Application of Superconducting Magnetic Energy Storage to Compensate the Pitch System Delay in Output Power Smoothing of Wind Turbines

The pitch system is a central part of modern wind turbines and good pitch control is essential for proper operation of the wind turbine. However, often when considering the pitch control, the pitch system dynamics is approximated by a simplified low order model, which may be acceptable for electrical pitch systems and turbine control purposes, but which does not capture the potential damping possibilities that may arise by actively using the fluid power systems to reduce the loads on the wind turbine structure. The focus of the current paper is therefore on the load reduction possibilities arising from applying an active damping filter in the fluid power systems to damp structural loads on the wind turbine, while maintaining the power production. Utilising the 5MW NREL reference wind turbine the paper presents a model of the fluid power pitch system, which is incorporated into the aeroelastic code FAST. Based on the model, an active damping approach is applied in combination with the standard pitch control to reduce oscillations in the pitch actuator force and hence the fatigue loadings on the mechanical structure. With basis in the implemented algorithm, the wind turbine is simulated under standard (IEC) load conditions and the load reduction possibilities analysed for the critical areas of the wind turbine along with performance of the wind turbine (pitch angle and power output).

The electrical networks installed already has a lot of traditional generators-based wind turbines (WTs) as a squirrel cage induction generator (SCIG). The day by day with increasing of loads, it became necessary to increase the generation to match the load demand, because of SCIG has a bad effect on the electrical network stability, the permanent magnet synchronous generator (PMSG) is the preferred type to increase the generation in the future. The load insertion and rejection causing a fluctuation in the frequency and voltage. So, there is an urgent issue to utilize an energy storage system with robust control to overcome transient events and improve the power system performance with WTs. The superconducting magnetic energy storage (SMES) system is the best solution mixed with renewable energy sources (RESs) because it has a lot of merits in efficiency, time response, and lifetime. The combination of the SMES, SCIG, and PMSG lead to an increase in the overall capacity of the electrical network. To control and state the SMES modes of operation a fuzzy logic controller (FLC) is utilized. The system components such as SCIG, PMSG, SMES, and FLC are performed by MATLAB/Simulink, in addition to the simulation results which proved the capability of the FLC-SMES to alleviate the frequency and voltage of the studied system. Also, PMSG has a better response to power systems.

Wind velocity distribution differences in wind wheel rotation plane caused by wind shear and tower shadow, not only causes load fluctuations of wind turbine blades, but also leads to pulsations of wind turbine aerodynamic torque and output power. In order to reduce the influence of wind shear and tower shadow on the fluctuations of three-bladed wind turbine, an individual pitch control strategy based on the pitch angle signal adjusted jointly by wind turbine output power and rotor azimuth angle is proposed. A band-pass filter is designed to filter out the three times pulsating component of the wind turbine output power, and a PID controller is used to obtain regulatory signal of pitch angle, which is then converted to tiny variable of each blade combining with the azimuth angle signal and superimposed to the reference pitch angle of the collective pitch control. Simulation results on GH Bladed platform show that the proposed individual pitch control strategy is effective to smooth blade load fluctuation, diminish aerodynamic torque ripple, reduce rotor fatigue damage, and prolong life time of wind turbine.

With variable speed wind turbines (VSWT), the maximum power point tracking (MPPT) should be implemented through making the rotor following the optimum rotor speed. But, due to wind variability, there will be fluctuations in the output power of wind turbine generators. If these generators are connected to a DC grid, the power fluctuations will negatively be reflected on the DC voltage. So, Superconducting Magnetic Energy Storage (SMES) is proposed in this study as an effective solution for voltage stabilization of DC grids connected to wind energy systems. The adopted wind turbine generator is Permanent Magnet Synchronous Generator (PMSG). The models of wind turbine, PMSG, and interfacing rectifier are built using PSCAD/EMTDC software. Then, a model for SMES is built including a superconducting coil with large inductance and a DC-DC bidirectional converter. The SMES control is built through PI controller to determine the duty cycle to the DC-DC bidirectional converter to achieve charging, freewheeling and discharging modes for the SMES. Two various operating conditions are considered, operation with variable wind speed and operation with sudden load change. SMES could effectively absorb the excess or deliver the shortage in output power enabling DC voltage stabilization at the desired value.

