Wind Conversion System Research Articles

Wind conversion systems effects on power grid and ability of thyristor controlled series capacitor and static synchronous series compensator devices for dynamic performance enhancing

Wind conversion systems effects on power grid and ability of thyristor controlled series capacitor and static synchronous series compensator devices for dynamic performance enhancing

Investigation of the Robust Fractional Order Control Approach Associated with the Online Analytic Unity Magnitude Shaper: The Case of Wind Energy Systems

This paper investigates the development of a novel analytic approach for computing Unity Magnitude (UM) shapers that deviates from established numerical methodologies. The experimental validation on a test bench confirms the practicality and benefits of the suggested UM shaper technique. The study extends the use of UM shapers to improve the control of wind conversion systems (WCSs), particularly those including hybrid excitation synchronous generators (HESGs), demonstrating their adaptability and versatility. Experimental validation guarantees real-world application, confirming the suggested UM shapers’ trustworthiness. Strict management is still required to assure the system’s efficiency and dependability. In reality, the dynamic equations of a turbine, as well as those of an HESG, are substantially nonlinear; most system parameters are very uncertain; and, finally, a WCS is always impacted by disturbance sources such as load variations, harmonics, and mechanical vibrations. Robust control measures must be used to overcome these issues. A CRONE controller (Robust Fractional Order Control) of the second generation is created. A comparative study performed on the Simulink platform reveals substantial gains brought about by UM shapers in real-world circumstances. The study demonstrates the effectiveness of UM-shaped inputs in mechanical stabilization and Maximum Power Point Tracking (MPPT), emphasizing both theoretical soundness and practical advantages. The analytic equations for UM shapers in undamped and damped systems, offered together with a real-time algorithm, contribute to the optimization of wind conversion systems.

Enhanced Backstepping Control for HESG-Based Wind Conversion Systems in MPPT Applications

Enhanced Backstepping Control for HESG-Based Wind Conversion Systems in MPPT Applications

Advanced modeling and control of wind conversion systems based on hybrid generators using fractional order controllers

AbstractThe focus of this study is on modeling and management of a Wind Energy Conversion System (WECS) based on a Hybrid Excitation Synchronous Generator (HESG). Using a wind simulator, two controllers, CRONE and H∞, are evaluated for Maximum Power Point Tracking (MPPT) and optimal rotation speed. The results show the CRONE controller's higher tracking capability, and robustness tests investigate the influence of parametric uncertainty. Space harmonic effects, commutation effects, and turbine shaft flexibility are all addressed in the sophisticated models. The introduction of Fractional Order Proportional‐Integral (FOPI) control for MPPT is a game changer. Although fractional calculus‐based accuracy and robustness are uncommon in WECS, they show promise for emissions reduction and increased energy efficiency. This work validates a dependable control approach inside an isolated HESG‐based WECS's power‐maximizing range. Extensive investigation of the parameters impacting FOPI control efficiency yields useful insights for effective MPPT control. A variable‐speed wind turbine (WT) is linked to a HESG through a multiplier, with a controller controlling generator coil excitation voltages and a rectifier connecting the WECS to a load. A thorough 3 kW HESG electrical model that includes generator space harmonics and converter commutation effects is among the contributions. For HESG‐based WECS stability, frequency analysis finds important resonant and anti‐resonant frequencies. These issues are addressed by a FOPI control technique, which ensures system stability and performance. The necessity of exact frequency analysis in HESG‐based WECS is highlighted by a step‐by‐step controller parameter tuning approach.

Robust fault estimation for wind turbine pitch and drive train systems

The reliability and accuracy of the wind conversion system largely depend on the early detection and diagnosis of faults. In this paper, a novel fault estimator for wind turbine pitch and drive train systems is developed. The main objective is to estimate actuator and sensor faults along with the system states while mitigating the impact of process disturbances and noises. To accomplish this, an augmented state is created by combining the states of the system and different faults. Subsequently, an Unknown Input Observer (UIO) is developed to estimate them simultaneously. The UIO matrices are obtained by optimizing a multi-objective function formed by transforming states and faults estimation errors into the frequency domain using a genetic algorithm. Compared with other approaches, particularly H∞, the proposed technique shows great superiority in accurately estimating various actuators and sensors faults.

Optimizing direct power control of DFIG-based WECS using super-twisting algorithm under real wind profile

In this study, we address the optimization of the direct power control of a doubly fed induction generator within a wind conversion system under actual wind conditions. The primary objective is to enhance the dynamic response of the wind energy conversion system (WECS) while minimizing the impact of wind fluctuations on power generation. To achieve this goal, we introduce a novel control methodology based on the super-twisting algorithm (STA). This approach allows for effective regulation of both reactive and active power output in the WECS. We employ comprehensive simulations using a detailed model of the WECS and real wind profiles to evaluate the efficacy of the STA-based control strategy. Our simulations demonstrate that the adopted STA-based control strategy successfully tracks the desired power set-point and effectively mitigates the adverse effects of wind power fluctuations and uncertainties on the WECS power output. Specifically, it exhibits superior performance in managing transients and rejecting disturbances compared to a conventional approach employing a switching table and hysteresis controller. These results suggest the practical viability and potential applications of the STA-based control strategy in real-world wind energy systems.

