Grid-connected Wind Turbine Research Articles

Comparative analysis of PI and fuzzy logic controller for grid connected wind turbine under normal and fault conditions

This research is dedicated to improving the control system of wind turbines (WT) to ensure optimal efficiency and rapid responsiveness. To achieve this, the fuzzy logic control (FLC) method is implemented to control the converter in the rotor side (RSC) of a doubly fed induction generator (DFIG) and its performance is compared with an optimized proportional integral (PI) controller. The study demonstrated an enhancement in the performance of the DFIG through the utilization of the proposed FLC, effectively overcoming limitations and deficiencies observed in the conventional controllers, this approach significantly improved the performance of the wind turbine. Additionally, the selected membership functions were found to be highly compatible with the unique characteristics of wind energy. The optimization process is implemented for the controllers of both the grid side converter (GSC) and RSC. Through simulated analyses conducted using MATLAB/Simulink software, comprehensive assessments are carried out. The robustness of the FLC is evaluated compared to the optimized controllers across various wind profiles and challenging fault conditions. The results demonstrate satisfactory performance of the FLC in terms of steady-state time, stability, and precision under diverse wind speed profiles. The FLC achieves a significantly better settling time than the enhanced PI, improving by approximately 14–70% under normal conditions and 40–70% under various fault conditions. Additionally, the FLC outperforms the enhanced PI in fault conditions by reducing peak-to-peak oscillations by about 30–65%. It also delivers a smaller steady-state error, with improvements of around 2–4% under both normal conditions and most fault scenarios.

Power Quality Management Using FACTS Device for Grid-Connected PV Solar and Wind Turbine Systems

Power Quality Management Using FACTS Device for Grid-Connected PV Solar and Wind Turbine Systems

Experimental Investigation and Validation of Measured Wind Turbine Noise Characteristics using Standardized Technology

This paper aims in affirming the accuracy and consistency of acoustic noise assessment at an experimental and Grid Connected wind turbine. The experimental turbine is a three-bladed, upwind turbine located in the Tuticorin District of Tamil Nadu State in India. The measurement campaign was carried out during the noise measurement equipment by Brüel & Kjær (B&K) PULSE Wind Turbine Sound Power Determination system strictly in accordance with the IEC 61400-11 2012-11 AMDI 2018 Ed.3.1. The Experimental study deals in the measurement of total noise emitted from various wind turbine component and sub-systems, when the turbine is in ON condition. The background noise was obtained while the turbine is in OFF condition. The measurement data was obtained as per the above referred standards for wind speeds ranging from 7m/s to 13.5 m/s at 50m hub height. The measurement was also obtained simultaneously at 10m height above ground level for the wind speed ranging 6m/s to 8m/s during the windy season of September 2022. The measurement data both at turbine hub height and 10m level were obtained at the same atmospheric condition 26o C and 0.996atm and in a down wind direction. The other parameters like Aweighted sound pressure level, 1/3 octave band spectrum, electric power, and wind speed were also measured at both hub heights at 10m level. The measured parameters were compared with the PULSE Software output and in the process; it is concluded that the noise characteristic of the experimental wind turbine is less than 3dB at a distance of 66m in the down wind direction from the test turbine. The measured results were also validated from the PULSE software and the results show a close match.

Protection of rotor side converter of doubly fed induction generator based wind energy conversion system under symmetrical grid voltage fluctuations

This paper presents the protection of the rotor side converter in a grid-connected doubly fed induction generator (DFIG)-based wind energy conversion system (WECS) during a symmetrical voltage dip. In order to manage rotor current and regulate DC link voltage, an efficient active crowbar protection circuit is implemented in the rotor side converter (RSC). To improve the low-voltage ride-through capability for grid-connected wind turbine systems, an integrated DFIG-based WECS role is crucial because wind turbines must remain connected to the utility grid during faults to ensure continuity and reliability of power supply. This paper aims to design and implement an efficient active crowbar protection technique to protect the RSC and avoid excessive rotor current during a symmetrical voltage dip. Therefore, the efficient active crowbar protection circuit is designed using MATLAB-Simulink software, and its performance is validated using a real-time (RT) simulator. Finally, the existing methods are compared with the proposed work outcomes, and a conclusion is made.

