Permanent Magnet Synchronous Generator Research Articles

MPPT Optimal Torque Control Strategy for a PMSG-based Wind Turbine Emulator

A wind turbine emulator is a valuable tool, which enables real-time physical simulation of a wind turbine behavior using a dedicated experimental test setup, providing a controlled environment for research and development purposes. One significant advantage of using this tool is its ability to test control algorithms designed to maximize power extraction from the wind turbine. This paper continues previous work on developing a small-scale variable-speed wind turbine emulator based on a Permanent Magnet Synchronous Generator for stand-alone applications (Benhacine et al., 2024). This paper presents enhancements made to the emulator. These improvements facilitate the assessment of a maximum power point tracking control strategy designed to optimize power extraction from the wind turbine.

Application of Artificial Intelligent Techniques for Power Quality Improvement in Microgrid System

This paper focuses on modeling, control and power quality improvement of a microgrid connected system. This last was designed as a multi-converter system with Wind Turbine driven Permanent Magnet Synchronous Generator, and lithium ion Battery Storage Energy System. These sources are connected by a continuous bus to a nonlinear load through a DC /AC converter and three-phases multi-functional voltage source inverter. Where, wind systems are considered as primary power resource, and the grid is used for the effect of consumption of the overage power available from sources, when the battery has been fully charged. Multi Functional Voltage Source Inverter is used to ameliorate the performance of the proposed system, guaranteeing both reactive power and harmonic compensation. Moreover an intelligent control by fuzzy logic control algorithm are managed In order to extract the maximum power from wind turbine, to guarantee an effective storage management, this about the DC side. For the AC side a direct power control strategy with fuzzy logic algorithm have been used. The simulation of the system solution is carried out in Matlab/Simulink. The obtained simulation results show that the technique of fuzzy logic furnish the best solution in term of robustness, optimization performance, low THD and fast dynamic response.

Enhanced MPPT in Permanent Magnet Direct-Drive Wind Power Systems via Improved Sliding Mode Control

Addressing the challenges of significant speed overshoot, stability issues, and system oscillations associated with the sliding mode control (SMC) strategy in maximum power point tracking (MPPT) for permanent magnet synchronous wind power systems, this paper introduces a fuzzy sliding mode control (FSMC) method employing an innovative exponential convergence law. By incorporating a velocity adjustment function into the traditional exponential convergence law, a novel convergence law was designed to mitigate oscillations during the sliding phase and expedite the convergence rate. Additionally, a fuzzy controller was developed to implement a fuzzy adaptive SMC strategy, optimizing the MPPT for permanent magnet synchronous wind power generation systems. Simulation results indicated that this approach offered a faster response and superior interference rejection capabilities, compared to conventional and modified SMC strategies. The improved FSMC strategy demonstrated a swift, dynamic response and excellent steady-state performance, improving the efficiency of MPPT, thus confirming the effectiveness of the proposed method.

Three-Phase Single-Stage AC-DC Converter Using Series–Series Compensation Circuit in Inductive-Power-Transfer-Based Small Wind Power Generation System

In this paper, a three-phase single-stage AC-DC converter for an IPT-based small wind power generation system (WPGS) with an S-S compensation circuit is proposed. It applies a three-phase single-stage AC-DC converter to improve the input power factor (PF), efficiency, and reliability in small WPGSs. Also, inductive power transfer (IPT) was applied to compensate for brush wear in the nacelle of small and medium-sized wind turbines while ensuring electrical safety. In conditions of the three-phase Permanent Magnet Synchronous Generator (PMSG) voltage (80~260 Vrms) for the wind turbine and the load (150~1000 W), it was verified that the desired output voltage below 3% can be controlled through the fixed link voltage (VLink) control without wireless communication. A 1 kW prototype was built and tested to demonstrate its applicability to the rotation of small and medium-sized wind turbine nacelles instead of brushes and slip rings.

