Permanent Magnet Synchronous Generator Research Articles

Maximum power optimization of a direct-drive wind turbine connected to PMSG using multi-objective genetic algorithm

This work aimed to develop and evaluate a maximum power point tracking (MPPT) control system for a wind energy conversion system (WECS) based on a permanent magnet synchronous generator (PMSG). PMSG is commonly used to generate direct-drive and variable-speed wind energy. Initially, the generator and converter on the DC load side are controlled to follow the wind speed reference set by the MPPT algorithm. The paper presents the optimization problem formulation, including the optimization space, constraints, and objectives. The genetic algorithm (GA) is used to extract the maximum power from the WECS in this design improvement. In this study, to control and stabilize the maximum power point (MPP) of the wind turbine, a proportional integral (PI) controller and a GA heuristic approach were utilized. The GA approach was employed to determine the best settings (Kp, Ki) using MATLAB/Simulink with a 12.3 kW PMSG to model and simulate the proposed system. Based on four performance indicators-integrated squared error (ISE), integrated absolute error (IAE), integrated time absolute error (ITAE), and integrated time squared error (ITSE), the GA approach was used to optimize the controller settings. The results of the simulation show that the wind turbine (WT) can effectively track the necessary MPP. The simulation's output also includes generated power, DC bus voltage, electromagnetic torque, and currents.

Decentralized Sampled-Data Control for Stochastic Disturbance in Interconnected Power Systems With PMSG-Based Wind Turbines.

The presented work is concerned with the stability performance of frequency response for interconnected power systems (IPSs) with permanent magnet synchronous generator (PMSG)-based wind turbines (WTs) via a decentralized control scheme against external and stochastic disturbances. To do this, initially, the state-space model is derived when a PMSG is penetration into IPSs. Differing from existing works, IPSs with PMSG-based WTs, including the stochastic disturbance, are modeled as a stochastic state-space model. Then, decentralized sampled-data load frequency control is designed to regulate the frequency response of the proposed model against the deterministic and stochastic noises. By constructing bilateral looped Lyapunov functional and using Itôs formula, stochastic sufficient conditions are derived, which ensure that the closed-loop form of the proposed model is asymptotically stable in the mean square with H∞ performance index γ . Finally, three-area IPSs with PMSG-based WTs are validated with derived sufficient conditions. The simulation results confirmed the better-stability performance of frequency response for the proposed stochastic IPSs with PMSG-based WTs.

A Proposed Hybrid Machine Learning Model Based on Feature Selection Technique for Tidal Power Forecasting and Its Integration

Renewable energy resources are playing a crucial role in minimizing fossil fuel emissions. Integrating machine learning techniques with tidal power forecasting could greatly enhance the accuracy and reliability of predictions, which is crucial for efficient energy production and management. A hybrid approach combining different methods often yields better results than relying on individual techniques. The accuracy of tidal current power is very important, especially for smart grid applications. This work proposes hybrid adaptive neuro-fuzzy inference system (ANFIS) with the Kalman filter (KF) and a neuro-wavelet (WNN) for tidal current speed, direction, and power forecasting. The turbine used in this study is driven by a direct drive permanent magnet synchronous generator (DDPMSG). The predictions of individual and hybrid models including the ANFIS, the Kalman filter, and the WNN for tidal current speed and the power it generates are compared with another dataset as a way of validation which is the tidal currents direction. Also, other published work results in the literature are compared to the proposed work. Different hybrid models are proposed for smart grid integration. The results of this work indicate that the hybrid model of the WNN and the ANFIS for tidal current power or speed forecasting has the highest performance compared to all other models.

Using a Stand-Alone Wind Energy Conversion System as a Sustainable Technology to Produce Electricity in Iraq

This work looks into Iraq's best places for wind turbines, with an emphasis on economic factors. It studies wind energy conversion systems using mathematical models from Matlab and Simulink. This research aims to pinpoint areas where wind energy can produce power on its own, separate from the national grid, for a range of applications, including energy storage, water pumps, heating, and cooling. In addition, the project will use PMSG to investigate wind turbine efficiency and create vector control technique technology for permanent magnet synchronous generators. Two Iraqi cities were taken to make the calculations of wind speed and its effect on electrical generations (Nasiriyah and Basra), where wind speeds of a height of 20 and 50 m were taken at the hub level of the turbine. The mechanical, electrical, and performance characteristics of the turbine were computed during the test to achieve optimal operation cases. The development of the system was done by MATLAB SIMULINK, where the overall efficiency was enhanced to 88.22%.