Zynq FPGA for hardware co-simulation of Takagi-Sugeno neuro-fuzzy for MPPT algorithm incorporating sensorless wind speed estimation in grid-connected wind system

This paper presents a hardware implementation on the Field Programmable Gate Array (FPGA) Zed-Board of a Maximum Power Point Tracking (MPPT) incorporating pitch angle control system and sensorless wind speed estimation using the Takagi-Sugeno (TS) Adaptive Neuro-Fuzzy Inference System (ANFIS). The described approach is applied specifically to a grid-connected Permanent Magnet Synchronous Generator-based Variable Speed Wind Turbine (VSWT). Firstly, the paper proposes an estimator-based TS-ANFIS model for real-time wind speed estimation, addressing challenges with conventional anemometers, such as precision, and susceptibility to adverse weather conditions. The estimated wind speed guides the calculation of an optimized mechanical speed for MPPT control. Secondly, an MPPT-based TS-ANFIS controller is introduced to achieve the maximum power point, integrating pitch angle control to prevent turbine failures in high wind speeds. Finally, the paper emphasizes the hardware implementation on the FPGA Zed-Board, leveraging its parallel processing capabilities to enhance control system quality by reducing sampling periods and loop delays. Validation includes simulations in Matlab/Simulink using the Xilinx system generator and hardware co-simulation on the FPGA Zed-Board. A comparative analysis highlights the contributions and advancements of the proposed models and controllers compared to recent schemes in the field. Indeed, the proposed MPPT-based TS-ANFIS approach effectively maximizes the power extracted from the VSWT, achieving an estimated average efficiency of 99.84 %. In contrast, PID methods show average efficiencies of 92.63 %. Additionally, compared to other published works, the proposed MPPT-based TS-ANFIS method demonstrates a rapid response time of 0.001 s and lower static error at 0.02 %. Furthermore, the proposed WSE-based TS-ANFIS model exhibits superior performance and effectiveness, yielding a root mean squared error (RMSE) of 0.0085381, a determination coefficient (R2) value of 0.99985, and a Pearson correlation coefficient (r) value of 0.99996. Moreover, the proposed hardware implementation of these approaches maintains lower power usage, operating at a high frequency of 80.38 MHz and achieving a high throughput of 2572.16 Mbps.

Dynamic voltage restoration using neural networks for grid-connected wind turbine

Dynamic voltage restoration using neural networks for grid-connected wind turbine

Adaptive machine learning for forecasting in wind energy: A dynamic, multi-algorithmic approach for short and long-term predictions

This study elucidates the formulation and validation of a dynamic hybrid model for wind energy forecasting, with a particular emphasis on its capability for both short-term and long-term predictive accuracy. The model is predicated on the assimilation of time-series data from past wind energy generation and employs a triad of machine learning algorithms: Artificial Neural Network (ANN), Support Vector Machine (SVM), and K-Nearest Neighbors (K-NN). Empirical data, harvested from a 2 MW grid-connected wind turbine, served as the basis for the training and validation phases. A comparative evaluation methodology was devised to scrutinize the performance of each constituent algorithm across a diverse array of metrics. This evaluation framework facilitated the identification of individual algorithmic limitations, which were subsequently mitigated through the implementation of a dynamic switching mechanism within the hybrid model. This innovative feature enables the model to adaptively select the most efficacious forecasting technique based on historical performance data. The hybrid model demonstrated superior forecasting accuracy in both, short-term energy forecasts at 15-min intervals over a day, and in broad, long-term. It recorded a Normalized Mean Absolute Error (NMAE) of 5.54 %, which is notably lower than the NMAE range of 5.65 %–9.22 % observed in other tested models, and significantly better than the average NMAE found in the literature, which spans from 6.73 % to 10.07 %. Such versatility renders it invaluable for grid operators and wind farm management, aiding in both operational and strategic planning. The study's findings not only contribute to the existing body of knowledge in renewable energy forecasting but also suggest the hybrid model's broader applicability in various other predictive analytics domains.

Wind power development: A historical review

Wind power only received occasional attention since the introduction of electricity until the 1970s, when a revived interest in alternative energy sources spurred the development thread that led to today’s wind turbines. Although attention and financial support at the time were directed toward government-funded MW-scale wind turbines, the small models developed in the late 1970s for the Danish market were ultimately the way forward. The wind industry has since matured, as evidenced by the lower specific power and higher capacity factors of recent turbine models and the similarity between their power curve shapes. Moreover, this study highlights two historical accomplishments by Europeans that are sometimes incorrectly credited to Americans: the first wind turbine to generate electricity was built in 1883 by Austrian Josef Friedländer and the Danish Agricco (1919) became the first public grid-connected wind turbine.