Advancing wind energy: adaptive neural network control for optimized permanent magnet synchronous generators

Our contribution in this paper is to design an adaptive neural network (NN) based control of a permanent magnet synchronous generator in order to overcome the effect of structured and unstructured uncertainties and external disturbances, in addition to ensuring the stability of the system, the proposed robust control strategy compensates adaptively for significant uncertainties present in uncertain nonlinear systems. First, we present the vector control of PMSG model applying two tests: with and without constrains, and then, the neural network control with PI controllers. However, conventional controllers suffer from limitations due to the presence of these high uncertainties. Therefore, we aim to improve the efficiency of artificial neural control by using dynamic compensators instead of PI controllers. The estimated states are used as inputs to the neural network (NN). Simulations of the proposed control algorithm are conducted then compared to the previous controllers: vector control and neural network control with PI controllers. Furthermore, using dynamic compensators in artificial neural control achieved both efficiency and optimality. Results have been successfully confirmed via computer simulations using MATLAB.

Evaluation of advanced control strategies for PMSG in wind turbines: backstepping fuzzy logic control and adaptive neural network control approaches

This study presents a comparative analysis of two advanced control strategies for Permanent Magnet Synchronous Generators (PMSGs) in wind turbines: Backstepping Fuzzy Logic Control and Adaptive Neural Network Control. The aim is to evaluate their effectiveness in handling structured and unstructured uncertainties and enhancing system performance. Backstepping Fuzzy Logic Control integrates backstepping techniques with fuzzy logic regulation to improve flexibility and robustness. This method addresses the limitations of traditional PI controllers by enhancing adaptability to parameter variations and external disturbances. In contrast, Adaptive Neural Network Control employs neural networks with dynamic compensators to address high uncertainties and nonlinearities, aiming to surpass the performance of conventional PI controllers. The study involves simulations to compare these control strategies based on several criteria: robustness in managing parameter changes and external disturbances, flexibility in adapting to dynamic conditions, and overall performance including efficiency and stability. Simulation results indicate that both strategies offer significant improvements over traditional PI controllers. Backstepping Fuzzy Logic Control demonstrates strong adaptability and robustness, while Adaptive Neural Network Control shows superior efficiency and optimality, particularly in high-uncertainty environments. This comparative analysis provides insights into the strengths and limitations of each approach, offering guidance for selecting the most suitable control strategy based on specific operational requirements. The findings contribute to advancing control methodologies in wind energy systems and suggest directions for future research and practical implementation.

A hybrid fuzzy logic-based MPPT algorithm for PMSG-based variable speed wind energy conversion system on a smart grid

Recently, wind power has gained popularity as a sustainable energy source. Wind energy conversion systems (WECSs) can accept fixed speed and variable speed (VS) operations. VS-WECSs are preferable to conventional WECSs because of their higher electricity collection capacity. Maximum power point tracking systems (MPPTs) are essential for maximizing the efficiency of wind energy generation in wind turbine installations linked to power grids. This study introduces a hybrid fuzzy logic controller-based MPPT (FLC-MPPT) for wind turbines (WTs) connected to permanent magnet synchronous generators (PMSGs) to accurately determine the maximum power output of WTs. This study employs a three-phase back-to-back converter to link a PMSG to a utility grid. The reference signals for pulse width modulation controllers comprise two-phase system currents. It constructs a converter that can transfer electrical energy in both directions using insulated-gate bipolar transistor technology and is powered by a battery. The machine-side converter uses model predictive control for the present control loop. Given the generator's susceptibility to changes in wind conditions, this factor is of the utmost importance. A WT simulation was conducted using MATLAB/Simulink and an FLC methodology was employed. The model used a PMSG. Measurements of rotor speed, power, induced voltage, and current were taken in relation to variations in wind speed. The simulation results show that the FLC-MPPT can maximize the output power over a wide range of wind speeds with a higher efficiency of 92.6% and performance of 95.7%.

Parameter Identification of PMSG-Based Wind Turbine Based on Sensitivity Analysis and Improved Gray Wolf Optimization

With the large-scale integration of wind power, it is essential to establish an electromagnetic transient (EMT) model of a wind turbine system. Focusing on the problem of the difficulty in obtaining the parameters of the direct-driven permanent magnet synchronous generator (PMSG) model, this manuscript proposes a method based on trajectory sensitivity analysis and improved gray wolf optimization (IGWO) for identifying the parameters of the PMSG EMT model. First, a model of a PMSG wind turbine is established on an EMT simulation platform. Then, the key parameters of the model are determined based on the sensitivity analysis. Five control parameters are selected as the key parameters for their higher sensitivity indexes. Finally, the key parameters are accurately identified, using the proposed IGWO algorithm. The final case study demonstrates that the proposed IGWO algorithm has better optimization performance compared with the GWO algorithm and particle swarm optimization (PSO) algorithm. In addition, the simulation waveforms show that the identified parameters are accurate and applicable to other operating conditions.

