Wind turbine blockset in matlab simulink pdf

The switching models include minimum pulse width, dead-time compensation and pulse dropping. Common Blocks Library. The basic transformations are from abc to dqo arbitrary reference and the opposite one, as well as from a dq signal to the complex representation of it.

In order to take the connection type into account, some transformations from a three-phase system in phase quantities to a three-phase one but in line-to-line quantities have been implemented. In order to find the magnitude and the phase for a three-phase system the corresponding block can be used.

Content of the Transformations Library. Some of these models e. Measurements Library. Since the main component of a control scheme is the PI Controller, a model with an anti wind-up structure has been implemented in Simulink.

A simplified control for active and reactive for a doubly fed induction generator is developed. This control algorithm can be used with a reduced order model of the generator Fig. Content of the Control Blocks Library. This library will be extended with other types of controllers as for example the active stall controller and capacitor bank controller used in fixed-speed wind turbines.

Each method implements the same set of dynamic equations for the induction machine in different ways. The general structure for these models is shown in Fig. Simulink model of induction machine in Simulink. Implementation of induction machine model in dq-rotor reference frame used in Model A and Model B. The only difference between Model A and Model B consists in the implementation of the state-space equations with currents as state-variables.

The same equations are implemented in Model B by using few blocks, e. Function and Integrator blocks. The third model - Model C — shows in Fig. Simulink implementation of dynamic equations for Model A. Simulink implementation of dynamic equations for Model B.

Simulink implementation of dynamic equations for Model C. The Simulink Profiler collects performance data while simulating a model and generates a simulation report. This report is useful to find out how much time Simulink spends on executing each block from a model and hence where to focus the model optimization efforts. The simulation mechanism in Simulink involves several callbacks to some specific Simulink Functions at each time step. Pseudo-code for execution of a dynamic system model in Simulink According to this conceptual model, Simulink executes a dynamic model by invoking the functions presented in Table 3.

The Profiler measures the time required to execute each invocation of these functions and generates a report at the end of the model that details how much time was spent in each function. Table 3. Function Purpose Level Simulate the model. This top-level function invokes the other sim functions required to simulate the model. The time spent in this System function is the total time required to simulate the model.

ModelInitialize Set up the model for simulation System Execute the model by invoking the output, update, integrate, etc. Output Compute the outputs of a block at the current time step.

Block ModelTerminate Free memory and perform any other end-of-simulation cleanup. Ode5 fixed step solver has been used. Simulink Profiler Summary Report for the considered models.

The number of blocks used in a model has a big influence on the total simulation time as shown in Table 2. Model A, which uses much more blocks than Model B, has the biggest recorded time even if the number of Integrator blocks is the same. The functions for the constitutive blocks from the models have been omitted. So, the total simulation time for a Simulink model is affected first by the number of blocks used in the model and then by the number of Integrator blocks.

Total time spent executing all invocations of specific functions for the considered models as a percentage of the total simulation time for Model A. Average time for execution of a C S-Function and for an Integrator block. It has been considered the average time self-time required to execute Update, Output and MinorDeriv functions for these blocks as a percent from the sum of the self-time for these functions for the Integrator block.

It is obvious that the total time required for all invocations of functions related to the S-function block is smaller than the corresponding time for one Integrator block even if this S-function implements five differential equations.

Therefore, using a S-function which implements all the differential equations from the considered dynamic system, the simulation speed can be increased with at least a factor of two. Moreover, the numerical stability increases using an S-Function. So, in modelling of large dynamic systems, which involves a big number of Integrator blocks it is desirable to use C S-Function concept in order to increase the simulation speed and improve the numerical stability.

The content of the main libraries is briefly presented and then some aspects regarding the simulation speed for the developed models are shown.

The mathematical descriptions for the models as well as their Simulink implementation are shown. The wind speed is calculated as an average value of the fixed-point wind speed over the whole rotor, and it takes the tower shadow and the rotational turbulences into account [71]. A main component in this model is the normally distributed white noise generator.

Therefore, in order to obtain the same wind time series in all considered simulation tools used in the Simulation Platform some investigations have been done. It has been found that the built-in white noise generator from different simulation tools uses a different algorithm and thus a different wind time series is obtained. Currently, the wind model is available in two basic versions. The general structure of these Simulink models is shown in Fig.

