Comparative Studies on Control Systems for a Two-blade Variablespeed

7/26/2019 Comparative Studies on Control Systems for a Two-blade Variablespeed

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Comparative studies on control systems for a two-blade variable-

speed wind turbine with a speed exclusion zone

Jian Yang a, Dongran Song a ,b, Mi Dong a , *, Sifan Chen b , Libing Zou b, Josep M. Guerrero c

a School of Information Science and Engineering, Central South University, Changsha, PR Chinab China Ming Yang Wind Power Group Co., Ltd., Zhongshan, PR Chinac Department of Energy Technology, Aalborg University, Denmark

a r t i c l e i n f o

Article history:

Received 2 November 2015

Received in revised form

17 March 2016

Accepted 24 April 2016

Keywords:

Two-blade variable speed wind turbine

Control system

Speed exclusion zone

Tower resonance

Power capture

Tower loads

a b s t r a c t

To avoid the coincidence between the tower nature frequency and rotational excitation frequency, a SEZ

(speed exclusion zone) must be built for a two-blade wind turbine with a full rated converter. According

to the literature, two methods of SEZ-crossing could be adopted. However, none of them have been

studied in industrial applications, and their performance remains unclear. Moreover, strategies on power

regulation operation are not covered. To fully investigate them, this paper develops two control systems

for a two-blade WT (wind turbines) with a SEZ. Because control systems play vital roles in determining

the performance of the WT, this paper focuses on comparative studies on their operation strategies and

performance. In these strategies, optimal designs are introduced to improve existing SEZ algorithms.

Moreover, to perform power regulation outside the SEZ, two operation modes are divided in the pro-

posed down power regulation solutions. The developed control systems performance is conrmed by

simulations and eld tests. Two control systems present similar capabilities of power production and

SEZ-bridging. Nevertheless, at the cost of signicantly increased tower loads, one captures 1% more

energy than the other. Overall consideration must be made for the control system selection for a WT with

a SEZ.

2016 Elsevier Ltd. All rights reserved.

1. Introduction

A wind turbine system is a system that converts mechanical

energy obtained from wind into electrical energy through a

generator. It can be categorized by types of generators used, power

control methods, constant- or variable-speed operations, and

methods of interconnection with the grid[1]. To ensure high per-

formance while minimizing costs, new solutions are developed

constantly for WT (wind turbines) (). Fundamental changes have

been addressed, such as continuously variable transmissions [2,3]and new sensing technologies[4,5]. Meanwhile, advanced control

algorithms have been widely studied, such as soft computing

techniques[6,7]and sustainable control[8]. Despite the develop-

ment of good concepts in recent years, engineering and science

challenges still exist.

Modern high power WTs are typically designed in a variable-

speed type, capturing wind energy and reducing the mechanic

loads effectively. However, a wide speed operation region allows

the resonance between rotor rotary frequency and natural fre-

quencies of other structural components. To tackle underlying

problems, some methodologies are applied during the design

phase, including natural characteristic calculations and potential

resonance analyses[9]. Considerations include not only the certain

gap reserved among the natural frequencies of the blades, tower

and driver train but also the avoidance of coincidences among

natural frequencies and external resonance force [10]. It is rec-

ommended that the eigen-frequency of the rotor blade be outsidea 12% range of the rotational frequency of the WT and the lowest

mode frequency of the tower be kept outside ranges dened as

10% of the rotor frequency and 10% of the blade passing fre-

quency [11]. In practical applications, the tower resonance is

dangerous because it results in the vibration of the whole WT set.

For a three-blade WT, it is possible to move the natural frequency

to the region between 1 P and 3 P by redesigning the tower's

thickness and radius. However, this approach does not work for a

two-blade WT because changing the tower's natural frequency to

be lower than 1 P or higher than 2 P will greatly increase the cost.

Therefore, to prevent the WT from operating in the SEZ (speed* Corresponding author.

E-mail address:[email protected](M. Dong).

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j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m/ l o c a t e / e n e r g y

http://dx.doi.org/10.1016/j.energy.2016.04.106

0360-5442/

2016 Elsevier Ltd. All rights reserved.

Energy 109 (2016) 294e309
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exclusion zone), the only feasible way is to redesign the control

system.

Control algorithms for a WT with a SEZ are described inprevious works [12e17]. Among these works, two control ap-

proaches can be distinguished. The rst one, recorded in[12], is

based on the torque control with a conventional lookup table.

The second one, proposed in [13e15], is developed based on a

proportional integral (PI) torque control method. In both of

them, a certain speed region, including the critical speed and its

vicinity, is built up to form the SEZ. Differences between them

are the means of establishing and bridging over the SEZ. The rst

approach is to create an ambiguous function between rotor

speed and generator torque, so that the generator can accelerate

to cross the SEZ, through an unbalanced relation between the

aerodynamic torque and demanded generator torque. The sec-

ond is to gradually adjust the speed reference from one xed

speed boundary to another. Despite the two approaches avail-able, studies about their applications in real wind turbines are

few. As far as we know, only in [16]are different widths of SEZs,

based on the second approach, investigated and validated on a

1.3 kW test rig. In addition, in [17], the rst approach is

employed for the design of a two-bladed WT's control system. In

the wind energy industry, control strategy validation through

eld trials is vital and irreplaceable. Based on eld trials and

related data analysis, for the control approach applied in [17],

two drawbacks are exposed: i) the experimental turbine fails to

cross over the SEZ under certain wind conditions; ii) the power

capture performance is unsatisfactory. Therefore, optimization

techniques must be further investigated. Moreover, the perfor-

mance of available control approaches is not studied in the

literature, which is vital for WT designers and owners to select acontrol system for a WT with a SEZ.

