Comparative investigation and improvement of wind farms based on wind energy conversion and grid connection methods

Georgios A. Adamidis DEMOCRITUS UNIVERSITY OF THRACE

University Campus Kimmeria, 67100 Xanthi, Greece

adamidis@ee.duth.gr

Thomas G. Nathenas DEMOCRITUS UNIVERSITY OF THRACE

University Campus Kimmeria, 67100 Xanthi, Greece

tnathena@ee.duth.gr

Athanasios D. Karlis DEMOCRITUS UNIVERSITY OF THRACE

University Campus Kimmeria, 67100 Xanthi, Greece

Tel/Fax: ++30/25410-79722 akarlis@ee.duth.gr

Keywords Fuzzy logic control, Windgenerator Systems, Multilevel converters

Abstract In this paper two different conversion systems of wind energy into electricity are investigated. In the first system studied the wind turbine is connected to a three phase diode rectifier. At the output of the non-controlled rectifier a DC/DC boost converter is connected. Controlling the switching pattern for the DC/DC converter the maximum power point tracking (MPPT) is achieved. In the second system the wind turbine is connected to a three-level rectifier consisting of IGBTs switches. The three-level rectifier is triggered with the space vector modulation method (SVPWM). The maximum power is achieved through and algorithm which modifies the switching pattern. On the grid side a three level inverter is connected. The controllers applied to both systems are fuzzy controllers. For the study of these two systems Matlab/ Simulink was used in steady state and transient response.

Introduction The energy conversion system which was used consists of a variable speed wind turbine with a permanent magnet synchronous generator (PMSG), with nominal power of 1.5 ΜW. During the last years, a rising interest in non-contaminating energy sources has emerged from the industrial and academic communities. Major renewable energy sources (RES), i.e. wind and solar, are today economically feasible alternatives to conventional electric power generation. Among the various factors contributing to this success are the development of new power electronics technologies, new circuit topologies and novel control strategies [1]. The research effort around wind energy conversion systems (WECS) is intense during the last years. Two are the main systems used. The first one applies an induction motor and the second one a PMSG [2], [3]. In case of the induction motor the required control system is complex [4]. On

the other hand in case of the PMSG simpler control systems can be applied. Many research efforts deal with WECS composed of PMSG, rectifier and inverter [5] although, the last can increase the cost of the system. Another disadvantage of this setup is the complex MPPT algorithm needed to trigger the rectifier properly [6]. As a result, simpler WECS tend to be used. The system “PMSG-diode rectifier-DC boost converter-inverter” is used due to its simpler MPPT control and decreased cost [7]. Many MPPT control algorithms have been investigated as well. They are divided into two types. According to the first one, the wind turbine characteristics are known. The second one appears to be more flexible, as it is able to ignore the change of the wind turbine characteristics due to mechanical aging. Perturbation and observation (P&O) method is widely used in capturing the MPPT operation without knowing the wind turbine characteristic [8]. Many efforts have been made in the control of these systems (WECS). The conventional PI controller is replaced by the Fuzzy Logic Controller (FLC). The FLC outweighs the PI controller in transient response and in the overall robustness of the system [9]. Multilevel inverter is used as interface with the ac power grid due to their advantages for good quality output signals. The triggering method for those inverters can be chosed between SPWM and SVPWM. The latter appears as a better solution [10]. This work presents a full detailed modeling and a novel control scheme of a three-phase grid connected wind energy conversion system. The control algorithms incorporate a maximum power point tracker (MPPT) for optimal active power generation. The WECS model consists of a variable speed wind turbine and the MPPT is implemented via a step-up DC/DC converter. The output voltage of a permanent magnet generator is connected to a fixed dc-link through a three-phase rectifier and the DC/DC converter. A three level voltage source inverter (VSI) is used to convert the energy produced by wind turbines into useful electricity and to provide requirements for power grid interconnection. The switching pattern generation for the VSI is achieved using SVM [12] and a neutral point balancing algorithm is applied in order to stabilize the neutral point potential. Moreover, the VSI meets all the constraints of high quality electric power, flexibility and reliability imposed for applications of modern distributed energy resources (DER).

