Wind Power Conversion Research Articles

A comparative study of virtual synchronous generator and sinusoidal pulse width modulation in a wind high power conversion chain

The virtual synchronous generator (VSG) and sinusoidal pulse width modulation (SPWM) are two prominent control strategies that have attracted particular interest recently. In this paper, we compare these two inverter control strategies in a 5MW wind power conversion chain. The studied conversion chain includes a wind turbine, a permanent magnet synchronous generator, the power converters, namely the uncontrolled rectifier, and a two-stage inverter connected to the grid via an LCL filter. Our study of the two control methods shows that both strategies reduce the total harmonic distortion (THD) while respecting the grid connection conditions. The simulation results manifest that the VSG strategy has a better THD reduction of 0.99 % which is improved compared to the SPWM with a THD of 1.33%.

Performance analysis of cascaded doubly fed induction generator with matrix converter for wind power conversion systems

Performance analysis of cascaded doubly fed induction generator with matrix converter for wind power conversion systems

Artificial Intelligence-Based Direct Power Control for Power Quality Improvement in a WT-DFIG System via Neural Networks: Prediction and Classification Techniques

This paper discusses the improvement of power quality injected into the AC grid. This approach is achieved by enhancing the quality of injected power signals and mastering the active and reactive power exchanged between the DFIG based wind turbine (WT-DFIG) and the electrical grid, resulting in an improvement of the overall system performance and efficiency. This study includes all WT-DFIG operating modes, successively and continuously, as well as all local reactive power compensation modes. Therefore, novel control strategies are proposed in this paper for wind energy conversion systems based on artificial intelligence techniques. These techniques include Neural Network Prediction (PNN-DPC) and Classification (CNN-DPC). They aim to eliminate the drawbacks and difficulties associated with conventional Direct Power Control (C-DPC), while retaining its advantages. The paper also provides a thorough explanation of the mathematical models for neural network techniques and WT-DFIG system models. The MATLAB/Simulink environment is used to investigate the performance of the proposed techniques under different conditions and operating modes related to different scenarios. The results reveal a significant reduction in the ripple of the generated active power and the compensated local reactive power, better quality of the generated signal currents and a remarkable reduction in the current total harmonic distortion (THD). Furthermore, compared to C-DPC, PNN-DPC achieves a reduction of 72.07% in active power ripples, 77.07% in reactive power ripples, and 76.79% in current Total Harmonic Distortion (THD). CNN-DPC shows similar improvements with 72.04%, 77.13%, and 76.54% of reductions respectively. In addition, CNN-DPC slightly outperforms PNN-DPC. Nevertheless, both proposed control techniques show significant improvements in all characteristics compared to other methods. Consequently, the proposed control strategies indicate that artificial intelligence has the potential to improve the power quality and performance of wind power conversion system.

Fuzzy Logic-Based Smart Control of Wind Energy Conversion System Using Cascaded Doubly Fed Induction Generator

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.

New design of robust controller based on fuzzy 12 linguistic variables for wind power conversion system

New design of robust controller based on fuzzy 12 linguistic variables for wind power conversion system

Research and Analysis of Liquid Cooling Heat Dissipation Equipment for Insulated-Gate Bipolar Transistor Modules of Wind Power Converters Based on the Finite Element Analysis Method

The primary objective of this study is to develop a simulation model for a liquid cooling plate (LCP) for insulated-gate bipolar transistor (IGBT) modules, with the aim of reducing the operating temperature of wind power converters (WPCs). The initial impetus for this study was the observation that the energy conversion efficiency of a WPC declines when the operating temperature of the IGBT module exceeds a critical threshold. Three LCPs, with and without heat sinks, were modelled under extreme conditions using the finite element simulation method. The effect of the number and height of the fins on the cooling efficacy was evaluated through the simulation and analysis of the LCP model with heat sinks. The results demonstrate that the optimal configuration, comprising five 10 mm fins and 13 10 mm struts, can achieve the following reductions: maximum temperature by 11.4 K, heat dissipation efficiency by 3.33%, pressure drop by 10.6 KPa, and pump power by 31.00%. Moreover, the findings suggest that the number of fins has a significant impact on temperature fluctuations, whereas the height of the fins exerts a markedly significant influence on pressure drop.