The Output power of wind turbine is determined by wind speed. The Output power can be adjusted by controlling the generator speed and pitch angle of wind turbine. When the wind speed below the wind turbine rated, the output power of generator can be maximized by controlling the generator speed at point of maximum power coefficient. When the wind speed above the wind turbine rated, output power of wind turbine will exceed the power generators rated. In this condition, the output power of wind turbine needs to be regulated to conform to the generator power rate. Output power of wind turbine can be regulated by adjusting the pitch angle of wind turbine. In this paper is developed the control strategies based intelligent control for controlling the generator speed and pitch angle of wind turbine, so the maximum output power tracking (MOPT) of wind turbine can be obtained at any wind speed variations. Generator speed is controlled using PI Fuzzy Logic Controller (PI-FLC) based Direct Field Oriented Control (DFOC). Pitch angle of wind turbine is controlled using Elman Recurrent Neural Network (RENN). The simulation results with Matlab Simulink shows that the both controller was successfully regulates the output power when the wind speed above the wind turbine rated and the output power can be maximum when the wind speed below the wind turbine rated.

Recently there has been a marked increase in wind power generation. From a power system point of view, because a wind turbine is an intermittent generator with large output fluctuation, any increase in the number of wind turbines gives rise to concerns about the adverse effects of wind turbines on power quality. The smoothing effects of wind turbine output fluctuation are of great importance in assessing the impacts of a large number of wind turbines. With regard to impacts on power system frequency (generation–demand balance), smoothing effects on a power system‐wide scale need to be examined in greater detail, because impacts of wind turbines on power system frequency are dominated by the total power output of wind turbines interconnected to the system. This article examines smoothing effects of wind power output on a power system‐wide scale. First a summary of wind measurements, in which observations were made at 16 sites, is presented. Next, correlation coefficients of wind power output of distant wind turbines are analysed; considerable differences are observed in the correlation coefficients from day to day. Then a new indicator for assessing the smoothing effects—average coherence—is introduced to resolve difficulties of conventional indicators such as coherence. Average coherence is evaluated for the measured data; the results show that smoothing effects among wind farms distributed over some hundreds of kilometres may not be so significant for periods of more than about 100 min. Copyright © 2004 John Wiley & Sons, Ltd.

Application of Neural Network Fitting for Pitch Angle Control of Small Wind Turbines

Variable pitch control technology is one of the key technology of wind power generation technology. This paper has studied the pitch control system of wind turbine and the variable pitch power control strategy for wind turbine. Based on the control system and control strategy, Hydraulic variable pitch control system model is established, and build a variable pitch wind turbine system. Then, it has been design an improved PID controller for variable pitch control system. The simulation analysis has carried using Matlab/Simulink simulation software for opening and closing oars two process to carry, the result shows that the improved PID controller of hydraulic variable pitch control system has good speed and accuracy.

The power output of a wind turbine depends on both wind speed and turbine control. There is a fluctuation in the natural wind speed, which changes the turbine power output. In this paper blade pitch control based on detailed monitoring of the inflow wind, including vertical velocity distributions, has been experimentally evaluated in a field test wind turbine. The inflow wind speeds were observed by 11 sets of ultrasonic anemometers. In this first test, the blade pitch is changed to keep optimum angle of attack based on the local inflow wind speed in the rotor plane. The blade pitch is independently controlled as a reference radial position of 80% of rotor radius. As a result of the pitch controls, the wind turbine power output was increased and the power output fluctuation was decreased for the cyclic pitch control based on the local wind speed. With the cyclic pitch control, the fluctuation in rotor thrust and average rotor thrust were also reduced compere to collective pitch control.

The instantaneous wind speed variations are ignored in the wind turbine power curves. Hence, the output power of the wind turbines becomes a function of only the average wind speed. In the variable-speed wind turbines, the output power is a function of wind speed as well as the wind dynamics because in order to extract the maximum amount of electrical energy, the control system in these turbines will adjust the rotor speed and blades' pitch angle according to the instantaneous wind speed. Since the wind dynamics is not taken into account in the power curve, the power generated by the controllers is overlooked and therefore the turbine output power is not represented accurately by the power curve. In this paper, a new method is proposed using a new index called wind turbine controllability factor in order to make it possible to calculate precisely the output power of wind turbines based on the wind dynamics. In this method, the energy pattern factor is used as an indicator of the amount of instantaneous wind speed variations and power curve is modified corresponding to the values of the energy pattern factor.