The control strategies discussed above are utilized only to

maximize power production while maintaining the desired rotor

speed and avoiding equipment overloads [18]. Currently, wind

farms are required to play roles similar to those of conventional

power plants in power systems [19]. As a result, WTs are com-

manded to regulate power according to the power set-points set by

central control systems of wind farms. Thus, these WTs must

perform three power generation tasks: power optimization, power

limitation, and power regulation. These three tasks are fullled in a

certain operation region, constrained by the rotor speed. In the case

of a WT without a SEZ, it is necessary only tolimit the rotor speed to

the speed reference by the pitch controller under the power limi-

tation. To date, many studies have focused on generic WTs,

especially those with doubly fed induction generators[20e24]. For

a WT with a SEZ, specic control strategies must be studied, which

are required to perform power generation tasks while maintainingthe rotor speed outside the SEZ. However, there is no literature on

such strategies.

The objective of this work is to perform comparative studies of

control systems for a two-bladed WT with a SEZ. Starting from

available methods, this paper develops two control systems to

perform power generation tasks while bypassing the SEZ. For both of

them, three operation strategies are discussed, including power

optimization, power limitation and power regulation. In such stra-

tegies, optimal designs are introduced to improve existing SEZ al-

gorithms and solve their problems. Moreover, to perform power

regulation outside SEZ, simple yet effective down power regulation

solutions are presented. The control strategies are veried through

simulations and eld tests. Their performance is evaluated according

to International Electro-technical Commission (IEC) standards.

2. Studied two-blade WT

2.1. Basic information

The studied WT is a two-blade 3.0 MW super compact drive

machine. It is manufactured by China Ming Yang Wind Power

Company, and its specications are shown inTable 1.

The WT has a super compact structure, and its main body

consists of two parts: the energy conversion system and its sup-

porting tubular steel tower. The energy conversion system diagram

is shown in Fig. 1, including a blade rotor, a low-ratio gearbox, a

Nomenclature

qset,qm the pitch angle set-point and the measured pitch

angle.

wA,wB,wC,wD four speed points at optimal tip speed section.

wb,wc the lower and upper speed boundaries of the

speed exclusion zone.wo the critical speed of a two-blade wind turbine.

wr p the speed reference of the pitch controller

wr pl,wr ph wr p in low power mode and high power mode

wr t the speed reference of the PI torque controller

wr tl,wr th wr tin low power mode and high power mode

wr m the measured rotor speed

Topt the optimal generator torque

Pset the power command from wind farm controller

Prated,Pm the rated power and the measured electrical power

Pset b the power set-point to the boost converter

controller

Pl the power set-point from the lookup torque

controller

Pl l,Pl h Pl in low power mode and high power mode

PB,PC the power set-points at rotor speedswB and wCPE,PF the upper and lower power limits at the speed

boundarieswband wcPl1,Pl2,Pl3 three power limits at the speed boundarywcPh1,Ph2,Ph3 three power limits at the speed boundarywbttask,tcross time of control system task and set time to cross the

SEZ

Hs,Hm,Hl three hysteresis time

Mx, My, Mz the rolling, nodding and yawing moments

Table 1

Specications of the studied WT.

Parameters Value

Rotor diameter 110 m

Number of rotor blades 2

Rated electrical power 3000 kW

Rotor speed range 6.0e21.0 rpm

Nominal rotor speed 16.2 rpm

Rated wind speed 12.2 m/s

Rotor moment of inertia 1:5 107kg$m2

Generator moment of inertia 2:1 103kg$m2

Gearbox ratio 23.94

Cut-in wind speed 3 m/s

Cut-out wind speed 20 m/s

J. Yang et al. / Energy 109 (2016) 294e309 295


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PMSG (permanent magnet synchronous generator) and a full-scale

power converter (consisting of diode rectiers, DC-Boost con-

verters and grid inverters).

2.2. Characteristic curves of the studied WT

By using the Bladed software application[25], the characteristic

curves of the studied machine are obtained. Curves of the aero-

dynamic power coefcient (Cp) vs. the TSR (tip speed ratio), and

thrust coefcient (Ct) vs. TSR are shown in Fig. 2. Conventionally,

the pitch angle and TSR for maximum Cp acquisition are called the

optimal pitch angle and optimal TSR, respectively. Fig. 2 shows that,

for the studied WT, the maximum Cp is 0.454, and the corre-

sponding optimal pitch angle and optimal TSR are 0 and 10.5,

respectively. Meanwhile, the optimal pitch angle is changing in the

range of1 to 1 along with the TSR variation in the scope of 8e12.

In addition, Ct increases with decreasing pitch angle when the TSR

is a constant. According to[26], tower loads are proportional to the

thrust coefcient. Therefore, to reduce tower loads, it is benecial

to maintain a large pitch angle and a lower TSR.

Fig. 3 shows the Campbell diagram of the studied machine, inwhich the coupled modes are functions of rotor speeds. At a rotor

speed of approximately 10 rpm, the blade passing frequency 2 P

crosses the frequencies of the lowest two tower modes in the sta-

tionary frame. To avoid excessive excitation of these modes, a SEZ must

be set up, which is handled by the control system studied in this work.

2.3. Control system architecture of the studied WT

The control system of a modern WT is usually divided into two

levels: the generator control and the WT control. These two control

levels are characterized by different bandwidths [22]. For the

studied turbine, a unied control architecture is adopted, running a

WT and ensuring energy injection from power converters into the

electricity network at maximum efciency [27]. Fig. 4 illustrates the

architecture, in which a Siemens IPC P320 is the control unit. Based

on the Pronet protocol, the power converter and other major

components are controlled by one unique controller within two

task periods of 250 ms and 10 ms, respectively. With this unied

architecture, relations and constraints among different control

levels becomeclear. Therefore, it turns outto be quite convenient toimplement control algorithms for the WT.