Control for Wind Turbine System using PMSG when Wind Speed Changes

This paper presents the proposed model to control grid-connected wind turbine by permanent magnet synchronous generator (PMSG). With the wind speed changing continuously, the rotor system needs to be able to self-regulate according to wind speed and direction to ensure efficient operation of the turbine. The PMSG was chosen because the magnetic flux is always available thanks to the permanent magnet system glued to the rotor surface. The generator provides power with low rotational speed but high efficiency. These are the important advantages of using PMSG for wind turbine. Matlab - Simulink software was used to design the controllers and the survey results proved that this control system meets the power quality requirements when connecting to the grid and optimizing the energy conversion process for turbine wind.

Aggregation Equivalence Method for Direct-Drive Wind Farms Based on the Excitation–Response Relationship

The grid interconnections for direct-drive wind farms have triggered multiple new sub-synchronous oscillation events, which can prevent the power system from operating safely and stably. However, the excessively high order of the detailed model for large-scale wind farms with multiple direct-drive permanent magnet synchronous generators (PMSGs) connected to power systems poses a challenge when investigating small disturbance stability and instability mechanisms. This study establishes a model of the grid-connected PMSG system based on the voltage/power excitation–response relationship to describe the dynamic characteristics of the port of the PMSG, and the analysis of active and reactive response characteristics of PMSG lays the foundation for model simplification. Based on the unit model, a direct-drive wind farm aggregation equivalence method based on the excitation–response relationship is proposed. The equivalent model obtained by this method is suitable for the small disturbance stability analysis of direct-drive wind farms grid connected system, with good accuracy. The simulation verified the effectiveness of the aggregation model.

Observer-based fuzzy control for fractional order PMSG wind turbine systems with adaptive quantized-mechanism

This study aims to present an observer-based fuzzy control approach for a wind turbine system (WTS) equipped with a fractional-order permanent magnet synchronous generator (PMSG) by utilizing an adaptive quantized-mechanism. To do this, firstly, the fractional order control is introduced into the nonlinear PMSG model to improve the convergence rate beyond the existing integer order control techniques. In the next step, the nonlinear PMSG model is converted into linear sub-models using Takagi–Sugeno (T–S) fuzzy models. Using a fractional order Lyapunov function, an adaptive quantization mechanism, and a linear matrix inequality (LMI), we then obtain the necessary conditions for global stabilization of the PMSG-based WTS. Finally, the method proposed in this study demonstrates its superiority and efficiency through comparison with existing methods.

Design of 20 MW direct‐drive permanent magnet synchronous generators for wind turbines based on constrained many‐objective optimization

AbstractThis study introduces a constrained many‐objective optimization approach for the optimal design of 20 MW direct drive (DD) permanent magnet synchronous generators (PMSGs). Designing a high‐performance, competitive DD‐PMSG requires considering the generator's performance as well as its weight and material cost. Therefore, we focus on four main characteristics as our design objectives: (1) specific power (power per weight), (2) power‐per‐cost, (3) efficiency, and (4) power factor. To achieve this, we apply an advanced constrained nondominated sorting genetic algorithm III (NSGA‐III), a many‐objective optimization method utilizing evolutionary computation, capable of optimizing four or more objectives with constraints. Additionally, the electromagnetic finite element method is employed to evaluate the generator's characteristics. Through our proposed design process, we optimize three distinct 20 MW DD‐PMSG configurations: a 320‐pole/300‐slot, a 350‐pole/300‐slot, and a 350‐pole/336‐slot topology. Following this optimization, we perform additional multiphysics simulations (covering electromagnetic, structural, overload, and thermal aspects) and control response simulations on four selected models from the Pareto‐optimal solutions to validate their effectiveness as preliminary DD‐PMSG designs. Finally, we conduct a comprehensive analysis of all simulation results.