<p>With the increase in the development of offshore wind farm (OWF) around the world, this paper describes OWF consisting of permanent magnet synchronous generator (PMSG) wind turbines connected to Active network (AC grid) and Passive network (loads) through Multi Terminal High voltage direct current(MT-HVDC) transmission system. This paper discusses the effect of using a Superconducting Magnetic Energy Storage (SMES) unit in a hybrid power system that contains OWF. In this paper, we have aggregated 300 wind turbines of 1.5 MW PMSG using an aggregation technique (multi full aggregated model using equivalent wind speed (MFAM_EWS)). Furthermore, we have used a detector to detect any tripping of any wind turbine and substitute the shortage of power due to this loss of wind turbines immediately through SMES. The Active network in this paper should have a minimum of 150 MW power to be supplied by controlling the SMES unit (absorbing or providing power according to the system requirement). Simulation has been carried out by MATLAB/Simulink program to test the effectiveness of the SMES unit during tripping some of the wind turbines, fluctuation in wind speeds, load change and voltage dips. </p>

This paper deals with the development of a wind turbine pitch control system and the construction of a Hardware-in-the-Loop-Simulation (HILS) testbed for the performance test of the pitch control system. When the wind speed exceeds the rated wind speed, the wind turbine pitch controller adjusts the blade pitch angles collectively to ensure that the rotor speed maintains the rated rotor speed. The pitch controller with the individual pitch control function can add individual pitch angles into the collective pitch angles to reduce the mechanical load applied to the blade periodically due to wind shear. Large wind turbines often experience mechanical loads caused by wind shear phenomena. To verify the performance of the pitch control system before applying it to an actual wind turbine, the pitch control system is tested on the HILS testbed, which acts like an actual wind turbine system. The testbed for evaluating the developed pitch control system consists of the pitch control system, a real-time unit for simulating the wind and the operations of the wind turbine, an operational computer with a human–machine interface, a load system for simulating the actual wind load applied to each blade, and a real pitch bearing. Through the several tests based on HILS test bed, how well the pitch controller performed the given roles for each area in the entire wind speed area from cut-in to cut-out wind speed can be shown.

Nghiên cứu được thực hiện nhằm tìm hiểu những ưu điểm và nhược điểm khi kết hợp các tua bin gió ở bus DC và bus AC. Được mô phỏng bằng phần mềm MATLAB/Simulink, mô hình gồm 5 tua bin gió PMSG được nối song song và với mỗi tua bin gió có công suất 200W. Khi mô phỏng ở tốc độ gió không đổi là 12 m/s, kết quả nghiên cứu cho thấy kết nối các tua bin gió ở bus DC cho ra công suất lớn hơn (PT =787 W) so với công suất ở bus AC (PT = 720 W). Khi mô phỏng ở tốc độ gió thay đổi, kết hợp các tua bin gió ở bus DC, hiệu suất kết hợp trung bình đạt 99.54%, cao hơn so với hiệu suất khi kết hợp tại bus AC là 97.64%. Có thể thấy rằng tổng công suất đầu ra của các tuabin gió được kết nối tại bus AC không phải là công suất cực đại vì tần số của điện áp AC được tạo ra bởi các tuabin gió phụ thuộc vào tốc độ gió, trong khi tổng công suất đầu ra của các tuabin gió được kết nối ở bus DC không bị ảnh hưởng khi tuabin gió hoạt động ở các tốc độ gió khác nhau. Do đó, việc kết nối các tuabin gió ở bus AC là không hiệu quả.

Produced power of a wind turbine depends on a mixed variety of factors such as wind speed, air density, wind beat and type of used generator in wind turbine. According to the probabilistic essence of wind speed and temperature which affect the other parameters, the output power of a wind turbine would be probabilistic. In this paper, a new proposal has been presented to predict the wind turbine generation. The results have been yielded based on data that measured in East Azerbaijan distributed company for a 3kw wind turbine. Investigation of turbine's dynamic, temperature changes and wind turbulence by considering wind dynamic make the proposed method to be more precise and reliable. The presented results show the impact of each effective parameter on output power of wind turbine. Also, it has been seen that the output power which is gained in this method is different from the one which only uses the average speed and wind speed standard deviation to assess the wind turbine generation capability.

This paper presents a method to maximize the output power of a DFIG wind turbine. In this method, an optimization technique based on mathematical analysis has been used. The modeling of DFIG is performed using MATLAB. To evaluate the maximum output power of a DFIG, detailed expressions for output power and losses are derived as functions of generator slip, the magnitude and phase angle of rotor excitation voltage in various wind velocities. The outcomes of this method demonstrate that maximum output power of a DFIG wind turbine do not happen in the maximum input power (the mechanical power of wind turbine).