Data-driven control of wind turbine under online power strategy via deep learning and reinforcement learning

This study proposes a data-driven wind turbine (WT) model predictive control (MPC) enhanced by a deep-learning (DL) radial basis function network (RBFN) and a reinforcement-learning (RL) deep Q-learning network (DQN). The RBFN provides comprehensive aerodynamic predictions, including thrust, torque, and power. Besides, the MPC linearization relies on the RBFN prediction to estimate force sensitivities. The DQN achieves an online power strategy (OPS) that solves the 2-degree-of-freedom (2-DOF) optimization of rotor speed and pitch angle, which can actively adjust power capture to meet different power requirements. The DQN adopts a novel bisection algorithm with a first-in-first-out (FIFO) queue for high-precision 2-DOF results. The MPC coordinates the permanent magnet synchronous generator (PMSG) and pitch servo, considering shaft rotation and tower movement. Compared with the maximum power point tracking (MPPT) and power reference point tracking (PRPT) based controls, the proposed RBFN-DQN-MPC reduces power fluctuation and ensures constant output. This study also compares the DQN with the categorical DQN (C51), which indicates that the DQN is more effective in the 2-DOF optimization. Hence, WTs enhanced by the DL-RL-MPC are intelligent and reliable for flexible wind generation.

Nonlinear Enhanced Control for Wind Energy Generation System-Based Permanent Magnet Synchronous Generator

This paper proposes a Nonlinear Backstepping Approach (NBA) to improve the control performance of a Permanent Magnet Synchronous Generator (PMSG)-based Wind Energy Generation System (WEGS) under parameter uncertainties and short circuits with fluctuations in the grid voltage. Both the rectifier and the three-phase inverter are controlled using the NBA scheme; this method ensures Maximum Power Point Tracking (MPPT), which is a very appealing control objective with unpredictable scenarios of wind speed, and regulates the active and reactive power flows to the electrical network under varying wind speeds. Also, an inverter was employed to control voltage of the DC bus and the powers. The regulator’s stability is achieving using the Lyapunov approach. Simulation results with Matlab/Simulink confirm the efficiency of the presented scheme. The comparative analysis of the NBA with conventional Vector Controllers (VCs), under parameter deviations and for low voltage drop conditions, demonstrates the efficiency of the studied method.

Investigation on Overvoltage Distribution in Stator Windings of Permanent Magnet Synchronous Wind Turbines

The PWM voltage pulses output by the inverter reaches the stator winding of the wind turbine generator through the cable. Due to the impedance mismatch between the motor and the cable, the voltage at the motor end rises under the action of the circuit wave process; on the other hand, electromagnetic oscillation occurs within the motor winding. Higher overvoltage is generated under the combined effect of both, which greatly accelerates the aging and breakdown of the insulation layer of the permanent magnet synchronous wind turbine. In this paper, a three-dimensional electromagnetic model of the permanent magnet synchronous wind turbine generator is established. The distribution circuit parameters of the stator winding of the permanent magnet machine are calculated using the finite element method, and its circuit model is based. The voltage distribution of the stator winding under different PWM excitations is investigated by simulation software, and the effects of the time of the rising edge and the pulse width of the PWM pulse on the stator winding voltage to ground and the turn-to-turn voltage distribution are studied. The results show that the effect of the rising edge time is larger when the rising edge time is shorter, the maximum voltage to ground occurs in the first coil, and the amplitude can be up to 1.5 times of the output voltage. When the rising edge time is longer, the maximum voltage to ground occurs in the end coil, and the amplitude is slightly higher than the output voltage. The trend of turn-to-turn voltage variation is similar for different rising edges; only the maximum turn-to-turn voltage amplitude is different. Pulse width has a small effect on overvoltage and only occurs when the pulse width is less than 10 μs. The research results of this paper are of great significance in revealing the aging and breakdown mechanism of the generator stator insulation, as well as the insulation coordination and design.