Low voltage ride through enhancement of a permanent magnet synchronous generator based wind energy conversion system in an islanded microgrid: A dynamic matrix controlled virtual DC machine

In an isolated microgrid, the wind energy conversion system based on direct-drive permanent magnet synchronous generator may experience fluctuations in the DC bus voltage due to wind variations and grid voltage drop, thereby compromising system reliability. To address this issue, the scheme of the supercapacitor energy storage system is proposed. The existing double closed-loop PID control, which cannot provide inertia support, has shortcomings such as difficult parameter setting and slow dynamic response. To solve this problem, the dynamic-matrix-control based predictive control for a virtual DC machine method is proposed. Firstly, the concept of virtual DC machine control is firstly introduced in supercapacitor energy storage system. Secondly, according to the unit step response of virtual DC machine, the prediction model of virtual DC machine is established. Finally, the desired torque increment reference of virtual DC machine is calculated by the dynamic-matrix-control controller to change the input torque reference. Hardware-in-the-loop experiment verifies the effectiveness of the proposed method: Compared with traditional double closed-loop PID control, the maximum voltage fluctuation is reduced by 67.9 % under random wind fluctuation and the inhibition effect on DC voltage surge and plunge when fault occurs in the power grid is increased by 61.4 % and 57.9 %.© 2017 Elsevier Inc. All rights reserved.

Selecting the Best Permanent Magnet Synchronous Machine Design for Use in a Small Wind Turbine

The article describes the selection of a permanent magnet synchronous machine design that could be implemented in a small wind turbine designed by the GUST student organization together with researchers working at the Technical University of Lodz. Based on measurements of the characteristics of available machines, eight initial designs of machines with different rotor designs were proposed. The size of the stator, the number of pairs of poles, and the dimensions of the magnets were used as initial parameters of the designed machines. The analysis was carried out about the K-index, the so-called index of benefits. The idea was to make the selected design as efficient as possible while keeping production costs and manufacturing time low. This paper describes how to select the best design of a permanent magnet synchronous generator intended to work with a small wind turbine. All generator parameters were selected keeping in mind the competition requirements, as the designed generator will be used in the author’s wind turbine. Based on the determined characteristics of the generator variants and the value of the K-index, a generator with a latent magnet rotor was selected as the best solution. The aforementioned K-index is a proprietary concept developed for the selection of the most suitable generator design. This paper did not use optimization methods; the analysis was only supported by the K-index.

Stability Analysis via Impedance Modelling of a Real-World Wind Generation System with AC Collector and LCC-Based HVDC Transmission Grid

Stability Analysis via Impedance Modelling of a Real-World Wind Generation System with AC Collector and LCC-Based HVDC Transmission Grid

Study and Analysis of RBFN based MPPT controller for wind energy integrated with Traction Power Supply System

The need of energy for railway is rising due to the increased speed at which trains must operate to maintain safety and dependability. This situation implies more electricity consumption and more challenges to railway operation stability. Therefore, this research suggests configuring wind energy integration with the current railway traction substations built on the current traction substation. The suggested setup consists of a converter that converts DC to DC with RBFN-based MPPT regulator wind energy source linked to a permanent magnet synchronous generator (PMSG), a rectifier, and a conventional traction system. The proposed system is modelled and analyzed by utilizing a radial basis function network (RBFN) in this study. Three traction substations: Aysha, Adegla and Dewanle:-are the subject of the case study, which integrates wind energy with the railway electric power system working at 25 kV AC. For the Aysha wind farm, a MATLAB/Simulink simulation is run in order to confirm the suggested technology. The setup with or without MPPT was used in order to evaluate the results. The proposed system produces an average output of 260.3kW without MPPT and 289.3kW with MPPT controller at wind speed of 20m/sec. The simulation findings suggest that the RBFN-based control method performs better under diverse wind conditions and is more suited for wind energy integration with traction system.

A modular IGBT power stack − based and open hardware framework for small wind turbines assessment

Wind energy technologies have emerged as the predominant renewable energy source within the framework of present-day electric power systems. Their design process, aligned with foundational theories, ought to be precision-engineered and systematized to fully maximize the potential of this energy source. This study presents a platform as solution designed and built to characterize and assess Small Wind Turbines (SWT), based on free software and open hardware. Additionally, the developed methodology step-by-step guide is disclosed. The characterization is based on the use of Permanent-Magnet Synchronous Generator (PMSG) as machine widely adopted in Wind Energy Conversion System (WECS) less than 100 kW. The core theoretical background is detailed to confirm the accuracy of the parameters procedures acquisitions. Poles number, machine design constant, armature reactance, synchronous reactance, and power-dynamic characteristic related to WECS are determined. This laboratory set-up is composed of variable industrial fan, rectifier, boost converter and a bidirectional Direct-Current (DC) source as a battery emulator. All components have been assembled within the laboratory environment using commercially available elements. Low implementation cost and versatile methods determine the real input in practice of this platform. To validate the effectiveness for any SWT, a real one is tested, and every parameter proposed is calculated.

