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Control Method of the Speed of Ship Genera-tor Set Based on Cloud Computing Technology / Método de controle da velocidade do conjunto

de geradores de navios com base na tecnologia de computação em nuvem

Dong-lin Cai

Marine Engineering Department, Nantong Shipping College, Nantong, 226010, China

Abstract: The control process of speed of ship generator set based on cloud computing is complex. The steady-state behavior in the current control method is bad. The control strategy is relatively complex. In order to improve the effect of the energy-saving control, firstly, this paper analyses the working process of speed of ship generator set detailedly. From the genetic algorithm, the traditional PID control process is improved. Through the well-designed fitness function and genetic operators, we carry out energy-saving control of intelligent control of speed of ship generator set under the cloud computing, making the generator set under the massive cloud computing complete control quickly. The experimental results show that this method has preferable control effect in the cloud computing environment.

Key words: Cloud computing; Speed of ship generator set; ControlMethod

Resumo: O processo de controle da velocidade do conjunto de geradores de navios baseado na computação em nuvem é com-plexo. O comportamento de estado estacionário no método de controle atual é ruim. A estratégia de controle é relativamente complexa. Para melhorar o efeito do controle de poupança de energia, primeiro, este trabalho analisa detalhadamente o proces-so de trabalho da velocidade do conjunto de geradores de navios. A partir do algoritmo genético, o processo de controle PID tradicional é melhorado. Através da função de fitness bem desenvolvida e dos operadores genéticos, realizamos o controle de economia de energia do controle inteligente da velocidade do conjunto de geradores de navios sob a computação em nuvem, tornando o grupo gerador sob o controle total da computação em nuvem, com controle completo rapidamente. Os resultados experimentais mostram que este método tem efeito de controle preferencial no ambiente de computação em nuvem.

Palavras-chave: computação em nuvem; Velocidade do grupo gerador do navio; Método de controle

BOLETIM TECNICO DA PETROBRAS

VOL. 61, 2017Guest Editors: Hao WANG, Min DUANCopyright © 2017, PB PublishingISBN: 978-1-948012-00-3

http://www.pbpublishing.com.br

ISSN:0006-6117 EISSN:1676-6385

433 BOLETIM TECNICO DA PETROBRAS

1. Introduction

Since the emergence of grid-connected wind generation in 1980s, with the development of blades aerodynam-ics, computer technology[1], control technology, gener-

ator technology and new materials, the development of wind power generation technology is very rapid. The unit capac-ity has developed from the initial several kilowatt-class to megawatt-class which enters the wind farms recently. The development of power control mode is from fixed pitch stall control to full paddle blade variable-pitch and variable speed control[2-4]. The operating reliability has increased from 50% in early 1980s to more than 98%. And the wind power gener-ator in the wind farm can realize centralized control and re-mote control. The development space of wind farms is more wide, moving inland from the sea. Developed countries have made remarkable achievements in the development and uti-lization of wind energy. forming a wind mill industry on a vast scale. In October 2001, the global wind power gener-ation installed capacity has breaked 20 thousand MW[5-7]. The new capacity reached 5000MW. Experts predict that the global wind turbine installed capacity will continue to in-crease at an annual rate of more than 25% from 2002. By 2010, the world’s wind turbine installed capacity will break-100GW[8-10].