Analysis of an anaerobically digested animal waste-based microturbine driven-biogas energy system

The paper designs a biogas power plant that runs on anaerobically digested (AD) animal waste and integrated with a micro turbine and permanent magnet synchronous generator to generate renewable power. Cow dung, poultry manure, and swine have been explored as potential feedstocks for AD, and the various subprocesses are investigated at discrete temperature intervals that cover both the mesophilic and thermophilic temperature ranges (30 °C–50 °C). The biodegradability of animal wastes, retention time, loading rate, and the size of the reactor influence the overall biogas yield. Methane production from cow dung increased from 131.4 L/d at 30 °C to 171.12 L/d at 50 °C in 15 days. Whereas the methane output from poultry manure, and swine at 50 °C were 278.4 L/d and 284.5 L/d respectively. Moreover, a methane recovery efficiency of 75 % and a purge efficiency of 97 % were attained through pressure swing adsorption (PSA). Furthermore, the system is maintained at 25 kW at steady-state conditions, attaining saturation for a torque value of 7.77 p.u. In a dynamic setting, the load is varied for a range of 25 kW–40 kW, and stable sinusoidal waveforms are generated as outputs that indicate the system's ability to withstand load variations.

Simulating the Operation Modes of a Wind Farm with a Three-Phase Permanent-Magnet Synchronous Generator

Simulating the Operation Modes of a Wind Farm with a Three-Phase Permanent-Magnet Synchronous Generator

Advanced nonlinear control of WEC system in AC microgrid connected to the main grid with electric vehicle integration

This research investigates an AC microgrid interconnected with the utility grid, comprising a 5.2 kW wind power system using a Permanent Magnet Synchronous Generator (PMSG), a 6.1 kW photovoltaic system (PVS), and integrated electric vehicles (EVs) with 600 V, 10Ah batteries operating in V2G and G2V modes. Bidirectional back-to-back converters, controlled via a voltage-oriented control (VOC) strategy, facilitate the interconnections. The PMSG system is controlled using vector control methodology, while the PVS employs a double-stage configuration with a perturb and observe algorithm for maximum power point tracking (MPPT). Advanced controllers based on Active Disturbance Rejection Control (ADRC) regulate generator speed and the DC link voltage of the grid-connected converters. The backstepping technique is utilized for internal loop control of PMSG currents and coupling filter currents for the grid-connected converters. A comparative study between the ADRC-Backstepping controller and the PI controller was conducted, demonstrating the superior efficacy of the ADRC-Backstepping approach. Simulation results show accurate regulation of DC link voltage at reference levels, operation with unit power factor, with a current THD below 4 %, demonstrating the effectiveness and robustness of the proposed control strategies under varying conditions.

PMSG-based wind farm high-voltage ride-through improvement for single-pole tripping of circuit breakers

For transient single phase-to-ground (SPG) faults in transmission lines, single-pole circuit breaker (SPCB) operation can improve system reliability. This issue is more critical in transmission lines emanating from wind farms (WFs). In the large-scale WFs, the grid codes necessitate that wind generation remains in operation during the transmission line faults. For this purpose, the grid codes focus on the development of fault-ride-through (FRT) requirements. In this paper, it is shown that after the SPCB operation, the terminal voltage of the permanent magnet synchronous generator (PMSG)-based wind turbine (WT) rapidly increases and may cross the high-voltage ride-through (HVRT) boundary. Therefore, the WT terminal overvoltage after the SPCB operation may result in undesirable tripping of the WT. The obtained results in this paper show that in most cases both the coupled and decoupled sequence controllers of the WT converter equipped with the FRT requirements are not able to improve the HVRT performance after the SPCB operation. To enhance the HVRT performance of PMSG-based wind turbines after the SPCB operation, a dc-link chopper controller is proposed. EMTP-RV simulation results on the IEEE 118-bus and 5-bus systems show the success and effectiveness of the proposed method.

MPPT algorithm based on metaheuristic techniques (PSO & GA) dedicated to improve wind energy water pumping system performance

This paper presents a comparative study between four techniques recently used to improve the wind energy conversion system (WECS) to water pumping systems. The WECS is a renewable energy source which has developed rapidly in recent years. The use of the WECS in the water pumping field is a free solution (economically) compared to the use of the electricity grid supply. The control of WECS, equipped with a permanent magnet synchronous generator, has the objective of carefully maximising power generation. A comparative study between the proposed Fuzzy Logic Control, optimised using a genetic algorithm and particle swarm optimisation algorithm, and the conventional Perturb and Observe MPPT method using Matlab/Simulink, is presented. The performance of the proposed system has been verified against the generated output voltage, current and power waveforms, intermediate circuit voltage waveform, and generator speed. The presented results demonstrate the effectiveness of the control strategy applied in this work.