An Approach to Improve Power System Resiliency in Grid-Connected Wind Turbine Generator Power System

An Approach to Improve Power System Resiliency in Grid-Connected Wind Turbine Generator Power System

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.

Control optimization of grid-connected PMSG wind turbine with OOBO algorithm and cascade PI-PID controller

Control optimization of grid-connected PMSG wind turbine with OOBO algorithm and cascade PI-PID controller

A Modified Reduced-Order Generalized Integrator–Frequency-Locked Loop-Based Sensorless Vector Control Scheme Including the Maximum Power Point Tracking Algorithm for Grid-Connected Squirrel-Cage Induction Generator Wind Turbine Systems

A Modified Reduced-Order Generalized Integrator–Frequency-Locked Loop-Based Sensorless Vector Control Scheme Including the Maximum Power Point Tracking Algorithm for Grid-Connected Squirrel-Cage Induction Generator Wind Turbine Systems

Optimal Control and Optimization of Grid-Connected PV and Wind Turbine Hybrid Systems Using Electric Eel Foraging Optimization Algorithms.

This paper presents a comprehensive exploration of a hybrid energy system that integrates wind turbines with photovoltaics (PVs) to address the intermittent nature of electricity production from these sources. The necessity for such technology arises from the sporadic nature of electricity generated by PV cells and wind turbines. The envisioned outcome is an emissions-free, more efficient alternative to traditional energy sources. A variety of optimization techniques are utilized, specifically the Particle Swarm Optimization (PSO) algorithm and Electric Eel Foraging Optimization (EEFO), to achieve optimal power regulation and seamless integration with the public grid, as well as to mitigate anticipated loading issues. The employed mathematical modeling and simulation techniques are used to assess the effectiveness of EEFO in optimizing the operation of grid-connected PV and wind turbine hybrid systems. In this paper, the optimization methods applied to the system's architecture are described in detail, providing a clear understanding of the intricate nature of the approach. The efficacy of these optimization strategies is rigorously evaluated through simulations of diverse operating scenarios using MATLAB/SIMULINK. The results demonstrate that the proposed optimization strategies are not only capable of precisely and swiftly compensating for linked loads, but also effectively controlling the energy supply to maintain the load's power at the desired level. The findings underscore the potential of this hybrid energy system to offer a sustainable and reliable solution for meeting power demands, contributing to the advancement of clean and efficient energy technologies. The results demonstrate the capability of the proposed approach to improve system performance, maximize energy yield, and enhance grid integration, thereby contributing to the advancement of renewable energy technologies and sustainable energy systems.

An novel oscillation suppression strategy for permanent magnetic synchronous generator based on grid-forming control

With the increase of permeability of renewable energy and power electronic equipment, the inertia and damping parameters of the direct-drive wind turbine based on grid-forming control have a large impact on the system stability, and the system oscillation will be triggered when the parameters are not set properly. In this paper, the problem is addressed by establishing the small-signal model of two permanent magnetic synchronous generators connected to the grid in detail, analyzing the influence of the active control parameters on the system stability through the root locus of the dominant characteristic root, and proposing the adaptive control of damping and inertia to suppress the system oscillations. Finally, a real-time simulation platform for grid-connected wind turbine systems was built, and the experimental results verify the correctness of the small-signal modelling for stability analysis of grid-forming wind turbines established in this paper.

Modelling and Simulation of Grid Connected Wind Turbine Induction Generator for Windfarm

As the power generation sector moving towards the sustainability to achieve clean and renewable energy source, the wind power generation plays a vital role due to its abundance in nature. A big chunk of the decrease in carbon emission is a major attribute to the growth of the wind energy sector. Wind turbine production, structural development, logistics, maintenance and R&D are just some of the areas that could benefit from the growth of the wind energy industry. This brought out the attention of researchers of the electrical engineering to focus on wind power generation. It can be more efficient and cost-effective to operate wind turbines as a wind farm rather than individually. This has led to a surge in the construction of wind farms, both onshore and offshore wind farms. Therefore, in this paper, the study and analyse of single Induction generator with wind turbines and 33MW windfarm performance is presented. The simulation result demonstrates the efficiency of DFIG in producing energy at a constant wind speed, as well as its ability to regulate both active and reactive power at steady-state.

