave circumstances, such as different wave heights and periods. The HWWECS is made up of two buoy units and a wind system that work together to power a generator. The Wave Analysis at Massachusetts Institute of Technology (WAMIT) software is used to calculate the hydrodynamic forces. A variable inertia hydraulic flywheel is used to bring the system into resonance with incident wave frequencies in order to improve power production. Full article

Emerging magnetic lead screws (MLSs) have been proven to be promising in sustainable wave energy conversion areas due to their high efficiency and power density. This study is aimed at developing a constrained maximum power point tracking (MPPT) strategy for MLS-based wave energy converters (WECs). In this paper, the mechanism of the MLS is analyzed and the dynamic model of the MLS-based WEC is established. The variations in hydrodynamic coefficients were analyzed using ANSYS AQWA, based on which the theoretical MPPT requirements were explored. Afterward, two constraints (stroke and translator force constraint) were introduced to ensure the safe operation of the converter. An adaptive constrained genetic algorithm (ACGA) was applied to realize MPPT under constraints. For irregular wave situations, an extended Kalman filter (EKF) was applied to estimate the frequency and amplitude of the wave excitation force with which the constrained GA can be realized. Simulations and experiments were carried out to verify the constrained MPPT. In the two cases (wind speed u = 7 m/s and u = 10 m/s) of the simulation, the proposed ACGA can improve the energy harvest rate by 3.95% and 3.57% compared to the standard constrained genetic algorithm (SCGA), while this rate was improved by 6% in the experimental case. Full article

Wind power systems, which are currently being constructed for the electricity worldwide market, are mostly based on Doubly Fed Induction Generators (DFIGs). To control such systems, multilevel converters are increasingly preferred due to the well-known benefits they provide. This paper deals with the control of a standalone DFIG-based Wind Energy Conversion System (WECS) by using a three-level Neutral-Point-Clamped (NPC) converter. The frequency and magnitude of the stator output voltage of the DFIG are controlled and fixed at nominal values despite the variable rotor speed, ensuring a continuous AC supply for three-phase loads. This task is achieved by controlling the DFIG rotor currents via a PI controller combined with a new Simplified Direct Space Vector Modulation strategy (SDSVM), which is applied to the three-level NPC converter. This strategy is based on the use of a line-to-line three-level converter space vector diagram without using Park transformation and then simplifying it to that of a two-level converter. The performance of the proposed SDSVM technique in terms of controlling the three-level NPC-converter-based standalone WECS is demonstrated through simulation results. The whole WECS control and the SDSVM strategy are implemented on a dSPACE DS 1104 board that drives a DFIG-based wind system test bench. The obtained experimental results confirm the validity and performance in terms of control. Full article

In terms of energy generation and consumption, ships are autonomous isolated systems, with power demands varying according to the type of ship: passenger or commercial. The power supply in modern ships is based on thermal engines-generators, which use fossil fuels, marine diesel oil (MDO) and liquefied natural gas (LNG). The continuous operation of thermal engines on ships during cruises results in increased emissions of polluting gases, mainly CO/CO₂. The combination of renewable energy sources (REs) and triple-fuel diesel engines (TFDEs) can reduce CO/CO₂ emissions, resulting in a “greener” interaction between ships and the ecosystem. This work presents a new control method for balancing the power generation and the load demands of a ship equipped with TFDEs, fuel cells (FCs), and REs, based on a real and accurate model of a super-tanker and simulation of its operation in real cruise conditions. The new TFDE technology engines are capable of using different fuels (marine diesel oil, heavy fuel oil and liquified natural gas), producing the power required for ship operation, as well as using compositions of other fuels based on diesel, aiming to reduce the polluting gases produced. The energy management system (EMS) of a ship is designed and implemented in the structure of a finite state machine (FSM), using the logical design of transitions from state to state. The results demonstrate that further reductions in fossil fuel consumption as well as CO₂ emissions are possible if ship power generation is combined with FC units that consume hydrogen as fuel. The hydrogen is produced locally on the ship through electrolysis using the electric power generated by the on-board renewable energy sources (REs) using photovoltaic systems (PVs) and wind energy conversion turbines (WECs). Full article