3. Operation strategies of the studied WT

Considering the power generation system, there are three

operation tasks for modern WTs[24]:

Limiting the output power to the rated power for high wind

speeds (power limitation);

Maximizing the powerextracted from the wind for a wide range

of wind speeds (power optimization);

Adjusting both active and reactive powers to set-points ordered

by the wind farm control system (known as power regulationoperation or deloaded operation or de-rating operation).

When these three tasks are executed, the rotor speed must be

maintained in the predened range. Otherwise, the machine would

suffer from overload. For a generic WT with no SEZs, its rotor speed

is controlled within a continuous operation zone limited by the cut-

in speed and the rated speed. However, for a WT with a SEZ, its

rotor speed not only is constrained by the cut-in and rated speeds

but also must be held away from the critical speed. Separatedby the

SEZ, there are two operation zones: a low speed zone and a high

speed zone. Therefore, the existence of the SEZ affects such WTs

power optimization and power regulation operations. For the sake

of simplicity, SEZ-related torque control and pitch control strategies

will be discussed, whereas other controls unaffected by the SEZ are

Fig. 1. Energy conversion system diagram of the studied WT.

Fig. 2. The aerodynamic power coef

cient and thrust coef

cient curves of the studied WT.

J. Yang et al. / Energy 109 (2016) 294e309296


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neglected. For the studied WT, the pitch controller is used to controla hydraulic pitch system and the torque controller is used to control

the DC-Boost converter. The common operation strategies

employed are summarized as follows.

In the power limitation condition, the operation strategy for the

studied WT is mainly in charge of the pitch controller. The rotor

speed is controlled to be the rated value by the pitch controller,

and the generator torque is limited to the rated value by the DC-

Boost converter controller. As illustrated in Fig. 5, the pitch

controller contains three main parts: a PD controller and two

fuzzy logic units. Regarding the PD controller, its input is the

error between the referencewr pand the feedbackwr m, and its

output is the set value of pitch speed to the hydraulic propor-

tional valves. Two fuzzy logic units, FC1 and FC2, are designed

for the pitch bias determination and over-speed problem pre-vention, respectively[28].

In the power optimization condition, the torque controller is

responsible for the optimized operation, and the pitch angle is

maintained at its optimal value by the pitch controller. In this case,

the rotor speed is controlled by the torque controllerdnot only to

track theoptimal TSRoutside theSEZ but also to cross over the SEZ.

In the power regulation condition, the operation strategy re-

quires cooperation between the pitch controller and the torque

controller. According to[24], three control strategies are avail-

able for DFIG WTs with no SEZs. Recall that down power regu-

lation mainly involves the scheduling power and rotor speed

set-points; these control strategies can also be employed by

the control system of PMSG WTs. However, a special down po-

wer strategy must be developed for a WT with a SEZ.

Fig. 3. Campbell diagram of the studied WT.

Fig. 4. Control system architecture of the studied WT.

-

+

m

_r mw

L1 d t Com

FC2

+

+

set

+

-+

+

FC1

_set bP

L2PD

Gain

scheduling

_r pw

Fig. 5. The structure diagram of the pitch controller.



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4. Control systems of the studied WT

As mentioned previously, there are two different control ap-

proaches for a WT with a SEZ in previous works. Based on them,

two control systems (denoted as Control Systems 1 and 2) are

developed for the studied WT. Control System 1 is based specif-

ically on[17], whereas Control System 2 is based on[16]. Mean-

while, optimal techniques are presented to improve conventional

SEZ-crossing methods. Furthermore, power regulation strategies

are proposed to full power output adjustment.

4.1. Control System 1

4.1.1. Structure of Control System 1

The structure of Control System 1 is illustrated in Fig. 6,

including four main parts: the pitch controller, the speed reference

unit, the DC-Boost converter controller and the power set-point

unit.

Based on Fig. 6, the operation strategies are summarized as

follows:

Power limitation strategy: The reference wr p for the pitch

controller is the rated value, and the power set-point Pset b for

the DC-Boost converter controller is calculated based on the full

powerespeed curve andwr m.

Power optimization strategy:The pitch angle is maintained at its

optimal value by the pitch controller, and the rotor speed is

adjusted by the torque control strategy explained as follows.

Power regulation strategy: The down power regulation strategy

is divided into low power mode and high power mode. Both are

determined by the power command Pset from the wind farm

controller and the power division point PE, which corresponds to

the upper power limit at the lower speed boundary of the SEZ.

When Pset> PE, the WT operates in high power mode: wr ptakes

wr ph, which is generated from the high powerespeed curve and

Pset. Meanwhile,Pset b takesPl h, which is derived from the full

powerespeed curve andwr m. WhenPset PE, the WT operates

in low power mode: wr p takes wr pl generated from the low

powerespeed curve and Pset, whereas Pset b takes Pl l derived

from the low powerespeed curve andwr m.

4.1.2. Optimized torque control scheme in Control System 1

The torque control scheme is illustrated in Fig. 7,including three

parts: the power set-point unit, the bias unit, and the DC-Boost

converter controller.