Fuzzy Logic Current Controller In order to overcome the drawbacks of the PI controller for the current control, a fuzzy logic controller is applied. Fig. 1 shows the internal structure of the proposed fuzzy logic current controller. Inverter current error e(n)=i*(n)-i(n) and the difference of the error Δe(n) at the nth sampling instant are used as inputs for the fuzzy processing. The output of the fuzzy controller is considered as the amplitude of the reference voltage (V). The fuzzy controller of Fig. 1 will be applied both on d and q axis. Thus, on d-axis input is ids and ids* and output is related to Vds*. The same procedure is applied on q-axis. Throughout this subsection i and V will be referred as input and output respectively, for the sake of simplicity. Input and output are used as numerical variables from the real system. To convert these numerical quantities into linguistic variables seven membership functions are used for each input and nine membership functions are used for output. The following seven fuzzy sets are chosen for each input: NB (negative big), NM (negative medium), NS (negative small), ZE (zero), PS (positive small), PM (positive medium) and PB (positive big). For the output, nine fuzzy sets are chosen: NB (negative big), NM (negative medium), NS (negative small), NVS (negative very small), ZE (zero), PVS (positive very small), PS (positive small), PM (positive medium) and PB (positive big). Fig. 2 shows the normalized triangular membership functions for input (i) and output (V). To determine the shape of the membership function for each fuzzy set the knowledge and the experience of an expert is required.

i) Seven fuzzy sets are used for e(n) and Δe(n). ii) Nine fuzzy sets are used for V(n). iii) Fuzzification using continuous universe of discourse. iv) Defuzzification using the “centroid” method. v) Mamdani’s minimum fuzzy implication. vi) Triangular membership functions.

The fuzzy controller is characterized as follows: Fuzzy logic controller consists of a set of simple linguistic rules to determine the control procedure. The linguistic rules associate the pair “error” and the “difference of the error” with the output “reference voltage”. Fuzzy rules are summarized in Table I. All fuzzy rules assume the simple IF-THEN form: IF e(n) is Ai and Δe(n) is Bj THEN ΔV is Oij where Ai, Bj and Oij are fuzzy sets that represent the specific fuzzy values of e(n), Δe(n) and ΔV(n). Fig. 3 illustrates the fuzzy logic surface. The fuzzy surface is the output plotted against the two inputs. It is an interpolation of the effect of the 49 rules of Table I.

Fig. 1: Internal structure of the fuzzy logic current controller.

a) b) Fig. 2: Membership functions for a) input and b) output variables.

Fig. 3: Fuzzy logic surface.

Table I. Fuzzy rules

e(pu)

Δe(pu) NB NM NS ZE PS PM PB

NB NB NB NB NM NS NVS ZE

NM NB NB NM NS NVS ZE PVS

NS NB NM NS NVS ZE PVS PS

ZE NM NS NVS ZE PVS PS PM

PS NS NVS ZE PVS PS PM PB

PM NVS ZE PVS PS PM PB PB

PΒ ZE PVS PS PM PB PB PB

Investigation of the variable speed wind turbine system With diode rectifier, DC-DC converter, inverter and grid connection In this case the three-phase output voltage of the generator is rectified by a three-phase diode rectifier. Then the rectified voltage is applied o a boost converter (DC/DC Boost Converter). With the boost converter and the control circuit the control of the output current of the rectifier and hence of the current of the generator and of the torque is achieved. Alongside, the boost converter operates as interface of the voltage of the generator, which varies with the wind speed, and the DC voltage applied to the input of the grid connected inverter. The three level voltage source inverter (Voltage Source Inverter VSI) aims to transfer power from the wind turbine to the grid. Fig. 4 shows the electric power system under investigation. The DC/DC converter is controlled taking into consideration the algorithm of the MPPT through small output power changes. At any time the voltage Vdc and the current Idc at the entrance of the boost converter are measured and active power, Pt is calculated. The value Pt is compared with the previous P (t-1). In case the power Pt is greater than the P (t-1) then the sign ΔD remains the same and is simply added (duty Cycle in the time t) to Dt and the procedure is repeated. Otherwise, if the power Pt is lower than the P(t-1) the ΔD changes sign. In any case, if the value Dt takes maximum or minimum value, Dmax and Dmin, respectively, the sign of ΔD will still be completed.

Fig. 4: Wind energy system with rectifier, DC-DC converter and the control system.

(1)

Equation (1) is the rule for the change of the Dt where Dt and Dt-1 are the values of the duty cycle for iterations t and t-1, respectively (where 0<Dt<1). The ΔPt−1/ΔDt−1 is the slope of the output power for the iteration t-1and C1 is a constant which represents the step change.

With controlled three level rectifier, inverter and grid connection Figure 5 shows a three-level rectifier connected to the grid via a three level inverter. This system consists of the Wind Turbine (WT) in association with the three-level rectifier. The three-level rectifier is a neutral point clamped converter. Fig. 5 shows the block diagram under investigation. In the investigated system we will implement a simple method for maximum power point tracking. This method does not require calculations of speed and density of the wind or the characteristics of the WT. The proposed algorithm requires the

Grid

calculation of the instantaneous real power and speed of the generator which are accepted as input data and produces the optimal speed reference output. This velocity vector is sent to the control of the generator for the system to operate at the maximum power point. Specifically, its operation is based on the well known method called "Hill Climbing Algorithm". According to this, in each step the slope of the power curve is calculated and depending on its sign the desired change in the rotational speed of the generator is implemented.