Wind power generation technology develop towards the direction of increasing single-machine capacity, alleviating the unit volume and improving the efficiency[11-12]. Taking single machine capacity as an example, in the early 1980s, single-machine capacity of commercialized wind turbines mainly is 55k W. From mid-1980s to early1990s, it is mainly 100~450k W. In the middle of and late 1990s, it is mainly 500K W~1MW[13-15]. At present, the large-scale and medi-um-sized units connected to the grid has become the main form of wind power utilization. For reducing the cost per kilowatt, saving the utilization area of wind farms, acceler-ating the construction speed of wind farms, improving the economic benefits of wind power, many wind power manu-facturers are committed to improving single-machine capac-ity, producing the commercial unit whose capacity is greater than 1MW[16-18]. The fixed pitch constant speed wind turbine which enters the wind farm in the mid-1980s mainly solves the problem of synchronization of wind power set and the safety and reliability of operation. The use of ssoft cut-in technology, aerodynamic braking technology, yaw and au-tomatic untwisting technology are the most basic problems of wind generating set in grid connected operation needs to solve[18-20]. The soft cut-in technology adopts the soft cut-in method based on bidirectional thyristor to synchronize and close the asynchronous generator technology. The aerody-namic brake technology refers to 1.5~2.5m part in the tip of the blade, which is designed to the steerable the leaf opex spoiler. When wind turbines need to take off the network and stop[21-23], the leaf opex spoiler can rotate 90 degrees to form the spilling flap according to the control instruction

action, which causes the wind wheel speed to drop rapid-ly. Automatic untwisting technology refers to that when the engine room has been adjusted to 720 degrees in standby state, or has been adjusted to 1080 degrees in the running state[24], The generator cables introduced to the tower from the cabin are in the state of winding engine, then the control-ler will report the fault, and the wind turbine will be shut-down and automatically execute unwrapping. After untwist-ing, the fault signal is eliminated and the controller is reset automatically[25-26]. Because the power output is limited by its performance of the blades, the pitch angle of blade has been fixed during installation. The generator speed is limited by the grid frequency. Therefore, in the allowable range of the wind speed, the control system of fixed pitch wind tur-bine in the running process doesn’t make any control for the change of output energy caused by wind speed. This great-ly simplifies the control technology and the corresponding servodrive technology. So that the fixed pitch wind turbine can be commercialized in a short time. In the early days, the constant speed constant pitch wind turbines are made in Denmark”[27]. This control concept is called “Danish con-cept windmill”.

In 1990s, the reliability of wind turbine is not a problem. The varying oar distance wind turbine began to enter the wind farm. The varying oar distance technology refers to that the blade can rotate around the axis. The constant speed wind turbine with variable pitch can be used to control rotate speed on startup.The power can be controlled on grid-con-nection. The starting ability and power output characteristics of the wind turbine are improved significantly. Because the effect of varying oar distance constant speed wind turbine under the rated wind speed is not ideal. In the mid and late 1990s, A variety of variable speed wind turbine based on power electronics technology began to enter the wind farm. According to the capacity control way of the blades, the variable speed wind turbine includes two types: the variable speed fixed pitch stall control concept unit and the variable speed varying oar distance control concept unit. the develop-ment of variable speed varying oar distance unit is ripe[28]. Many MW class commercial operation units use this con-trol mode, but it requires a costly and complicated propeller pitch angle regulatory system. The variable speed fixed pitch stall control unit is still in the experimental stage. The obvi-ous advantages of this model leave out the propeller pitch angle regulatory system. The stall control mode depends on the distinctive airfoil structure of blade. The molding tech-nology is difficult.

In recent years, with the increasing of requirements large-scale and relevancy in wind power generation technology, the cloud computing technology is introduced to the relevant practical applications. The wind turbine has gradually become the pillar of large power grid in power generation. At the same time, people have more and more requirements on the wind power generator grid connected system with energy saving

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effect. Therefore, it has great value to study and improve the methods for regulating and controlling the wind power sys-tem capacity[29-30]. Experts and scholars have been committed to the research this study. However, due to the great change of the correlation of the cloud computing, the regulation of converter is difficult to maintain stability. It brings great diffi-culties to reasonable regulation. The traditional PID stability control method in the cloud computing environment is dif-ficult to maintain the stability of the converter with taking a long time. The energy saving control method is more compli-cated.

For solving the above problems, first of all this paper analyses the working process of speed of ship generator set detailedly. From the genetic algorithm, the traditional PID control process is improved. Through the well-de-signed fitness function and genetic operators, we carry out energy-saving control of intelligent control of speed of ship generator set under the cloud computing, making the generator set under the massive cloud computing complete control quickly. The experimental results show that this method has preferable control effect in the cloud comput-ing environment.