Influence of the Fictitious Grid on Flicker Assessment of Grid Connected Wind Turbine

This work studies the influence of the signal processing method on the flicker measurement of grid connected wind turbine in continuous operation according to the procedure detailed in the IEC 61400-21 standard. Two different methods for solving the fictitious grid are analyzed: Zero Crossing Detection and Short Time Fourier Transform. The deviations in the flicker measurement results obtained by applying both methods to actual signals from a measurement campaign are discussed. And the results are compared taking into account the grid impedance angle and the wind condition.

Virtual inertia support based frequency and dynamic voltage control for grid-connected SPMSG-based wind turbine

The Challenge to stabilize the grid frequency increases with the increment of renewable energy resources. System inertia/frequency control is a significant concern for maintaining system stability with a fast response time during the load transition. This manuscript proposes surface-mounted permanent magnet synchronous generator (SPMSG) based wind energy conversion system (WECS) with a frequency support DC-link controlling loop and a converter protective DC-link voltage-controller frequency support system. To achieve power exchange, the frequency control system (FCS) for the SPMSG-based wind turbine supports the grid-side virtual inertia. The DC-link voltage is disturbed during the load transition to maintain the frequency, while the electrolytic capacitor requires extra care regarding the DC bus voltage. This manuscript incorporates the FCS system with a supercapacitor and dynamic voltage limiter to avoid additional care of the DC bus voltage. A detailed analysis of system frequency with the additional load increment, normal connected load decrement, and various fault scenarios has been done. The proposed system is compared with the existing virtual inertia support (VIS). The simulation results show that the proposed frequency control system-based VIS efficiently limits the frequency deviations & DC-link voltage. The results are verified in the OPAL-RT 4510 real-time simulator environment to ensure the efficacy of the proposed system.

Dynamic Investigations of Grid Connected Fixed-Speed Wind Turbine During Grid Faults

Especially during grid faults, grid code requirements for wind power integration have become a key element in improving grid efficiency and reliability. Under severe problems for network operation, wind turbines are expected to continue operating and supporting the grid during frequency restoration. This paper presents simulation results of a fixed-speed grid-connected wind turbine under various short-circuit current contributions. Fault analysis is carried out by studying the grid side line to ground fault, double line fault, double line to ground fault, and three phase fault involving ground and without ground. The obtained current waveforms are analyzed to explain the behavior, such as the rate of decay and peak values. Variations of active and reactive power during post-fault conditions and faulty conditions are investigated. Moreover, recommendations for switchgear and protection equipment are performed.

Characteristics of sub-synchronous oscillation in grid-connected wind farm system

With the rapid development of wind power, wind turbines are accompanied by a large quantity of power electronic converters connected to the grid, causing changes in the characteristics of the power system and leading to increasingly serious sub-synchronous oscillation (SSO) problems, which urgently require the generalized classification and characterization of the emerging oscillation problems. This paper classifies and characterizes the emerging types of SSO caused by grid-connected wind turbines to address these issues. Finally, the impact of the typical system parameters changes on the oscillation pattern is analyzed in depth to provide effective support for the subsequent suppression and prevention of SSO.

Analysis of the impact of transient overvoltage on grid-connected PMSG-based wind turbine systems

The annual increase in installation capacity and electrical production of renewable energy sources, primarily wind turbine generators (WTG), is shaping a renewable energy dominated power system. WTGs are susceptible to the temporary overvoltage caused by reactive power surplus following low-voltage ride through (LVRT). This can lead to the large-scale trip-off of WTGs and pose significant risks to the secure and stable operation of power systems. An insightful elaboration of the underlying mechanisms determining the occurrence of temporary overvoltage, and an analysis of influencing factors, is pivotal to ensure the reliable integration of WTGs. This paper investigates the temporary overvoltage in the AC systems integrated with multiple renewable energy stations. A temporary overvoltage model that accounts for various types of equipment has been derived. Resorting to the model, the influence of LVRT parameters of WTGs, SCR and IR of the AC system on the maximum terminal overvoltage has been quantitatively assessed. Simulations and semi-physical validations have been conducted to verify the effectiveness and accuracy of the theoretical analysis.