Effective uncertain fault diagnosis technique for wind conversion systems using improved ensemble learning algorithm

This paper introduces a pioneering fault diagnosis technique termed Interval Ensemble Learning based on Sine Cosine Optimization Algorithm (IEL- SCOA), tailored to tackle uncertainties prevalent in wind energy conversion (WEC) systems. The approach unfolds in three integral phases. Firstly, the establishment of interval centers and ranges, employing upper and lower bounds, effectively manages the inherent uncertainties arising from noise and measurement errors intrinsic to the wind system. Subsequently, the dataset undergoes processing via the Sine-Cosine Optimization Algorithm (SCOA), enabling the extraction of the most pertinent attributes. The culmination of predictive precision and classification performance is achieved through the integration of the refined dataset into an ensemble learning paradigm, harmonizing bagging, boosting techniques, and an artificial neural network classifier. The principal aim of the IEL-SCOA approach is to discern the spectrum of operational conditions within WEC systems, encompassing a healthy mode alongside six distinct faulty modes. These anomalies, encompassing short circuits, open circuits, and wear-out incidents, are deliberately induced at diverse locations and facets of the system, notably the generator and grid sides. Empirical results underscore the robustness and efficiency of the proposed methodology, showcasing an exceptional accuracy rate of 99.76 %. These outcomes definitively establish the IEL-SCOA approach as a potent and efficacious tool for precise fault diagnosis in uncertain WEC systems.

Operating the Induction Motor as a Generator Mode by Supplying DC Voltage and Investigation of the End Voltage Depending on the Excitation Current and RPM

Asynchronous or induction machines are among the leading devices in the electrical industry. They are well suited for motor and production applications with power ratings from a few kilowatts to megawatts. In addition, their use in renewable energy systems, especially in wind conversion systems, is increasing daily due to their advantages, such as low cost, brushless, and robust structure. In this work, the operation of a three-phase asynchronous motor with a winding rotor as an alternator, the variation of the voltage produced depending on the excitation current by keeping the number of revolutions constant, and the interpretation of the voltage produced according to the number of revolutions by keeping the excitation current constant have been investigated. The variation of the terminal voltage in ohmic, inductive, and capacitive loads has been experimentally investigated by observing the source voltage providing the rotational speed and excitation current constant.

Design and control of DFIG with SMES storage under symmetrical grid fault

<span lang="EN-US">This paper presents a novel design and robust control for wind conversion systems using DFIG. The system is designed to reduce the problems related to the sudden variation of the wind speed and to improve the sensitivity of the DFIG to grid faults to avoid disconnection of the wind system from the electrical grid. To enhance the DFIG behavior, power fluctuation and to protect power devices under symmetrical faults, a specific superconducting magnetic energy storage (SMES) scheme and its control are proposed. To validate this study, the control structure and strategies were implemented in the MATLAB/Simulink environment. The results obtained by simulation were compared with those using traditional control strategies, they highlight an improvement in the functioning of wind conversion systems of this type, showing the rigor and effectiveness of the proposed strategy.</span>

Efficiency, Cost, and Volume Comparison of SiC-Based and IGBT-Based Full-Scale Converter in PMSG Wind Turbine

Power electronics, as an enabling technology in most renewable energy systems, is gaining attention as the penetration of renewable energy sources increases. Wide-bandgap power electronics are of particular interest due to their superior voltage blocking capabilities and fast switching speeds. They can viably be considered in the renewable energy sources, especially as the penetration of wind energy is expected to increase by a great extent in the upcoming years. In this paper, a comparison of Silicon Carbide-based and Silicon-based wind energy conversion systems has been performed, as it is crucial in understanding the benefits of adopting wide-bandgap-based solutions at a commercial level. For this analysis, a 2 MW permanent magnet synchronous generator-based wind conversion system with a bidirectional full-scale frequency converter comprised of two back-to-back inverters is considered. The efficiency, cost, and total volume of the passive components comparison have been conducted for Silicon- and Silicon Carbide-based converters. The comparison presented is a fair comparison, meaning that the converters are designed with modules of the same power ratings. Wind energy systems are compared both for the same switching frequency (low switching frequency suitable for IGBT modules) and also considering a Silicon Carbide-MOSFET-based converter working at high switching frequencies. The comparison is performed in PLECS simulation tool, using the PLECS libraries for different modules obtained from the manufacturers’ experimental data. The results show the benefits of using the Silicon Carbide-based converter when it comes to volume reduction in the passive components and provide insights to what is missing in order to achieve overall system volume and cost savings.