A chaos game optimization algorithm-based optimal control strategy for performance enhancement of offshore wind farms

This paper presents a novel application of the chaos game optimization (CGO) algorithm to optimally design PI controllers for power electronic interface circuits of offshore wind farms (OWF) consisting of a permanent magnet synchronous generator powered by a variable-speed wind turbine. The OWF is linked to the network via a high-voltage direct current (HVDC) transmission system. The CGO metaheuristic method is employed to fine-tune voltage source converter (VSC)-based HVDC transmission systems’ proportional-integral controller gains. The study explores multiple strategies to extract the highest power from the system while ensuring stability under symmetrical and unsymmetrical fault conditions. The CGO algorithm consistently yields superior results to other algorithms, improving system regaining and stability post disturbances. Consequently, the technique enhances the dynamic and transient stability of the OWF. The detailed study is implemented using MATLAB/Simulink.

Adaptive neuro fuzzy technology to enhance PID performances within VCA for grid-connected wind system under nonlinear behaviors: FPGA hardware implementation

Wind Energy Conversion Systems (WECSs) exhibit nonlinear behavior due to internal and external disturbances, which can significantly impact the control performance. Firstly, this paper proposes a Vector Control Approach (VCA) based on Adaptive Neuro Fuzzy (ANF) of Proportional Integral Derivative (PID) controllers for a variable speed Permanent Magnet Synchronous Generator (PMSG)-based WECS connected to the grid to address these issues. The proposed ANF-PID controller combines the robustness of the fuzzy logic with the neural network's performance to ensure high accuracy, excellent tracking, and robustness against the WECS's nonlinear behavior. The neural network automates the placement of fuzzy logic membership functions. Secondly, this paper suggests a real-time hardware implementation of the VCA based on ANF-PID using a Field Programmable Gate Array (FPGA) to reduce the processing time and the WECS's sampling period. The effectiveness of the VCA based on ANF-PID controllers is validated by conducting a numerical simulation within the Matlab-Simulink using the Xilinx System Generator tool, alongside an experimental in-the-loop hardware implementation using FPGA board. Different scenarios are conducted to validate the robustness and stability of the proposed VCA based on ANF-PID control schemes, which is compared to Conventional Fuzzy PID (C-FPID) and PID controllers. The results exhibit that the VCA based on ANF-PID controllers outperforms VCA-C-FPID and VCA-PID controllers in terms of precision, tracking accuracy, and robustness against the WECS's nonlinear behavior and the PMSG parameter variations. The performances of the proposed controllers are tested under some criteria. In fact, the proposed ANF-PID controller provides a Mean Absolute Error (MAE), a Mean Squared Error (MSE) and a Root Mean Squared Error (RMSE) of 8.1911 × 10−04, 8.4181 × 10−05 and 0.0092, respectively. Compared to the C-FPID controller, the proposed controller offers an improvement gain of 98.96 %, 99.61 %, and 93.79 % of MAE, MSE, and RMSE, respectively. When compared to the PID controller, its improvement is even more significant, with a reduction of 99.9919 %, 99.9999 %, and 99.9288 % of MAE, MSE, and RMSE, respectively. In addition, the ANF-PID-based VCA utilizes hardware resources on the FPGA efficiently, requiring only 65.60 % slices LUT, 0.28 % LUTRAM, and 22.99 % FF. This makes it a more cost-effective option compared to the VCA-C-FPID controller for diverse control systems.

Developing onshore wind farms in Aotearoa New Zealand: carbon and energy footprints

ABSTRACT In recognition of deeper insights into the implications of wind farm deployments, this paper addresses the need for an updated Life Cycle Assessment (LCA) for onshore wind generation systems, using 4.3 MW wind turbines and direct drive permanent magnet synchronous generators. The environmental and energy performances were estimated through an LCA for an onshore wind plant under construction in Aotearoa New Zealand with a total nameplate capacity of 176 MW. This study used real construction data showing literature data overestimates civil works and underestimates transportation contributions in the wind farm footprint. Further, different end-of-life management alternatives for turbine blades are analysed: landfill, mechanical recycling, and chemical recycling. The results indicate a carbon footprint of 10.8–9.7 gCO2eq/kWh, a greenhouse gas payback time of 1.5–1.7 years for avoided combined cycle gas turbines, and an energy payback time of 0.4–0.5 years, in which the chemical recycling of the blades is the lower emission solution overall. The outcomes underscore the environmental efficiency of onshore wind farms and their important role in the energy transition. Notably, the manufacturing of wind turbines is the primary contributor to the carbon and energy footprints, highlighting a critical area for targeted environmental mitigation strategies.