Simulink implementation of the wind model. Mask interface for wind model. In order to validate the new white noise generator model some comparisons have been done. A wind time series for sec with 0. The 20 bin-width histograms for these wind time series are presented in Fig. Finally, the power spectra density for both wind time series has been calculated as shown in Fig. Even if the wind time series for the considered models are not identically as shown in Fig.

The Simulink model for the variable pitch wind turbine rotor is presented in Fig. Simulink model of the wind turbine rotor. The parameters from the mask interface are: blade radius, air density, cut-in and cut-out wind speeds, as shown in Fig. Mask interface for the wind model in Simulink. The masses correspond to a large mass of the wind turbine rotor, masses for the gearbox wheels and a mass for generator respectively.

Two-mass model of a wind turbine drive train. The moment of inertia for the shafts and the gearbox wheels can be neglected because they are small compared with the moment of inertia of the wind turbine or generator. Therefore the resultant model is essentially a two mass model connected by a flexible shaft. Only the gearbox ratio has influence on the new equivalent system. The dynamic equations can be written in two points: on the wind turbine side with the influence of generator component through the gearbox and on the generator side respectively.

The equivalent system on the generator side is shown in Fig. Equivalent diagram of the wind turbine drive train on the generator side. Simulink implementation of a two-mass model for the wind turbine drive train. The parameters from the mask interface are: moment of inertia for machine and wind turbine rotor, equivalent stiffness and damping coefficients for the shafts, gearbox ratio and initial conditions for the state variables speeds and angles for the low speed and high speed shafts , as shown in Fig.

Mask interface for the two-mass model of the drive train. One-mass Simulink model for the wind turbine drive train. These equations are written using both fluxes and currents as state-variables. Simplified diagram of induction machine with rotor and stator windings. Substituting 4. The derivative of the inductance matrix from 4. Grouping 4. For squirrel-cage induction machines, these inductances can normally be estimated from no-load and locked rotor tests.

From 4. A solution is to use modern software tools, which have these capabilities e. Starting from the general form 4. Matlab, Maple or Mathcad the coefficients from 4. Moreover, the operating mode, motor or generator, as well as the connection type for the stator windings, star or delta, can be selected.

A similar model and mask interface are available for wound rotor induction machine 4. A change of variables is often used to reduce the complexity of these state-space equations. There are several changes of variables, which are used but there is just one general transformation [34]. In this reference frame the machine windings are replaced with some equivalent windings as shown in Fig.

Induction machine windings in the dqo-arbitrary reference frame. Based on 4. The compact form of 4. The voltage equations are written again in terms of currents and flux linkages. Clearly, these variables are related based on the matrix inductance [ L ] and both cannot be independent or state variables.

After some mathematical manipulation, the state-space form of the dynamic equations 4. This, however, is not the case. Even though the flux linkages contain the leakage inductances, they are eliminated by the algebra. For balanced steady-state operation, the variables in synchronous reference frame are constants. This toolbox is a very powerful tool for reduced order modeling.

Based on some specific functions as modred, ssbal, minreal, and balreal the desired state variables can be eliminated from the state space equations and the reduced order models are obtained. The Simulink model for this machine is based on 4. Simulink implementation of the reduced order model for the induction machine.

The only difference consists in the initial conditions for the state variables, which are the fluxes in this case. For balanced steady state conditions the d and q variables are sinusoidal in all reference frames except the synchronously rotating reference frame wherein they are constants. In the following paragraphs the prime index will be used for the rotor equations in order to highlight that these are related to the stator circuit of the machine.

Equation 4. Equivalent circuit for steady state operation of a symmetrical induction machine. The steady-state voltage equations 4. Equivalent per-phase quadri-pole for the induction machine used in the steady-state analysis. Recalling 4. Using this approach the induction machine can be completely characterized in terms of steady-state values of the stator and the rotor currents, phase angle for both currents, electromagnetic torque, active and reactive power for both stator and rotor circuit.

Moreover, an analysis, both in motor and generator mode of operation, can be performed. The Simulink implementation of the steady-state model, both for a squirrel-cage machine and wound rotor one, is shown in Fig. Simulink implementation for steady-state model of induction machine. It has been chosen to use these blocks because the model also implements the rotor deep-bar effect.

Using these blocks the model can be implemented in matrix form with the minimal number of blocks. However, the model can also be implemented using standard blocks from Simulink.