The DC-Boost converter controller controls the generator tor-

que. A PI controller is employed to control the Boost converter

current, the set-point Iset b of which is obtained by dividing the

power set-pointPset b

by the rectier's output voltageUm b

. FC1, a

fuzzy logic unit, is used to decouple the pitch controller and the

torque controller [28]. The power set-point unit determines the

powererotor speed lookup table, which includes normal points

predened according to the WT's aerodynamic data and special

points related to the SEZ. In this work, eight pairs of powererotor

speed points are shown in Table 2. In [17], weprovedthat for a two-

blade WT, proper widths of the SEZ and its neighbouring zones can

be 10%. Here, the SEZ is preset to 9e11 rpm, its two neighbouring

zones are dened as 8.2e9 rpm and 11e11.9 rpm, and the upper

and lower power limits at two speed boundaries of the SEZ are 18%

and 2%, respectively.

To enhance the SEZ-bridging capability under different wind

conditions, a hysteresis technique is presented to replace the pre-

dened powererotor speed points within the SEZ. As illustrated in

Fig. 8, the technique is described as follows: when the rotorspeed isincreased above the lower speed boundarywb(9.0 rpm), the power

set-point Pset b is decreased with a certain rate to the end point

PF(2.0%); when the rotor speed is decreased below the upper speed

boundarywc(11.0 rpm), the power set-point is increased with a

certain rate to the end point PE(18.0%).

4.2. Control System 2

4.2.1. Structure of Control System 2

Similar to Control System 1, Control System 2 also contains four

main parts: the pitch controller, the speed reference unit, the DC-

Boost converter controller and the power set-point unit. Its struc-

ture is illustrated inFig. 9.

Based onFig. 9, the operation strategies for the control system

are as follows:

Power limitation strategy: both speed references of the pitch

controller and the PI torque controller are the rated value. As a

Fig. 6. Structure of Control System 1.



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result, the rotor speed and generator torque are maintained at

their rated value by the pitch controller and the torque

controller, respectively.

Power optimization strategy: the pitch angle is kept at its

optimal value by the pitch controller, and the rotor speed is

controlled by the PI torque control strategy.

Power regulation strategy:wr pof the pitch controller andPset bof the Boost converter controller are derived based on two po-

wer modes as mentioned earlier. When Pset > Ph3, the WToperates in high power mode: wr p takes wr ph, which is

calculated from the high powerespeed curve andPset, andwr ttakeswr th, which is obtained from the full powerespeed curve

and wr m. When Pset Ph3, the WT operates in low power mode:

wr ptakeswr pl, which is calculated from the low powerespeed

curve andPset, whereaswr ttakeswr tl, which is obtained from

the low powerespeed curve and wr m. Meanwhile, Pset b is

derived from the output of the PI torque controller and wr m.

4.2.2. Optimized torque control strategy in Control System 2

The torque control strategy is illustrated in Fig. 10 and also

contains three parts:the power set-point unit, the bias unit, andthe

boost converter controller. The Boost converter controller and the

bias unit are the same as those in Control System 1. The power set-

point unit refers to a PI torque controller and a mode selection unit.

The design of the PI controller is a routine with the assistance of

Bladed. Here, it is worth noting that the controller gains are dened

Fig. 7. The torque control scheme in Control System 1.

Table 2

Powererotor speed lookup table.

Measured value of rotor speed (rpm) Power set-point (100%)

6.0 0.0

8.2 8.0

9.0 18.0

11.0 2.0

11.9 17.0

13.7 35.0

15.0 48.016.2 100.0

Fig. 8. Powererotor speed curve in Control System 1.

1

2

PI torque

controller

Boost

converter

controller

Pitch

controller

1

2

Select mode

1: Low power mode

2: High power mode

3hPsetP

3set hP P _r plw

_r phw

3hPsetP

3set hP P

Low power-

speed curve

High power-

speed curve

Low power-

speed curve

Full power-speed

curve

_r mw

_r tlw

_r thw

_r pw

_r tw

limitT_set bP

limitT

limitT

3hPsetP

3set hP P>

3hPsetP

3set hP P>

Fig. 9. Structure of Control System 2.



7/16

in terms of generator torque with respect to the high speed shaft. Its

parameters are given as kp 8300.0[Nm/(rad/s)], k i1300.0[Nm/

(rad/s)], and the gain scheduling factor is 1.5. In addition, the

optimal generator torqueToptis calculated asTopt kw2r m[29]. For

the studied WT,k 14322[Nm/(rad/s)2].

Calculating the speed reference and torque limits for the PI

torque controller, the mode selection unit is in charge of the SEZ

algorithm. To carry out the comparison to Control System 1, the SEZ

with same range of 9e11 rpm is preset. Based on the PI torque

controller, the powererotor speed characteristic curve of the WT is

shown inFig. 11.

In the mode selection unit, three modes are denedaccording to

the WT's operation in different rotor speed ranges. InFig. 11,three

operation modes, named low speed mode, high speed mode and

SEZ mode, correspond to rotor speed ranges ofwA wb, wcwDand wbwc, respectively. The speed reference wr tand torque limit

Tlimit for the PI torque controller in these modes are calculated by

the algorithm described in pseudo code as follows:

In the pseudo code above, WT_speed_mode_ag is determined

by measured rotor speed wr mand measured electrical power Pm. It

takes one of three valuesdnamely, WT_lowspeed_mode, WT_high

speed_mode and WT_TEZ_mode, based on the location ofwr m in

wAwb, wcwD and wbwc, respectively. Its value changes, when

a mode transition (WT_lowhigh_transition/WT_highlow_transition)

is triggered by the variation of Pm.The mode transition is deter-

mined by the time duration of the compared result between Pm and

the predened power limit. To cross the SEZ under various winds, a

variable transition technique is employed. In this technique, con-

ditions for WT_lowhigh_transition and WT_highlow_transition are

summarized in Table 3. Predened are several parameter-

sdnamely, six power limits (Ph3,Ph2,Ph1,Pl3,Pl2 and Pl1), three hys-

teresis times (Hl,Hm andHs), and a crossing time tcross with two

values. For the studied WT, their values are given inTable 4.