Direct torque control of a dual star induction generator based on a modified space vector PWM under fault conditions

Recent studies have shown that electrical systems in wind power conversion are subject to a 67 % failure rate, and conventional three-phase generators are considered to be the most sensitive to these faults. Induction generator current harmonics are a major source of torque ripples causing acoustic noise and vibrations. These ripples can progressively increase under faulty operating conditions. In six-phase machines, there is appearance of high harmonic currents in the air gap as space harmonics. Power electronic converters are also subject to faults, the most common being Short-Circuit (SC) and Open-Circuit (OC) faults. SC faults cause large peaks in the line currents, which trigger the protection devices, resulting in a complete shutdown of the production system. OC faults, on the other hand, cause imbalances in the phases, but the system remains in operation.Direct Torque Control (DTC) based on Space Vector Modulation (SVM) at constant switching frequency is an effective solution to tackle induction generator current harmonics. This paper proposes a DTC combined with a Proportional Integral Fuzzy Logic Controller (PIFLC) optimized by Particle Swarm Optimization (PSO) in order to overcome the problems of torque ripples. Furthermore, using Vector Space Decomposition (VSD) and the Modified Space Vector Pulse Width Modulation (MSVPWM) strategy, a significant reduction of harmonics in the air-gap can be achieved.Simulations were carried out under MATLAB/Simulink, and the results obtained demonstrate the superiority of the proposed DTC-PIFLC-PSO controller in terms of robustness against wind speed variations and under faulty switch conditions in the power converter of the Dual Star Induction Generator (DSIG) generator. In addition, a comparative study with the classical PI controller is presented to show the effectiveness of the DTC-PIFLC-PSO controller against faults with a significant reduction in the Total Harmonic Distortion (THD) during both faulty and non-faulty conditions.

Hybrid DE-PSO algorithm for solving nonlinear equations of SHEPWM based wind power conversion

Hybrid DE-PSO algorithm for solving nonlinear equations of SHEPWM based wind power conversion

Disturbance observer-based finite-time adaptive neural control scheme of DFIG-wind turbine

This paper introduces a novel disturbance observer-based finite-time adaptive neural control approach to optimize wind power conversion in a doubly fed induction generator-based wind turbines (DFIG-WT). This control strategy offers appealing features including rapid finite-time convergence, both transient and steady-state performance enhancements, and robustness against external disturbances and inherent model uncertainties. The control strategy integrates the neural networks estimation capability with the interesting proprieties of the finite-time control method to achieve efficient wind power conversion. Closed-loop finite-time stability is conducted using the finite-time Lyapunov stability concept of nonlinear systems. The developed control strategy’s effectiveness is confirmed through numerical simulation.

Design and development of pilot plant applied to wind and light abandonment power conversion: Electromagnetic heating of solid particles and steam generator

With the rising capacity of renewable energy electricity but incomplete supporting dissipation equipment, this work develops a new charging and discharging device for electromagnetic heating of solid particles to convert electricity from renewable sources into superheated steam, which achieves battery storage efficiency with sufficient safety, terrain-independent and scalable through paralleling. The study reveals that the electro-thermal conversion efficiency of electromagnetically heated iron ore particles increases with particle mass flow rate at different wall temperatures, reaching a maximum of 93.8% at 500 °C. In contrast, the efficiency trend for quartz sand particles is inconsistent, peaking at 68% due to poor thermal conductivity causing inefficiencies at higher mass flow rates. A dimensionless mathematical model (Re-Nu, Re < 10) for both particles is derived from experimental data, offering theoretical guidance for industrialization. Experiments with a shell-and-tube solid particle-packed bed yield continuous production of 35 kg/h, 300 °C superheated steam for 12 min with an 86.4% discharge efficiency and achieve an 81% cycle efficiency, which surpasses compressed air storage(60%), approaches battery and flywheel efficiency(85%). Economic feasibility analysis for a 5MW/5MWH system under two business models demonstrates a short payback period of 2.62 years when providing industrial steam and 6.4 years when used in thermal power plant flexibility transformation. Technological innovations to improve equipment efficiency are critical to the first business mode (selling steam), while grid-determined peak prices are critical to the latter (thermal flexibility retrofits). The study underscores the technical and economic superiority of the proposed devices for utilizing abandoned wind and light, providing a novel solution for carbon reduction and peak shaving in the context of new energy.

Performance of Robust Type-2 Fuzzy Sliding Mode Control Compared to Various Conventional Controls of Doubly-Fed Induction Generator for Wind Power Conversion Systems

This paper presents a novel hybrid type-2 fuzzy sliding mode control approach for regulating active and reactive power exchanged with the utility grid by a doubly-fed induction generator in a wind energy conversion system. The main objective of this hybridization is to eliminate the steady-state chattering phenomenon inherent in sliding mode control while improving the transient delays caused by type-2 fuzzy controllers. In addition, the proposed control approach has proven to be successful in coping with varying generator parameters and exhibited good reference tracking. An in-depth comparative study with state-of-the-art advanced control techniques is also the focus of the present paper. The comparative study has three objectives, namely: a qualitative comparative study that aims to compare response times and reference tracking capabilities; a quantitative evaluation that takes into account time-integrated performance criteria; and finally, robustness capabilities. The simulation results, carried out in the Matlab/Simulink environment, have demonstrated the effectiveness and best performance of the proposed hybrid type-2 fuzzy sliding mode control with respect to other advanced techniques included in the comparison study.