The Stabilization of a Nonlinear Permanent-Magnet- Synchronous-Generator-Based Wind Energy Conversion System via Coupling-Memory-Sampled Data Control with a Membership-Function-Dependent H∞ Approach

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∞ performance index is presented, mitigating the continuous-time fuzzy system’s disturbances. Then, by using the Lyapunov–Krasovskii functional with the MFD H∞ 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.

Switched sampled-data-based membership function-dependent [formula omitted] control for PMSG-based WTS with actuator failures

This paper deals with the problem of sampled-data-based H∞ control design for nonlinear permanent magnet synchronous generator (PMSG)-based wind turbine system (WTS) subject to actuator failures. First, the Takagi-Sugeno (T-S) fuzzy system is employed to handle the nonlinearities of presented model. Next, by employing a Bernoulli stochastic variable, the general scenario of switched coupling memory sampled-data control (CMSDC) is designed which contains the sampled-data control (SDC) and memory SDC scheme as special cases. By combining the membership function-dependent (MFD) asymmetric looped-type Lyapunov-Krasovskii functional (LKF) and employing the available information of membership functions in H∞ performance, the delay-dependent stabilization conditions of considered PMSG-based WTS are derived through the switched CMSDC technique. Meanwhile, the disturbances of considered systems are attenuated by taking the advantage of the newly proposed MFD H∞ performance. Eventually, the simulation results are given to demonstrate the efficacy and applicability of the proposed CMSDC technique.

Optimum design of a coaxial magnetic gear integrated with a permanent magnet synchronous generator of a wind turbine based on the pelican optimization algorithm

This paper presents an optimum design of a coaxial magnetic gear (CMG) Integrated with a Permanent Magnet Synchronous Generator (PMSG) of a wind turbine using a pelican optimization algorithm (POA) launched in 2022. In order to evaluate the proposed system design based on POA, the well-known Particle Swarm Optimization (PSO) is implemented for the same CMG under the same conditions and constraints. Also, a Taguchi-method-based sensitivity analysis for the key design variables is employed to determine their impact on the system’s performance. The optimization process for the CMG design based on POA and PSO is executed based on the 2-D Finite element analysis (FEA) using the Finite Element Method Magnetics (FEMM) program. The results obtained from the POA and PSO are compared and analyzed. The results underline that the optimum design for the CMG/PMSG integrated system based on POA achieves more torque/weight ratio and then more generated power and currents as compared to PSO. It is concluded that the proposed design based on POA gives a superior and efficient design with substantial stability and rapid convergence.

Impact of translator mass and buoy choice on a power absorption of point absorbing wave energy converter linear generator with linear generator power take off

AbstractOcean waves have the potential to contribute to future renewable electricity production. A wave energy converter (WEC) is a technology developed to absorb the energy of the wave and convert it to another form of energy. The Uppsala University WEC (UU WEC) is a point absorber with a direct drive permanent magnet synchronous linear generator power take off. Among other parameters affecting the value of absorbed power for UU WEC are the buoy size, mass of the system consisting of the buoy and translator, and available wave energy at the site of interest. This study reviews the earlier static model that considered only static forces as the buoyancy and gravity forces and neglected all dynamic forces. The static model was proposed to simplify the early‐stage design decision. Although the static model was applied to two UU WECs of different dimensions, the present study shows that the static model is not held for certain buoy and translator dimensions. As an alternative, the dynamic model which accounts for the impact of hydrodynamic forces and various translator masses is proposed. The dynamic model is based on Cummins' equation and the linear potential flow theory, and the damping force is approximated as a viscous damper with the constant damping coefficient optimizing the absorbed mechanical power under a particular sea condition. The dynamic model is applied to four fixed buoy geometries of two shapes (cylinder and cylinder with a moonpool), each of two different dimensions, but the method can be extended to other buoy shapes and dimensions. In addition, the impact of translator mass was assessed for two sites located on the west coast of Sweden and near Gran Canaria, Spain. A translator of 10–11 t promotes 16.8% higher annual average power absorption for a cylindrical buoy compared to a translator of 6 t for the same buoy. However, heavier translators up to 15 t provide only 1.1% increase in average annual absorbed power.