2. Dynamic Characteristics of Wind Turbine and ItsInfluence on Control System

(1) The control target of wind turbine

From the above analysis, wind turbine systems have strong nonlinear multivariable with many uncertain factors and disturbances. The basic goal of the wind power generation control system is divided into four levels: ensure reliable op-eration, get maximum energy, provide good power quality, prolong the gear set’s life. The control system should achieve the following specific functions:

(1) ensure the stable operation of the system in the work-ing wind speed range.

(2) when the wind speed is low, track the optimal tip speed ratio to achieve maximum wind power capture.

(3) when the wind speed is high, the wind energy cap-ture is limited, keep rated output power of the wind turbine.

(4) reduce torque peak changes caused by gust, reduce the mechanical stress of the wind wheel and the fluctuation of output power.

(5) reduce transient response of power gearing chain.(6) less control cost. The amplitude of input signal should

be limited, for example, the adjustable range of propel-ler pitch angle and varying oar distance rate.

(7) reject the frequency may cause the mechanical reso-nance.

(8) adjust the output power of units, control stability of grid voltage and frequency

(2) Dynamic characteristics of wind generating set

(1) High non-linearityBaez theory assumes that the wind wheel is ideal. It has no wheel boss, but has infinite blades. The air-flow passes through the wind wheel without resis-tance. Supposing that the air flow is uniform when it passes through the swept surface of the whole wind wheel. Air current direction is axial. The max-imum power coefficient of Baez theory is 59.3%. There is a big difference between the wind turbine blades in actually running and assumed condition of Baez theory. The wind wheel is in the wind en-vironment in which the wind speed and wind di-rection is stochastic variable. Blade has tip loss and wake losses, hub losses. The drag coefficient increases and the lift coefficient reduces after the blade stall. These factors affect the distribution of power factor PC curve

(2) Frequent stochastic switching characteristics of vari-able speed wind turbine operating conditionTheoretically, the output power of wind turbine is in-finite. It is a cube function of the wind speed. In fact, due to the limitation of mechanical strength and generator rating, the output power is limited. Variable speed wind turbines are limited with two fundamental limitations: power and barred speed limits. The power curve of wind turbine has great difference with different type and manufacturer of wind turbine. Generally the variable-speed unit is composed of three operating curves. When the wind speed is low, the speed changes with wind speed, keeping the optimal tip speed ratio to achieve max-imum wind energy capture. The propeller pitch an-gle is the optimal value. With the wind speed in-creases, the speed limit is achieved, thereafter, until the maximum torque. The maximum speed is kept stable.

(3) The uncertainty of effective wind speedThe wind wheel is in a three dimensional time-vary-ing wind field environment. Due to different wind speed distribution on the whole rotating plane of wind wheel, and it is affected by turbulence, tower and surface roughness, the wind speed measured by using the anemoscope on top of the cabin is inac-curate. Even if the wind speed measured by the an-emometer is accurate, it is only a little wind speed. So the effective wind speed can not be measured directly.

(4) Many interference factorsThere are many error sources and uncertainties influ-enced the performance of wind turbines. For example, the change of Reynolds number will cause the power error with 5%. The sediment and rain on the leaves can cause 20% power change. Other factors-like the unit aging, atmospheric conditions, grid voltage and fre-

435 BOLETIM TECNICO DA PETROBRAS

quency variation, can cause changes on different de-gree in unit energy conversion process.

(5) The nonlinear and cross coupling characteristics of doubly fed induction generatorThe stator winding of the doubly fed induction gen-erator is directly connected to the electrified wire netting. The rotor winding is connected with the power grid through the AC-DC-AC circle frequency converter. According to the change of speed, wind power generation system regulates the frequency of excitation current, realizing the constant frequency output. Changing the amplitude and phase of the exci-tation current make the independent regulation of ac-tive power reactive power be realized. In this plan, the converter only needs to supply the slip power, which greatly reduces the demand for capacity. It is suitable for the variable speed constant frequency wind gener-ation system .