Nondestructive and accurate prediction of IGBT junction temperature in wind power converters: based on IDMOA-ELM prediction method

ABSTRACT This study has made significant advancements in predicting junction temperature of IGBTs in wind power converters. An improved dwarf mongoose optimisation algorithm (IDMOA) with superior performance was developed. The IDMOA improves the initial solution quality through Hammersley initialisation, balances global search and local optimisation with nonlinear dynamic decreasing weight factors, and enhances population diversity via differential evolution strategy to avoid local optima. The IDMOA optimizes random parameters of extreme learning machine (ELM), overcoming the limitations of traditional manual parameter setting and constructing a high-precision IDMOA optimised ELM (IDMOA-ELM) model. Simulation results indicate that the IDMOA-ELM excels in predicting the IGBT junction temperature, achieving a low RMSE value of 0.1034 ℃. This significantly surpasses existing technologies and provides robust support for temperature management in wind power converters. Furthermore, to verify the performance of the DMOA-ELM in practical application scenarios, IGBT accelerated ageing experiments were conducted, yielding a comprehensive validation dataset. The high accuracy and effectiveness of the IDMOA-ELM were confirmed through comparative analysis with experimental data, enhancing the credibility of the research. This study achieved non-destructive and high-precision prediction of IGBT junction temperature in wind power converters and significantly improving the reliability of wind power converters.

Modeling and Experimental Validation on Current Uniformity Characteristics of Parallel Spiral Structure Surge Arrester in ±550 kV DC GIS

The employment of a multi-column parallel connection is intended to enhance the energy absorption capability and reliability of surge arresters. However, the disparity in reference voltage between each varistor column and the uneven current distribution may result in a reduction in performance or even failure of the surge arrester. The objective of this study is to investigate the spiral structure of a ±550 kV DC gas-insulated switchgear (GIS) parallel arrester and its influence on the current distribution characteristics. This research develops a model of a ±550 kV DC GIS arrester and performs an in-depth theoretical analysis using multi-physics field simulations. Subsequently, a ±66 kV miniature prototype is constructed, and the accuracy of the theoretical analysis and simulation results is validated by experiments, validating the effectiveness of the proposed method. This study calculates the self-generated inductance in the spiral structure of ZnO varistors using simulations. The influence of the self-generated inductance on the current distribution of the multi-column arrester when absorbing energy is further investigated. The results indicate that the self-generated inductance of the spiral structure can reduce the current deviation factor by 28–65%. This research provides a novel approach to improving current equalization in the parallel surge arresters of DC GISs for offshore wind power converter platforms.

Sensitivity analysis on heat pump - mechanical vapor recompression desalination system by recovering waste heat of offshore power converter station

Abstract Offshore wind power converter stations produce massive low-temperature waste heat, which can hardly be used constrained by their offshore location. Therefore, the recovery of the waste heat has been raising widespread concern. Meanwhile, a large amount of fresh water is needed for its cooling system. So, a novel system combining high temperature heat pump and a mechanical vapor recompression system (HP-MVR) was proposed, and sensitivity analysis was performed to optimize it. The heat pump was used to absorb the waste heat and to produce high temperature water. The mechanical vapor recompression system was adopted to produce fresh water and to recover the condensation heat from the steam. In order to determine the impact parameters on the two crucial performance indicators of freshwater production and unit energy consumption, this article introduces a sensitivity analysis method, focusing on analyzing the sensitivity of the three operating parameters of heat pump condensation temperature, saturated water vapor inlet temperature entering the compressor, and freshwater condensation temperature to these two performance indicators. The results show that the sensitivity coefficients of heat pump condensation temperature, saturated water vapor inlet temperature entering the compressor, and freshwater condensation temperature are 1.13, -0.26, and 1.56. So, the freshwater condensation temperature has the most significant effect on freshwater output. Their sensitivity coefficients to unit energy consumption are 1.02, 1.41, and -0.64. The saturated water vapor inlet temperature entering the compressor has the most significant impact on the required power consumption per unit of freshwater. It will give some guidance for the application of low-temperature waste heat in seawater desalination and the reduction of operating costs.

Advanced control scheme of doubly fed induction generator for wind turbine using second sliding mode control

This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator(DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC).Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.