Intelligent power control of wind conversion system based on Takagi–Sugeno fuzzy model

SummaryThis paper comes up with a novel fuzzy control design for a wind conversion system (WCS). To do this, a boost converter is employed to adjust the rectified voltage under different wind speed levels. Initially, the boost converter model is well presented via the Takagi–Sugeno approach. Then, a T‐S fuzzy controller is designed to promptly calculate the duty cycle required for an optimal power operation. Afterward, the optimal DC current is determined and then transferred to the reference model to instantly determine the desired trajectories. These latter should be preserved so as to reach the maximum power. Following that, linear matrix inequalities (LMIs) are also used to guarantee the stability analyses and the performance. Finally, the sound performance and the validity of the suggested control schema are both proved by a numerical and some experimental results.

Subsynchronous control interaction analysis between PMSG-based offshore wind farm and SVGs

With the rapid development of wind energy, the subsynchronous oscillations (SSO) involved with wind conversion systems, has been the focus of academic concern. To analyse the subsynchronous control interaction (SSCI) issue of multi-converters (wind-power converter and widespread SVGs), the state matrix of a typical PMSGs-based offshore wind farm system including SVGs is constructed . It is proposed that SVGs in wind farm may cause SSCI issue by their uncoordinated control targets. Under certain conditions, the SSCI between SVGs forms the dominant oscillation mode, delivered with variation of the SSO frequency. By calculating the influence factors along with different converters, it can be concluded that unreasonable parameter configuration of converters and variations of operating conditions affect the SSCI characteristics. At last, time domain simulation is used to verify the SSCI mechanism and characteristics of the PMSG-based offshore wind farm and SVGs.

A hybrid excitation synchronous generator for a 1.5 MW grid-connected wind conversion system

A hybrid excitation synchronous generator for a 1.5 MW grid-connected wind conversion system

Proposed robust ADRC control of a DFIG used in wind power production

This work presents the control of the double fed induction generator (DFIG) used in the wind conversion system (WCS). The studied model is based on the control of the two converters grid side converter (GSC) and rotor side converter (RSC), in order to extract the maximum of power and also to keep the direct current (DC) bus voltage constant. The control strategy used here is based on linear active disturbance rejection control (LADRC) controllers. These are known, in the field of control systems, by their performance and robustness and allow a very good rejection of disturbances which can affect the wind system. In addition, this kind of controllers could help to meet the requirements of robustness against the variations of the parameters of the system and the uncertainties of its mathematical model. To validate the effectiveness of the proposed control, the system was modeled and tested by numerical simulation using MATLAB/Simulink software. The results carried out are discussed and analyzed in terms of references tracking, robustness and disturbance rejection. The results obtained have shown shown that the proposed control is promising and useful.

Advanced Fuzzy 12 DTC Control of Doubly Fed Induction Generator for Optimal Power Extraction in Wind Turbine System under Random Wind Conditions

A wind turbine (WT)-based doubly fed induction generator (DFIG) is the most often used generator in the wind conversion system market due to its advantages such as the ability of operating under variable wind speed and its high performance. However, nonlinear dynamical and parameter uncertainties of the DFIG make the controller design of this kind of system a challenging work. Thus, in this study, a novel control strategy was proposed to design the desired system dynamics, to highlight the efficacy of the proposed system, and to improve the performance of the closed-loop system. The proposed controller combines the twelve-sector direct torque control (12-DTC) and the fuzzy controller with modified rules to solve the limitations and shortcomings of the usual methods for the WT-DFIG system. All operation modes, successively and continually, were considered to reflect the true operation of WT-DFIG system subject to random wind speeds. The aims of this work was to ensure an optimal operation of the wind generator, extracting maximum power in the zone II of the WT characteristic, and limiting this power in its maximum value in the case (zone III), to transmit the power generated by the DFIG to the grid-side with minimum losses in the disturbances related to DFIG. Extensive numerical simulations were performed under MATALB/Simulink, where the proposed fuzzy twelve direct torque control (F12-DTC) was compared with conventional nonlinear controls: conventional DTC (C-DTC) and 12-DTC. The simulation results demonstrated clearly that the proposed one had the highest performance and robustness, with a significant reduction in rotor flux and electromagnetic torque ripples and better-generated power quality with low currents’ THD over the conventional strategies (C-DTC and 12-DTC).