3. Control Subject Selection of Cloud Computing Tech-nology Wind Turbine Generator

When analyzing the control characteristics of cloud com-puting wind power generation system, the operation mod-el of speed of ship generator set voltage DFIG in steady state condition needs to be analyzed. The DFIG rotor-side parameters in unit are transformed into the stator side pa-rameters, and according to the inertia of the wind power generation, DFIG T equivalent circuit can be expressed in Figure 1.

Us Ur

Us

Us

Rs Ls Lr Rr

Us

jωψ

Figure 1 DFIG T equivalent circuit

Under the voltage stabilization of wind power generator set, the transient computational formula of DFIG is established. The stator voltage equation and the stator flux linkage equa-tion can be expressed as:

( )

( ) ( )

1

1 1

1

+ = + +

= = −

j tU U es sm

j t j tUsm e j es smj

ω θ

ω θ ω θψ ψ

ω

(1)

In the formulas, smU isthe working voltage amplitude of the unit. θ is the stationary phase of the unit. From Figure 1, volt-age and flux linkage equations expression of the unit can be obtained:

= +

= + −

u R is s s dt

u R i jr r r r rdtω ψ

(2)

= + = +

s s s m r

r m s r r

L i L iL i L i

ψψ

(3)

In the formulas, su is the voltage vector of unit. ru is volt-age vector. sR is stator resistance. is rotor resistance. siis the stator current vector. ri is rotor current vector. sψ is the stator flux linkage vector. rψ is the rotor flux linkage vector.

rω is the speed of rotor angle. sL is the lss inductance. rLis the rotor inductance. mL is the mutual inductance of stator and rotor. From formula (2)& formula (3) , the rotor voltage equation is:

( )

( )

= − + +

− −

dU R j L I L Ir r r r r r rdtLm U R I js s s r sLs

ω σ σ

ω ψ(4)

In formula, 21 /= − m s rL L Lσ .Then, formula (1) is lead into formula (4), voltage vector of wind turbine rotor in rest frame is :

( )

( )( )1 +

= − + +

−

r r r r r r r

j tmsm s s

s

dU R j L I L Idt

LsU e R I

Lω θ

ω σ σ(5)

Among them, ( )1 1/= − rs ω ω ω , s is the revolutional slip of the DFIG rotor. From formula (5) , we can see that when the fluctuation of current, in stable condition and ideal grid-volt-age, the relationship between the unit operation slip and volt-age amplitude is direct proportion. Therefore, For ease of the analysis of wind turbines, it is necessary to set the rotor as an open circuit. From the formula (2) and formula (3), we can get:

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= −s ss s

s

d RU

dt Lψ ψ (6)

Supposing when 0=t t , due to high voltage, there is the volt-age ride-through in the generator unit. After the pressure fluc-tuates, 2smU is the grid voltage amplitude. Therefore, from formula (1), we can get:

( )

( )

( ) ( )

1

1 1

01

/2 20

1 1

,

,

+

+ + −

<= − + ≥

j tsm

sj t j t tsm sm sm

Ue t t

jt

U U Ue e e t t

j j

ω θ

ω θ ω θ τ

ωψ

ω ω

(7)

Among them, /= s sL Rτ is the stator time constant.

In the stationary reference frame, when 0≥t t , the stator current is ignored. Then the formula (7) is substituted into the formula (4), when the generator voltage fluctuates abnormally the induced voltage on the rotor is:

( )

[ ( ) ( )( ) ( )1 1 /21

mr

s

j t j t tsm sm sm

LE t

L

sU e s U U e eω θ ω θ τ+ + −

=

− − − (8)

Through the transformation of coordinate system, the rotor speed rotary coordinate system is obtained:

( ) [ ( ) ( )

( ) ( )

1

1 0

2

/2

1r

r

j s tr msm

s

j t j t tsm sm

LE t sU e s

L

U U e e e

ω θ

ω θ ω τ

+

+ −

= − −

−

(9)

From the formula (9), we can see that when high voltage fluc-tuations occur, the control objects of doubly fed induction generatorin the cloud computing environment are: 1. the cur-rent component which takes the slip angle frequency 1sω as the rotation center; 2. component of voltage which takes the rotor speed angular frequency as the rotation center.