4.3. Assessment of two control systems

As illustrated inFigs. 8 and 11,there are two powererotor speed

characteristic curves for the WT with two control systems. In view

of the WT performance, which is dependent on its powererotor

speed characteristic curve, control systems impacts on the per-

formance in terms of power capture and tower loads can be

assessed.

Considering power capture, the performance of the WT with

Control System 1 is inferior to that with Control System 2. On one

Fig. 10. The torque control scheme in Control System 2.



8/16

side, Control System 2 obtains better TSR-tracking than the Control

System does at four speed points (wA,wb,wcandwD). On the other

side, two optimal tip speed sections (wA wb andwc wD) are

betterhandled by the PI torque control strategy in Control System 2

than by eight powererotorspeed points dened in the lookuptable

of Control System 1. Regarding these two sides, the WT with Con-

trol System 2 would produce more power. However, the evaluation

is established on the static energy balance theory, which is valid

only on the premise that the WT rotor has a small inertia of

moment and the winds change slowly.

Regarding tower loads, the performance of the WT with Control

System 1 outweighs that with Control System 2. This deduction is

based on two aspects. For the rst aspect, tower loads are affected

by the WT's operation points outside the SEZ. According to the

analyses of the resonance problem discussed in[17], tower vibra-

tion amplitude decreases with increasing difference from the crit-

ical speed. Therefore, tower loads can be determined by the degree

by which the rotor speed converges to the critical speed. As illus-

trated inFigs. 8 and 11, Control System 2 possibly operates the WT

at the speed boundary of the SEZ, whereas Control System 1works

in neighbouring zones of the SEZ. In this aspect, Control System 1

produces fewer tower loads than Control System 2. For the second

aspect, tower loads increase with increasing instances of SEZ-

crossing. The crossing instances with Control System 2 are moreabundant than those with Control System 1 because the condition

for SEZ-crossing is easier to satisfy in Control System 2. When the

WT with Control System 1 can operate in neighbouring zones, that

with Control System 2 will work at the speed boundary of the SEZ.

Therefore, the WT with Control System 2 produces more tower

loads than that with Control System 1.

Although a basic assessment has been obtained based on ana-

lyses of the operation principles of two control systems, it is

indispensable to perform a detailed performance comparison

through nonlinear simulations andeld tests, which is important to

give designers the condence to choose a suitable controller for a

WT with a SEZ.

5. Performance comparisons of two control systems

5.1. Comparative study based on simulation

In this section, two works are performed through detailed

simulations with Bladed: control algorithm validation and perfor-

mance evaluation in terms of structure loads and power produc-

tion. To enhance the power capture capability, the control

algorithm in Control System 2 is further improved by adjusting the

optimal pitch angle. The details are as follows: the measured rotor

speed and electrical power are used to examine the TSR, and pitch

angles are adjusted to the optimal value based on the calculated

TSR. The correlation between the optimal pitch and the TSR can be

obtained by checking the Cp curves shown in Fig. 2. Therefore, three

controllers are developed as the external dynamic library.

Controller 1, Controller 2 and Controller 3 refer to control algorithm

1 (in Control System 1), control algorithm 2and updated control

algorithm 2 (in Control System 2), respectively. In view of the fact

that the simulation running time is shorter than the WT's real

operation time, the hysteresis times employed by Controllers 2 and

3 are shortened to 60 s, 10 s and 1 s in simulations.

5.1.1. Validation of the proposed control algorithms

Regarding SEZ-related controls, two operation scenarios, power

optimization operation and power regulation operation, are

considered. To validate the effectiveness of the controllers, 13

simulation tests are implemented, which are preset by the two

scenarios with single point history and 3D turbulent winds. The

single point history winds are set to step winds from 3 to 12 m/s,

and 3D turbulent winds are dened with 6 m/s meanwindspeed of

three typical turbulence intensities (14%, 16%, and 18%). In this

work, for the sake of simplicity, only two representative simulation

results are shown; one is based on the power optimization case,

and the other is the power regulation case with winds of 16% tur-

bulence intensity. Among numerous simulation data obtained from

Bladed, six signals are shown: wind speed, rotor speed, output

electrical power, pitch angle, and nacelle sideeside and foreeaft

accelerations. The simulation results with Controller 1, Controller 2,

and Controller 3 are plotted in black, red and green, respectively.

The simulation results of power optimization are illustrated in

Fig. 12a. It is clear that all three controllers succeed in bridging the

SEZ. However, their differences are obvious. First, the instances of

SEZ-crossing are notthe same. Three instancesoccur for Controllers

2 and 3, whereas there is only one for Controller 1. Second, beforeand after SEZ-crossing, Controllers 2 and 3 maintain rotor speeds

nearer the speed boundaries of the SEZ than Controller 1. Third,

except for several points, the WT's nacelle accelerations with

Controller 1 are slightly smaller than those from other two con-

trollers. These differences impact power capture and tower loads,

which will be numerically presented in the next section.

Table 4

Parameters for the studied WT.

Parameter Hs Hm Hl Ph3 Ph2 Ph1 Pl3 Pl2 Pl1 tl ts

Value 3 s 30 s 300 s 540 kW 440 kW 410 kW 200 kW 325 kW 350 kW 15 s 10 s

Table 3

Transition conditions in variable transition technique.

Transition type Condition Crossing

time (tcross)

WT_lowhigh_transition T(Pm > Ph3) > Hs tsT(P

m> P

h2) > H

m t

lT(Pm > Ph1) > Hl tlWT_highlow_transition T(Pm < Pl3) > Hs ts

T(Pm < Pl2) > Hm tlT(Pm < Pl1) > Hl tl

Fig. 11. Powererotor speed curve in Control System 2.