The parts of each bar extending deeply into the rotor iron have higher leakage inductances than those parts of the bar cross-section near the air gap, because more of the leakage flux links the deeper parts of the bar. One may think of each bar as being composed of several layers of equal cross section, and thus of equal resistance, but with inductances increasing with depth.

Deep-bar effect for a squirrel cage induction machine. Under running conditions, the slip is quite small and the frequency of the rotor currents is only Hz. As a result, the leakage reactance is neglected, and the current distribution is essentially uniform throughout each rotor bar. The effective resistance of the rotor is that of all layers in parallel.

This low resistance makes for low slip and high efficiency at full load. As the motor is overloaded, however, slip and frequency increase. Thus, the value of rotor leakage reactance in the circuit model becomes smaller and the value of rotor resistance becomes greater. Another important need is to include the leakage path saturation effect into a reduced model. The main saturation leakage path is at the tooth tips over the closed or nearly closed slots [46].

However, large machines usually have large slots openings, and hence the leakage path saturation effect is not significant for large machines [3]. Numerous approaches regarding the modelling of deep-bar effect have been presented in literature; therefore, all these models are complicated and require complex mathematics [3], [41], [42].

In [3] is presented a simplified approach for the modelling of deep bar effect, which gives accurate results. Therefore, this approach assumes a linear dependency of rotor resistance and rotor leakage reactance against the entire range of slip. Moreover, it requires extra parameters determined from tests at synchronous speed. Usually, the parameters from data sheets are given for rated operating point, near the synchronous speed and the method cannot be applied.

Resistance and leakage reactance deep-bar factors can be determined based on rated voltage and current, starting current and phase angle from short-circuit test at rated current. If the phase angle is not available, a value around 80o can be used as a good approximation in the first step of iteration. Then it can be corrected so that the calculated starting torque will fit the value from datasheet or test reports. Deep-bar effect for a 2 MW squirrel-cage induction machine as a function of slip: a rotor resistance rotor leakage reactance and b electromagnetic torque.

The same approach can be used for doubly fed induction machine since the manufacturers performs the standard tests as for the squirrel-cage induction machines. The Simulink model of induction machine, which implements the variation of the rotor parameters with the slip, is shown in Fig. Simulink model of the induction machine in dq rotor reference frame including deep-bar effect. The mask interface for this model is shown in Fig. Mask interface for the induction machine in dq rotor reference frame including deep-bar effect.

In order to include the deep-bar effect some additional parameters have been added in the mask interface: rated voltage and current, base frequency, number of pole pairs, starting current, phase angle at standstill. All these parameters are usually available in standard data- sheets. It will be assumed that the saturation of the leakage fluxes into a large induction machine can be neglected [33], [46] thus, the stator and rotor leakage inductances are constant.

The magnetizing inductance is a function of magnetization current as shown in Fig. Magnetizing flux versus magnetizing current. Assuming that the machine has magnetic, electric and geometric cylindrical symmetry, then the magnetic saturation caused by the main magnetic field is independent by the direction of this field and depends only on the absolute value of it.

Based on magnetization curve shown in Fig. Magnetizing and dynamic inductance versus magnetizing current. Then, using a mathematical approximation e. A simple search in IEEE database will produce around results. All these papers deals with the iron loss modelling for an inverter-fed induction motor and take into account the hysteresis losses as well as the eddy-current losses in a wide range of speed and frequency.

In wind turbine applications usually a large squirrel-cage induction generator is directly connected to grid and the rotor speed is almost fixed. When a doubly fed machine is used, again the stator windings are directly connected to the grid and the variable speed operation is achieved using a power converter in the rotor side.

In data sheets the no-load power, current and power factor are provided for the machine rated voltage as well as the electrical parameters for the rated operating point. So, it is convenient to use only this information in the case of a large induction machine, both squirrel-cage and wound rotor. A classical approach in iron losses modelling for an induction machine involves a resistance inserted in parallel with the magnetizing reactance in the equivalent per-phase diagram, as shown in Fig.

Equivalent diagram per-phase for induction machine including iron losses resistance. So, it is difficult to use this equivalent diagram for a dynamic model as well as for a steady state analysis. Unfortunately, the currents in this equivalent scheme are multiplied with some factors and the dynamic modelling become difficult.