New intelligent direct power control of DFIG-based wind conversion system by using machine learning under variations of all operating and compensation modes

Wind Turbine (WT)-based Doubly-Fed Induction Generator (DFIG) is a nonlinear system, in which the wind has variable behavior, and the local reactive power depends on the random demand of the AC grid; all these make conventional controls insufficient for an adequate power output. Thus, a new direct power control (DPC) strategy is proposed in this paper, to force the system to track the desired dynamics with higher performance and less drawbacks. This new approach is based on machine learning, Neural-Network- and Neuro-Fuzzy-DPC (NN- and NF-DPC), both are designed to overcome the problems related to power control, wind and local reactive power variations. All operating modes (sub-synchronous, super-synchronous and synchronous modes), with the possibility of local reactive power compensation are considered in this paper. Both NN and NF networks have been trained under the MATLAB interface. The trained NF showed better efficiency than the NN; the learning time is reduced to a few seconds with less computational effort, and less complexity. The effectiveness of both controls has been confirmed through simulation tests using MATLAB software. The obtained results have shown that the NF-DPC strategy presents better performances than NN-DPC and conventional control, with fast response, robustness, less power ripples and reduced Total Harmonic Distortion (THD) in the generated currents.

Harmonic analysis and attenuation using LCL-filter in doubly fed induction generator based wind conversion system using real time simulation based OPAL-RT

The paper deals with the performance checking of an optimally designed LCL-filter connected along the grid-side converter (GSC) in a doubly fed induction generator (DFIG) based wind energy conversion system (WECS) in attenuating harmonics. A repetitive approach is required for designing the parameters of the LCL-filter. The reasons being the explicitness of design parameters and design requirements of the proposed filter like IEEE-519 Std. for harmonic current attenuation, maximum voltage difference allowed in between two sides of the filter to limit switching losses, and limit of reactive power compensation. The proposed filter is compared with the conventional LCL-filter. Based on the proposed method, a minimal inductance and optimal capacitance-based filter is obtained in this paper which is validated using a 2.2 kW DFIG based WECS. Comparative stability analysis of DFIG system with and without proposed filter is performed using small signal stability analysis. The system under study is simulated using MATLAB/Simulink and OPAL-RT 4510, simultaneously. Simulation results validates the effective use of proposed filter design method into DFIG system in terms of harmonic attenuation, total harmonic distortion and reactive power compensation.

Optimal sizing design of a 1.5 MW permanent magnets synchronous generator for an onshore wind conversion system

This paper proposes a fast and accurate optimal sizing design of 1.5 MW Permanent Magnets Synchronous Generator (PMSG) for a grid-connected wind application. A design strategy inspired from the output space mapping technique is adopted. A fast analytical model is used and detailed to determine the parameters and the performances of the PMSG. Then, the results are validated by a precise finite element model and adjusted iteratively until coherence between the two models is obtained. A multi-objective particle swarm optimization algorithm is deployed with aim of reducing the total losses and weight of the generator. The algorithm's parameters and results are given and analyzed. Three optimal machines are chosen and tested using a 2D-finite element model. The main design parameters of the optimal generators are given and discussed. Good efficiency and optimal designs are obtained for the sized machines thanks to the adopted design strategy.

Prediction of the Speed and Wind Direction Using Machine Learning

The wind is a free energy source; however, its high unpredictability is a significant integration problem of large wind power plant into an energy system. In a wind conversion system, the wind speeds are a vital power-generated tracking, regulation, schedules and dispatch and satisfy consumer requirements. This paper proposes using the machine learning (ML) based ant colony optimization (ACO) method for the wind speed prediction. A correlation among predicted and real data from climate models showed strong consensus. The significance of the current research depends on its ability to forecast wind speeds, a crucial precursor to performing successful incorporation of wind power.

Solar Photovoltaic Interfaced Quasi Impedance Source Network Based Static Compensator for Voltage and Frequency Control in the Wind Energy System

In this paper, the purpose of improving the power quality of the standalone wind conversion system (WECS) is to utilize a quasi-impedance (qZ) static compensator (STATCOM) integrated solar photovoltaic (SPV) source network. The standalone WECS has utilized the flywheel energy storage system (FESS) and the self-excited induction generator (SEIG). The SPV power generation network integrates with the STATCOM DC-Link to compensate for the voltage and frequency fluctuations over a longer time. The SEIG terminal voltage and STATCOM DC-link voltage are regulated using an enhanced second-order generalized integrator (ESOGI) with a fuzzy logic controller (FLC). The coordination logic is proposed in order to handle the various scenarios and make the device energy efficient. The unit is built for optimal usage of the electrical energy generated from renewable sources by utilizing physical energy storage systems such as flywheel and battery. In both batteries and flywheels, excess power from the SPV and wind turbines is collected. To verify the performance of the SPV supported STATCOM, the simulation and experimental studies are performed under specific load conditions. This paper describes an optimal way to produce and utilize green power with better energy efficiency. With various current conditions, the typical level of harmonic distortion of the source current is about 1.4% lower than that specified by IEEE Std. 519–2014 for the tolerable 5% level.