Enhancing wind power conversion efficiency with Vernier DSPM generator and sliding mode control

Enhancing wind power conversion efficiency with Vernier DSPM generator and sliding mode control

Ziegler-Nichols Based Controller Optimization for DFIG Wind Turbines

Wind power conversion systems are becoming the most preferable alternate renewable energy source. Doubly Fed Induction Generator’s utilization rotating parts in wind turbines is increasing with the wind power penetration to the electric grid. The observation becomes more noticeable when there are abnormal conditions within the electrical power system. In this paper, MPPT Controller is incorporated with DFIG through the MATLAB Simulink program is simulated. A conventional PI controller is tuned with Ziegler-Nichol’s (Z-N) method and was implemented to the DFIG Control Block. The rotor-side converter (RSC) is utilized to regulate the power generated by the doubly-fed induction generator (DFIG), while the direct current (DC) bus voltage is controlled by the grid-side converter (GSC). The DFIG's angular and comparative angular speeds are used to generate the reference torque value in the MPPT controller. This improved the time response, output power, electromotive torque, and other current and voltage characteristics. A comparison was made between the output evaluation of the inbuilt controller and the output evaluation of the proposed controller. The MPPT with tuned PI Controller's results show that the suggested system, which uses DFIG coupled to a rotor, is accurate, dependable, and feasible. DOI: https://doi.org/10.52783/tjjpt.v45.i02.6966

Active power smoothing control strategy of offshore wind power system based on reduced matrix converter

On account of the fluctuation and randomness of wind speed, the output power of wind turbines fluctuates greatly, which may cause the frequency change of the power grid and increase the difficulty of power system dispatching. To solve this problem, an active power smoothing control (APSC) strategy based on RMC for offshore wind power systems is proposed in this paper. Compared with existing wind power converter systems, RMC adopted in this paper has the advantages of compact structure, small volume and high conversion efficiency. Based on the analysis of the exponential moving average (EMA) algorithm, a method for determining active power based on the fuzzy EMA algorithm is proposed. The method adjusts the cycle number N in real-time according to the wind speed, taking into account both the wind energy utilization rate and the smoothing performance of active power. The control principle of offshore wind power generation system (WPGS) based on RMC is analyzed in detail and the coordinated control strategy of RMC and inverter is proposed. Simulation results demonstrate the validity of the proposed method and control strategy.

Study on Grid-Connected Power Quality Improvement of Wind Farms Based on Repetitive Controller

The project highlights the wind energy and the process followed in the wind farms in order to generate the energy by using wind power and wind capacity as well. Moreover, it has been observed that wind energy is also considered one of the most effective electrical energy sources. The application of wind energy can be beneficial for different aspects of the business sectors of different countries across the globe and this is possible because of its cost-effectiveness. Furthermore, this study encompasses the strategies employed within wind farms to preserve and efficiently harness wind power for the generation of electrical energy. Notably, the project delineates the utilization of a diverse array of instruments, each instrumental in the conversion of wind power into valuable wind energy. Beyond the realm of technology, wind farms grapple with a spectrum of formidable challenges, stemming from the inherently capricious nature of wind. In addition, various issues concerning power quality and the stability of the power system have also been identified within these wind farms. To ameliorate these multifaceted challenges, the project introduces a range of meticulous control measures for implementation.

A Multi-Information Fusion Algorithm to Fault Diagnosis of Power Converter in Wind Power Generation Systems

Power electronics-based converters are the major and most vulnerable components in wind power generation systems. Converter faults will affect power quality,damage expensive equipment such asgenerators, or even pose a massive threat to the entire power grid. Fault diagnosis is considered as a powerful means to improve system reliability and reduce maintenance costs. Existing data-driven fault diagnosis methods related to improving feature extraction approaches to obtain high diagnostic accuracy are mostly based on single-scale feature of signals; this neglects the potentially valuable information of other scales. This paper proposes an algorithm of Dempster-Shafer and Deng entropy fusion multi-scale approximate entropy (DSDEMAE) for wind power converter fault diagnosis. Firstly, it calculates the multi-scale approximate entropy of fault signals, mining more potentially valuable information. Secondly, Dempster-Shafer is used to fuse features of various scales and effectively handles the conflicts and uncertainties between different features. Finally,Deng entropyis adopted to measure the uncertainty to adjust weight distribution, reducing the influence of highly conflicting features and mutually benefitting features of different scales. Extensive experimental results on simulated and experimental data demonstrate the effectiveness of the proposed algorithm. Compared with advanced methods, this method can diagnose the faults with higher accuracy and stronger robustness.