Fig. 5: Wind energy system with three level converter and the control system.

Simulation results In Table II the parameters of the simulated system are presented: Table II. System Parameters Nominal Power 1.5MW Nominal generator voltage 460V

Nominal generator current 1883A Nominal generator speed 1650rpm

(173rad/s)

Nominal wind speed 13m/s Poles number 8

Moment of Inertia 156.8kgm2 DC link voltage 1000

Transmission Gear ratio 1:50 Capacitors 300mF

d-axis induction 0.514mH q-axis induction 0.186mH

Nominal frequency 110Hz Stator resistance 0.514mΩ

During the simulation process the electrical quantities for both systems in Figs 4 and 5 are investigated. For the switching pattern generation the d-q reference frame was used, as illustrated in figure 4 and 5. From the simulation process of energy systems in Figs 4 and 5 a lot of waveforms were received both in transient and steady state. These waveforms project the electromechanical quantities in the wind turbine and grid side. In figure 6 and 7 selected waveforms which analyze the performance of the system in transient and steady state are illustrated. Initially consider that the wind turbine operates with wind speed is 10 m/s. At time t=2 sec we consider that the wind speed changes in 12 m/s. At 10 m/s wind speed the speed of the above mentioned wind turbine is 500 rpm while at 12 m/s it is 700 rpm. Figs 6.a and 7.a show the torque of the wind turbine and Figs 6.b and 7.b present the phase current of the

Rotor speed estimation

generator during the transient phenomenon, i.e. in the time interval when the speed of Wind varies from 10 m/s to 12 m/s for the two power system setups. At this point, it is worth noting that the change in wind speed of 10 m/s to 12 m/s caused smooth change of torque and current nf the wind turbine. This is due to the fuzzy logic controllers presented above.

a)

a)

b)

b)

Fig. 6: Wind generator a) electromagnetic torque, b) phase-a current of the system presented in Fig. 4.

Fig. 7: Wind generator a) electromagnetic torque, b) phase-a current of the system presented in Fig. 5.

Figures 8.a and 9.a illustrate phase-a current waveform for the generator of the conversion system in Figs 4 and 5 respectively when the wind speed is 10 m/s which means that the wind generator speed is 500 rpm. Figs 8.b and 9.b illustrate the THD of the currents for each of the above systems. From the comparison of the two systems is clear that the THD of the system in Fig 5 is lower than that of the system in Fig 4.

a. a.

b.

b. Fig. 8: a) currents in phase-a, b) THD of the current in system presented in Fig. 4

Fig. 9: a) currents in phase-a, b) THD of the current in system presented in Fig. 5

Operation of the grid side converter The block diagrams of the control systems of Figs 4 and 5, for grid connection are investigated. The power electronic device used for the grid connection is a three level converter. For the grid inverter control the switching pattern generation is based on a fuzzy logic controller. During the wind speed change the phase and line to line voltages remain unchanged. However the amplitude of the line currents is increased based on the transferred active power. In Figs 10.a.1 and 10.a.2 the waveforms of the phase currents and line to line voltage Vab respectively are presented. These quantities are measured on the converter output, before the coupling filter on the grid side (see Figs. 4 and 5). The waveforms were taken during the transient phenomenon of the wind speed step change from 10 m/s to 12 m/s. In this case the converter output current ia is changed from 1000A to 1500A, while the amplitude of the line to line voltage remains the same. Figs 10.b.1 and 10.b.2 present the harmonic analyses and the total harmonic distortions of the current ia and line to line voltage Vab respectively, before the coupling filter. It is obvious from the results that, in the case of a 3-level converter controlled with the help of a fuzzy logic controller, the electrical quantities are much better compared to the ones taken from a 2-level converter.

a. b.

c. d. Fig. 10: Electrical quantities at the output of the inverter, before the coupling filter: a) phase currents, b) line to line voltage Vab, c)THD of phase current ia, d) THD of the line to line voltage Vab.

Conclusion In this paper two different conversion systems of wind energy into electricity with pertinent MPPT were investigated. With the help of the software package Matlab/Simulink the performance of the two systems both in steady state and transient response were studied. The originality of this work is that in both systems studied, all the controllers were designed with the help of fuzzy logic and demonstrated better performance during transitional response. As a result of the investigation of the two systems, both in the steady state and the transient response, the power conversion system with diode rectifier in the three-phase synchronous machine side the currents have high harmonic distortion compared with the system equipped with a controlled three level rectifier. Furthermore, from the investigation of the grid side converter, it was concluded that the voltages and currents present low distortion. It must be also pointed out that for the investigation of the system a new PWM method for the three-level converter was used.

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