4. PID Control Process Design Based on ImprovedAnomaly Algorithm

Considering the cloud computing environment, for the selec-tion of initial parameters of PID controller in general, the wind turbine uses the empirical method to choose it. Due to the strong subjectivity of the selection method, its self-adaption is weak in the case of uncertain wind. Therefore, in order to make the selection of the initial parameters more accurate, this paper selects the initial parameters of the PID controller with the improved genetic algorithm, which is helpful to complete the control of wind turbine reasonably.

4.1. The SelecTion of Three ParameTerS

The control process of the wind turbine is mainly the process of binary coding. This is the encoding for the real value cod-ing. It is suitable for the parameter selection of the control-ler. Among them, three parameters such as voltage Kp, time Ti, electric current Td, have their own figure region, which can indirectly control the length of its binary string. Because the three parameters have agreater freedom, The tandem con-nection between each other can form the corresponding indi-vidual.

4.2. ParameTer conTrol iniTializaTion of Wind Turbine

Genetic algorithm has strong adaptability in the control of wind turbine. But there are some insufficiencies, such as local precocity, maximum drifting and so on. Before the application of genetic algorithm, the stochastic method is used to select the initial population. On this basis, the control parameters Kp, Ti, and Td can be obtained according to the requirements. This can make the original population condition suitable for the level of PID controller parameter preferences, which can effectively prevent the slowness of convergence rate and ear-liness.

4.3. deSign of conTrol fiTneSS funcTion

There will be many different combinations in the process of parameters selection of the PID controller in the wind turbine. There are also differences between the advantages and disad-vantages of these combinations. The fitness function is used to evaluate the difference, and the select direction of population selection can be guided accurately.

Let us output the integral of absolute value of error for evaluating the PID control system:

( )21 2 3( ) ( )= + +∫ uJ e t u t dt tω ω ω (10)

In the formula, e(t) represents the systematic error. u(t) is the output value of the controller. tu is the voltage rise time of wind turbine. ω1，ω2，ω3 are the weights.

When the overshoot occurs in the response, in order to avoid that the regulation target has a large overshoot, the over-shoot can be increased to the fitness function starting punish-ment. The expression is as follows:

( )21 2 4 3( ) ( ) ( )= + + +∫ uJ e t u t dt e t tω ω ω ω (11)

In formulas, 4 ( )e tω is the overshoot of the system.

4.4. deSign of geneTic oPeraTor

(1) selection operator. Not all of the control parameters can be added to the second generation parameters. This is decided by the nature of its own advantages and dis-

437 BOLETIM TECNICO DA PETROBRAS

advantages. In general, only the results of the control parameters with higher fitness can enter the next gener-ation population.

(2) crossover operator. Three segment individual bunch with the difference will appear the cross appearance. Therefore, the subsection single point overlapping method is used to discriminate the new individuals generated after crossover. In case This individual does not satisfy the value range of the parameters, you need to repeat the process and do crossed work again.

(3) mutation operator. The segmented single point individ-ual is used to implement the mutation operation. The form is “0”→“1”，“1”→“0”. Similarly, if the individ-ual after mutation are not in accordance with the value range of three parameters Kp,Ti,Td. The mutation opera-tion steps need to be repeated.

4.5. Procedure of conTrolling The Wind Turbine WiTh geneTic algoriThm

The control parameters of the algorithm are reasonably as-sumed, namely: the population total N, minimum structure parameter Nmix. The distribution probability pc, selection probability pm, then based on these parameters, optimizing control factor of PID controller, PID controller control factor initialization process is shown in Figure 2.