Active-Control-Based Three-Phase Reclosing Scheme for Single Transmission Line With PMSGs

Electric devices may be damaged due to the strong secondary impact when the circuit breaker recloses on permanent faults, so it is significant to identify the fault nature to reduce the harm of grid faults. To achieve this point, a new control scheme is designed to make permanent magnet synchronous generator (PMSG) based wind turbines behave as a three-phase symmetrical voltage source, so the overcurrent can be detected for permanent faults when the circuit breaker on the PMSG side is reclosed, but only the tiny capacitance current is present for temporary faults. Therefore, the fault nature can be identified by detecting the current amplitude. To accurately extract the power-frequency phasors, a fast matrix pencil extraction method is adopted. This method solves the difficulty in fault nature detection caused by the rapid disappearance of current and voltage after a three-phase trip using the controllability of power electronics. Meanwhile, the severe secondary impact can be reduced since the injected current is small even for permanent faults. Additionally, the proposed method can ensure the fault current at the inverter terminal is within the limiting value and operate properly for remote high-resistance faults. Extensive simulations and experiments are performed to verify this method.

A Novel Adaptive Third-Order Continuous Super-Twisting Controller of a Five Phase Permanent Magnet Synchronous Wind Generator

The aim of this research is to enhance the control of a Wind Energy Generating System (WEGS) incorporating a Five-phase Permanent Magnet Synchronous Generator (5 ph-PMSG) and addressing operational challenges in the presence of disturbances. The commonly employed Second-Order Super-Twisting Controller (SOSTC), with constant gains, has limitations, including uncertainties, significant transient state errors, and chattering effects, hindering its practical applicability. To overcome these drawbacks, the study proposes the application of an Adaptive Third-Order Continuous Super-Twisting Control (ATOCSTC). This novel approach integrates a third-order sliding mode surface, a smoothly continuous switching control term, and an adaptation law. Unlike the conventional SOSTC using discontinuous “sign” functions, ATOCSTC dynamically adjusts gains using tangent hyperbolic functions, providing a continuous and effective control mechanism. Comparative analysis with the conventional SOSTC under various disturbances such as wind speed fluctuations, parameter variations, and Grid Voltage Sag (GVS), reveals significant improvements with ATOCSTC. Notably, ATOCSTC leads to a 75% reduction in power ripples for grid active power and a 40.38% reduction for grid reactive power. These findings underscore the superior performances obtained with the proposed ATOCSTC in WEGS.

Backstepping Control of an AC/DC/AC Converter in a Grid Connected Wind Power System

The contribution of this paper is to study a nonlinear control approach known as the backstepping control method to manage reactive and active power using new parametric values for the grid connected wind power generation system. Specifically, the research focuses on a system containing a wind turbine system, a permanent magnet synchronous generator (PMSG), and a grid connected via AC/DC/AC converter. A comprehensive mathematical model for both the wind turbine system, PMSG, and the grid connected via AC/DC/AC converter was developed for this purpose. The Simulation results of the grid-connected wind power generation system are presented and analyzed to show the performance of the nonlinear backstepping control method. The characteristics of the response to variations in generator speed and the power injected into the grid show the highlight of the performance of the backstepping method, under varying wind conditions.

Grid-Impedance-Based Transient Current Control for Offshore Wind Turbines under Low-Voltage Fault

In order to enhance the transient stability of offshore wind turbines (OWTs) in marine energy systems, the grid codes stipulate that OWTs should possess the low-voltage ride-through (LVRT) ability of being grid-tied and injecting reactive current during grid fault. However, the grid-side converter (GSC) of OWTs may lose stability under weak grid or severe fault conditions due to inaccurate current references. To address this issue, a novel transient current control method is proposed to improve the transient stability of permanent-magnet-synchronous-generator (PMSG)-based OWTs. The feature of DC-link overvoltage is investigated and is alleviated by utilizing the GSC’s overcurrent capacity and chopper. Additionally, the equivalent circuit of the PMSG-based OWT connected to the onshore grid is derived based on Thevenin’s theorem. The feasible current region (FCR) is then determined, taking into account the GSC capacity, pre-fault power ability, LVRT requirement, and synchronization stability. Furthermore, a grid-impedance-based transient current control method is designed to enhance the fault ride-through performance and mitigate power oscillation of the OWT under various transient grid impedance and fault conditions. Finally, a simulation model is conducted using PSCAD v4.6.3 software to validate the effectiveness of the proposed method.