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In the down power regulation case, the power regulation de-

mand is set to 450 kW before 290 s and increased to 550 kW at

290 s with a ramping rate of 50 kW/s. The simulation results

illustrated inFig. 12b it show that all three controllers succeed in

following power commands while bypassing the SEZ. Four differ-

ences are distinguishable. First, the SEZ-crossing instances are

different. Three instances occur for Controllers 2 and 3, whereas

there is only one for Controller 1. Second, before and after SEZ-

crossing, the rotor speeds with Controllers 2 and 3 are upheld

tightly to the speed boundaries of the SEZ, whereas that with

Controller 1 is locate in the SEZ's neighbouring zones. Third, both

the nacelle foreeaft and sideeside acceleration amplitudes with

Controller 1 are obviously smaller than those with the other two

controllers. Finally, pitch actions behave differently when the

Fig. 12. Simulation results among three controllers: (a) at power optimization case and (b) at deloaded case.



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output power reaches the power demand. These differences have

directimpacts on the WT'sperformance, which will be presentedin

the next section.

5.1.2. Performance comparisons with simulation results

For performance comparisons, three simulation results are

presented. The rst two from the discussed simulation cases are

used for preliminary evaluation. The third is taken for detailed

comparisons, which is obtained from a complete set of simulations

according to the design requirement of the IEC standard[30].

To preliminarily evaluate the WT's performance with different

controllers, the averaging process function provided by Bladed is

used to calculate the averaged power and averaged tower mo-

ments. The numerical results from Fig.12a and b are summarized inTables 5 and 6, respectively. The results of the power optimization

case inTable 5show that the averaged power production is similar

between Controllers 2 and 3, as are the tower moments. Compared

with Controller 2, there is a slight power output increase for

Controller 3. This result proves that only the pitch angles differ in

the two controllers. By comparing the results between Controller 1

and Controllers 2/3, obvious discrepancies are found. Controller 2

increases the averaged power by approximately 1.6% but doubles

the tower Mx moments and increases the My moments by more

than 20%. By checking the results of the deloaded case in Table 6, it

is found that Controllers2 and 3 are similarin producing power and

tower moments. This ts with the fact that the trajectories of rotor

speed and pitch angle inFig. 12b are almost overlapped in the two

controllers. Compared with Controller 1, Controller 2 increases the

poweroutput by more than 3.1% yetincreases the towerMx and My

moments by more than 85% and 22%, respectively. Because pitch

actions under the power regulation operation directly affect the

aerodynamic thrust and thus the tower moments, these compara-

tive results are different from those in Table 5.

In accordance with the IEC standard [30], a complete set of

simulation series is performed to calculate the design loads, which

is essential to evaluate the controller impact on the loads before

carrying out the eld testing. In the simulation series, different

winds are dened based on the analysis of wind resource mea-

surement at the wind farm site where the studied machines are

deployed: the annual average wind speed at hub height is 6.42 m/s,

and the characteristic turbulence intensityat 15 m/sis 12%. Because

the same pitch control algorithms and supervisory control strate-

gies are performed in all three controllers, fatigue loads rather thanextreme loads are mainly affected. Therefore, performance com-

parisons are conducted on fatigue loads and power production.

To understand component loads, the coordinate system for load

outputs should be dened. The coordinate systems of Bladed are

given in theAppendix. With the coordinate systems, the damage

equivalent loads (DELs) are calculated based on the assumption

that the WT's lifetime is 20 years and the press cycle time is

1.0E 08. By using a Wohler exponent of 4 for steel and 10 for the

glass reinforced plastic (GRP), the DELs of four components (steel

blade root, GRP blade root, hub, yaw bearing, and tower bottom)

with Controller 1 are shown inTable 7.By treating its results as the

baseline, the comparative results of Controllers 2/3 are presented in

Fig. 13(the GRP blade root DELs of the three controllers are almost

equal and thus are not included). The comparative results are

summarized as follows:

Tower bottom DELs: the Mx DEL is increased by nearly 60%, and

the My DEL is increased by more than 10%. Other DELs: no signicant change is found; that is, only the

increments of the My DELs of the blade roots reach 5%, whereas

the others are less than 3.5%.

By comparing the DELs between Controllers 2 and 3, it is found

that the related DELs are very similar to each other. Only an

increment of 2% for the Mz DEL of the blade root is produced by

Controller 3, whereas other differences are less than 1%. The

optimal pitch angle adjustment applied to Controller 3 accounts for

the increased Mz DEL of the blade root.

To observe the contributions of different wind speeds to the

tower's DELs, the towerbottom Mx and My DELs of design load case

(DLC) 1.2 are shown inFig. 14. At wind speeds of 4 m/s and 6 m/s,

the tower bottom Mx and My DELs with Controllers 2 and 3 almostdouble those with Controller 1. The reason is that the rotor speeds

with Controllers 2 and 3 at low winds are limited to the speed

boundaries of the SEZ. At wind speeds of 8 m/s and 10 m/s, the

tower bottom Mx DELs of the three controllers are almost equal,

whereas the tower bottom My DELs of Controllers 2 and 3 are

higher. This is because the rotor speeds with the other two con-

trollers have reached the rated speed, but that with Controller 1 has

not. Therefore, a largerthrust is produced by higher TSRs. Above the

rated winds, slight differences among towerDELs are shown, which

are affected by torque demand differences in turbulent winds.