Initialize the population

Calculation of fitness value

Meet the termination conditions

Selection operation

Interlace operation

Mutation operation

The optimal PID initial parameters

Yes

No

Figure 2 Initialise flow chart of PID controller control factor

Genetic algorithm has the characteristics of multi input and less output. The 3 input logic structure is shown in Figure 3.

Figure 3 logic structure of input / output

According as 1( ) ( )=x k e k ， 2 ( ) ( )= ∑x k T e i ，x3(k) = (e(k)( 1))/e k T− − ，we can find:

( )pi

T=K e(k)+T

1 1 2 2 3 3( )

( ) ( ) ( 1)

= + +

+ − −∑

d

z k x x x wT

e i e k e kT

ω ω (12)

By comparison of formula (11) and formula (12),we can find that they are very similar. So it is a powerful synthesis of the genetic algorithm and PID network.

The gradient descent learning algorithm is used to adjust the weighting coefficient of the genetic algorithm, which greatly reduces the deviation between the actual control value and the ideal value. Then the optimal control of wind turbine control system is realized. Among them, the objective func-tion is:

( )2 2( ) ( ) ( )( )2 2

−= =

r k y k e ke k (13)

learning algorithm of Kp, Ti, Td is:

( ) ( ) ∂∆ = −∂p

yK k e k fu

η

( )( ) ( ) (1 ) ( ) ∂∆ = − −

∂∑i pyT k e k k f e ku

η (14)

( )( ) ( ) (1 ) ( ) ( 1) ∂∆ = − − −∂d p

yT k e k k f e k e ku

η

In the formulas, η is the standard factor. f is the propgressing function. Its incoming vector is the value of ω1，ω2，ω3.

5. Simulation Experiment Analysis

This experiment tests the performance of double fed wind power system high voltage control with the proposed design method in the cloud computing environment. The experiment uses Matlab/Simulink to simulate a 2MW Doubly fed wind power system. The parameters of this system are described in Table 1. The contrast analysis method used in the experiment is the traditional control strategy based on grid-connected in-verter.

In experiment, the voltage in the wind turbine is rap-idly increased to 1.08pu, Requ =60 state. The experiment analyzes the effect of the output voltage modulation wave of the system side converter by using the traditional strat-egy and the paper strategy, which can be expressed in Fig-ure 4. The current component and DC busbar voltage of system side converter are described in Figure 5 with two strategies .

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Table 1 ParameTerS of 2mWdouble-fed inducTion generaTor SySTem

Parameter Numerical value Parameter Numerical value

Rated capacity/MW 3 Stator rated voltage/V 543

Number of pole-pairs 3 Winding-linking of stator and rotor Y，y

Stator resistance/pu 0.00543 Turn ratio of stator and rotor 0.54

Stator leakage inductance/pu 0.1297 Rotor resistance/pu 0.00551

Rotor leakage inductance/pu 0.1504 Stator and rotor mutual inductance/pu 3.9538

Moment of inertia time constant /s 3.5

(a) Traditional strategy (b) The strategy of this paper

Figure 4 Side converter output voltage modulation wave

(a) Traditional strategy (b) The strategy of this paper

Figure 5 Side converter current and DC busbar voltage

439 BOLETIM TECNICO DA PETROBRAS

From the comprehensive analysis of the above two figures, the output voltage modulation wave of side converter of wind turbine in the traditional strategy and the strategy of this paper have a high level of stability in the cloud computing environment. Nevertheless, using the strategy of this paper, the output voltage is minimized and the control effect is maximized. At the same time, the reactive current in this strategy can limit the trend of rapid increase of grid voltage and ensure the stability of voltage.

6. Conclusion

First of all, this paper analyses the working process of speed of ship generator set detailedly. From the genetic algorithm, the traditional PID control process is improved. Through the well-designed fitness function and genetic operators, we car-ry out energy-saving control of intelligent control of speed of ship generator set under the cloud computing, making the gen-erator set under the massive cloud computing complete control quickly. The experimental results show that this method has preferable control effect in the cloud computing environment.

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