A simple approach assumes the iron losses resistance in series with the magnetizing reactance as shown in Fig. Equivalent T diagram of the induction machine with iron losses. Where the parameters of the magnetizing branch can be determined based on parameters from Fig. The electrical parameters for the parallel mode can be transformed through some simple mathematical calculations to the series mode equivalent circuit.

This model can be also used for a non-salient pole machine assuming identical values for inductances in d- and q-axis. Untransformed model In synchronous machines with salient poles the damping bars can be represented by a direct- and a quadrature-axis damping winding, which are short-circuited windings. Assume that on the stator of the machine there is a symmetrical three-phase sinusoidal distributed stator winding and on the rotor there are the field winding and direct- and quadrature-axis damper winding.

Schematic of the machine is shown in Fig. Schematic of the three-phase synchronous machine. Schematic of the corresponding model is shown in Fig. Schematic of the transformed model for salient-pole synchronous machine. Commutator model It can be shown that when the stator quantities of the salient pole machine are expressed in the d-q-o reference frame fixed to the rotor, the components of the stator flux linkages expressed in the rotor reference frame will not contain the rotor angle.

This corresponds to the commutator model of the salient-pole machine. This approach is useful for studying the un- symmetric behaviour of the synchronous machine. It follows that in the rotor reference frame, under linear conditions, the salient pole machine can be described by a system of voltage equations with constant coefficients and, in general, the only changing quantity is the rotor speed in these equations. Simulink implementation of synchronous machine model.

Mask interface for synchronous machine model in Simulink. Since the model is written for a salient pole synchronous machine, the mask parameters include different values for the rotor resistances and leakage inductances in d and q-axis as well as for the magnetizing inductances. An extra input are the parameters for the field winding.

The current through the equivalent winding of the permanent magnet I f is constant in all mode of operation. Schematic of PM synchronous machine with damper winding. The voltage equations of the PM synchronous machines in dqo rotor reference frame can be derivate from the voltage equation of synchronous machine 2. Schematic of the transformed model of PM synchronous machine in the dqo rotor reference frame.

Simulink model for permanent magnet synchronous machine. The model take into account the iron losses as well as the parameters variation with the operating temperature. The mask interface for this model is presented in Fig. Notice that the operating temperature is an input parameter in the model and there is also the possibility to take the iron losses into account. Mask interface for the permanent magnet synchronous machine in Simulink. The focus is on the modelling of different soft-starter-fed induction machine topologies as well as on the voltage source converters modelling using the switching function concept.

The influence of the load connection is taken into account in both cases. However, only few of them present in details the theory of operation with a 3-phase resistive-inductive load [67] and [73]. Especially the influence of the load connection type and the steady-state analysis are not presented in detail in the literature.

In [70] a comparison for full and half-wave controlled load both for star and delta connection is carried out, unfortunately, the branch delta connection is not treated. An analysis of variable-voltage thyristor controlled induction motors in terms of specific operation modes, harmonic content and performances for a star connected machine is presented in [26]. In [74] is presented a hybrid abc-dqo model for the induction machine, unfortunately this model has a complicated mathematical model and it can be used only for a star connection of the stator windings.

A generalized approach in modelling of the power converters-fed induction machine, which involves a time-domain static network, is presented in [22]. However, the proposed method can only be used for a star or delta-connected machine. Moreover these approaches do not take into account the deep-bar effect, which is present into a large induction machine. At present many wind turbines, up to 2.

Block diagram of directly grid-connected wind turbine. The scheme comprises the wind turbine rotor, linked via a gearbox to a generator, which through an electrical interface is connected to the grid. Research Organization:. Sponsoring Organization:. Product Type:. Publication Date newest to oldest Publication Date oldest to newest Relevance. ETDE Web. The report provides first a quick overview over Matlab issues and then explains the structure of the developed toolbox.

The attention in the report is mainly drawn to the description of the most important mathematical models, which have been developed in the Toolbox. Then, some simulation results using the developed models are shown. Finally, some general conclusions regarding this new developed Toolbox as well as some directions for future work are made.

Publication Type. More Filters. View 1 excerpt. Modeling of the wind turbine with a doubly fed induction generator for grid integration studies. Due to its many advantages such as the improved power quality, high energy efficiency and controllability, etc. General overview and description of the models. The power quality of a low-voltage grid with two wind turbines is investigated. Slow voltage variations as well as transients and harmonics are measured and analysed.

Furthermore, the spectrum of the … Expand. Highly Influential.