Based on the simulation results of DLC 1.2, the averaged power

at different wind speeds is calculated. As shown in Fig. 15, results

from Controllers 2 and 3 are compared with the baselinedthat is,

the result of Controller 1. It is clear that different averaged power isproduced by the three controllers. Compared with Controller 1, the

other two controllers increase the power production at wind

speeds of 8 m/s, 10 m/s and 12 m/s but decrease the power pro-

duction at other wind speeds. The increased power production at

medium wind speed is caused by the optimal TSR tracked by these

two controllers. The decreased power production by less than 0.3%

above the rated winds can be explained by the power loss model,

which is determined by the rotor speed and generated power. The

lower power production at 4 m/s and 6 m/s seems to contradict the

results shown inTable 5. However, it is reasonable when consid-

ering the inuence of different turbulence intensities.

Toassess the overall power production performance of the three

controllers, the AEP (annual energy production) is calculated based

on the averaged powerat DLC 1.2 andthe wind characteristic on the

Table 6

Summarized numerical results fromFig. 12b.

Controller Mx (MNm) My (MNm) Mz (MNm) Averaged power (MW)

1 4.723 9.115 0.805 0.381

2 8.640 10.880 0.973 0.393

3 8.592 10.812 0.972 0.393

Table 7

The DELs of four components with SN4.

Component Mx (kNm) My (kNm) Mz (kNm)

Blade root (steel) 5640.79 2281.65 57.40

Blade root (GRP) 5591.17 4204.39 68.64

Hub (steel) 393.36 2491.80 2491.84

Yaw bearing (steel) 452.34 2472.33 2482.58

Tower bottom (steel) 5003.96 9983.03 2482.45

Table 5

Summarized numerical results fromFig. 12a.

Controller Mx (MNm) My (MNm) Mz (MNm) Averaged power (MW)

1 3.757 7.298 1.103 0.502

2 7.413 8.917 1.066 0.509

3 7.361 8.899 1.066 0.510



11/16

wind farm site. The AEPwith Controller 1 is 6716.47 MWh, whereas

that of Controllers 2 and 3 is slightly higher with results of

6762.78 MWh and 6764.19 MWh, respectively. Thus, there is a 0.7%

difference in AEP, which must pay for a 10% increase in the tower

bottom DELs.

5.2. Comparative study througheld tests

After validation through simulations, the control algorithms are

transferred into the programmable logic controller (PLC) program

and then integrated into the control systems of the studied WT. The

eld testing site is located in a wind farm on the coast of southern

China, inwhich there are ten 3 MWtwo-blade WTs and seven 2 MW

three-blade WTs. Before thetesting, thecontrol systems of the3 MW

WTs employ the lookup table torque control algorithm. To carry out

eldtests, twoof theten machines, named N15 andN16,are chosenas

testing objectives because their locations and their power production

performance arequite similar. Control System1 is used toupdate N16,

and Control System 2 is tested on N15. Because Controller 3 produces

more powerthan Controller 2 in simulations, its updated algorithm is

adopted in Control System 2 for testing. The eld tests were carried

out in June 2015 for a duration of three weeks.

Fig. 13. DEL comparisons of four components among three controllers.

Fig. 14. Comparisons of tower bottom Mx and My DELs at DLC 1.2 among three controllers.

Fig. 15. Averaged electrical power comparison at DLC 1.2 among three controllers.



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5.2.1. Field testing results

In the eld testing, the control systems are tested in different

wind conditions under normal grid operations. Although power

regulation strategy is developed in the control system, this function

is inactivatedduring the tests because in that wind farm, there is no

such requirement to date.

Because different SEZ algorithms are employed by two control

systems, the results of SEZ-crossing recorded in a 10 ms period are

shown inFig. 16a and b.

It can be observed that when the SEZ is crossed over, the output

power varies signicantly. The peaks of the output power are

750 kW and 540 kW for N15 and N16, respectively. Meanwhile, the

crossovers of the SEZ occur at different wind speeds: near 5.5 m/s

for N15 and 4.5 m/s for N16. In addition, both nacelle foreeaft and

sideeside accelerations increase with more transitions between

two speed zones. The different acceleration amplitudes could be

the results of varying winds experienced by the whole rotor.

To further illustrate the different behaviour of the two control

systems, another eld testing result recorded for one day (24 h) is

presented in Fig. 17. Because the result is with a 10 s sampling

period, nacelle acceleration signals are excluded. It is very clear

that the rotor speed trajectories and SEZ-crossing instances are

different for N15 and N16, whereas wind conditions are surpris-

ingly similar.

Fig. 16. Cross over curves of SEZ on eld testing for: (a) N15 with Control System 2 and (b) N16 with Control System 1.



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5.2.2. Statistics analysis ofeld testing data

Because load measurement devices are not equipped in testing

WTs, only power performance evaluation is conducted by referring

to the IEC standard[31]. The data collection is performed between

10 July and 10 August and recorded with 10 min averaged values.

Four measurable data points (wind speed, rotor speed, output po-

wer, and pitch angle) are collected and form a valid dataset after

removing corrupted data. Based on the valid dataset, 10 min aver-

aged TSRs are computed from the instantaneous TSRs calculated at

each sampling point from the measured wind and rotor speeds.

Four characteristic curves of N15 and N16, including rotor speed

wind speed, pitch angleewind speed, TSRewind speed, and pow-

erewind speed, are illustrated inFig. 18. The former three charac-

teristic curves are quite different, whereas the powerewind speed

curvesare similar. This shows that one obvious SEZranges from 9 to

11 rpm, and the pitch angle of N16 is maintained at 3, whereas the

pitch angle of N15 varies in the area of 2e4. For the testing WTs,

the pitch angle of 3 is the optimal pitch angle (the same as the

0 illustrated in Fig. 2). TSRs of N15 are maintained near the optimal

value of 10.5 in the wind speed range of 4e

5 m/s and 7e

9 m/s,

whereas N16's TSRs are not constant in the whole wind speed

range. Meanwhile, TSRs of N15 and N16 are distributed in different

Fig. 17. Field testing curves on one typical day (black curves for N15 and red curves for N16). (For interpretation of the references to color in thisgure legend, the reader is referred

to the web version of this article.)

Fig. 18. Characteristic curve comparisons between N15 and N16.



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ranges. The TSRs of N15 are scattered between 9.0 and 11.5 at low

winds of 4e5 m/s and between 9.8 and 11.2 at high winds of

7e9 m/s. By comparison, the TSRs of N16 are more concentrated. It

means that the dynamic tracking TSR capability of N15 with Control

System 2 is inferior to that of N16.

To numerically compare the power capture performance of thetwo control systems, the averaged output power of N15 and N16

are calculated. By setting the averaged power of Control System 1

as the baseline, comparative results are shown in Fig. 19. It is

obvious that N15 outputs more power below rated winds except at

the wind speed of 7 m/s. This result is consistent with the

TSRewind speed characteristic curve (shown inFig. 18): at a 7 m/s

wind speed, the TSRs of N15 and N16 are near the optimal value of

10.5, whereas those of N16 are much denser. Compared with the

simulation results, more power is obviously produced by N15 in

the low wind range (3e5 m/s), whereas the power increasing

trend is similar in the high wind range (8e12 m/s). These differ-

ences can be explained by different time lengths and the inuence

of different turbulence, especially in low winds. Again, AEPs of N15

and N16 are calculated based on the

eld testing results, which are5763.1 MWh and 5695.8 MWh, respectively. It is proved that N15

with Control System 2 produces more power than N16 with

Control System 1. However, the AEP obtained from eld testing

results is less, approximately 15%, than that obtained by simula-

tion, for which the possible reasons could be the wake loss and

model tolerance.

6. Conclusions

This paper presents a comparative study on two control systems

for a two-blade WT with a SEZ, which is built to avoid tower

resonance. The SEZ of the studied WT is set up and bridged by an

appropriate torque control, performed through a Boost converter

controller at power optimization operation in collaboration withthe blade pitch control at power regulation operation.

In this paper, two control systems (Control Systems 1 and 2)

are developed based on existing torque control strategies, in which

three operation strategies have been performed. At power opti-

mization operation, Control System 1 employs a conventional

lookup table torque control strategy, whereas Control System 2

uses a PI torque controller. To guarantee successful SEZ-crossing

under different wind conditions, a hysteresis technique and a

variable transition technique are performed in Control Systems 1

and 2, respectively. For power limitation operation, the two con-

trol systems use the same pitch angle controller. Regarding both

the power regulation and the SEZ to be handled at deloaded

operation, two power operation modes are divided based on the

comparative result between the upper power limit of the SEZ and

the power regulation command. In this way, the WT operates in

the low speed range with low power command and in the full

speed range with high power command. As a result, the WT can

produce maximal power while maintaining its rotor speed outside

the SEZ.

Based on analyses of their operation principles, the impact of

control systems on theWT performanceis assessed:Control System

2 would produce more power at the cost of increased tower loads

compared with Control System 1. The assessment is further veried

through simulations and eld tests. For general operation cases

without down power regulation, detailed simulation tests are ful-

lled according to the design requirement of IEC-64100. The simu-

lation results illustrate the capability of developed control systems

to perform the discussed tasks. Meanwhile, the simulation results

show that, onthe onehand, fatigueloads causedby Control System2

are surely larger than those of Control System 1: increased DELs on

other components are less than 6%, but raised tower DELs are sig-

nicant, representing more than a 60% improvement and 10% in-

crease for tower Mx DEL and My DEL, respectively; on the other

hand,0.7% greaterpowerproduction is obtained by ControlSystem 2compared with Control System 1. The detailed numerical results

have shown that the increased DELs are mainly contributed by a

wind speed range corresponding to the SEZ. Following the simula-

tion tests, eld testing is implemented to validate the control sys-

tems and compare power production performance. Theeld testing

results show that both control systems arecapableof controlling the

WT to build up and cross over the SEZ. Again, it has been demon-

strated that energy capture performance is enhanced by Control

System 2. According to a comparison of the results between simu-

lations, an increased AEP of 1.1% is achieved by Control System 2.

The simulation results also reveal that, at power regulation

operation, Control System 2 produces more power than Control

System 1 at the cost of increased tower loads. However, in this

circumstance, there is a risk of frequent SEZ-crossings when thepower regulation command is switched between high power and

low power modes. Therefore, the WT would suffer from high tower

loads. In this case, it is necessary to design a proper wind farm

controller to send proper power commands to each WT with the

SEZ. Meanwhile, deliberate evaluation strategies are necessary to

carry out thorough comparisons because no applicable evaluation

standard is available to follow. These aspects would be the subject

of future publications.

Acknowledgements

This work is supported by the National Natural Science Foun-

dation of China under Grant 61573384 and the National High

Technology Research and Development Program (863 Program) ofChina under Grant 2015AA050604. This work is also nancially

supported by the Project of Innovation-driven Plan in Central South

University, No. 2015CX007 and the Fundamental Research Funds

for the Central Universities of Central South University under Grant

2015zzts050.

Appendix

The coordinate systems for load outputs in this study are

dened by Bladed. They are based on the GL convention and are

shown in following gures.

Fig. 19. Averaged output power comparison between N15 and N16.



15/16

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Fig. 20. Coordinate systems for load outputs.

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