Criticality Analysis of Wind Turbine System Components using Cost Importance Measure

International Journal of Engineering, Management & Sciences (IJEMS) ISSN-2348 –3733, Volume-2, Issue-5, May 2015

Criticality Analysis of Wind Turbine System Components using Cost Importance Measure Urvashi Chauhan, G.L. Pahuja, Vijander Singh, Asha Rani 

II. IMPORTANCE MEASURE

Abstract— Importance measure analysis is used to identify the critical components in the system which have the greatest impact on the system performance. Various importance measures are already proposed such as Birnbaum, Fussell Vesely, reliability achievement worth etc. which facilitates prioritization of system components for making maintenance strategy and reliability improvement. Only few existing importance measures have paid attention to the costs incurred by maintaining system components within a given time period.

This paper proposes a new component cost important measure and approach is applied on wind turbine system. Component having highest importance measure value is considered to be most critical component in the system.

There may be various component present in any system.

Some of those components are more important for system reliability/ maintainability and risk point of view than other components. Importance measure identify the criticality of components and gives ranking to them accordingly. Most critical component is assigned rank first and least critical is assigned the last rank. Priority of need of maintenance of component have been decided according to their rank[7,8].

Firstly ranked component need more attention in developing the reliability and maintenance strategy.

Index Terms — Electrical energy,renewable energy resources, wind turbine, component of wind turbine,cost importance measure, partial derivative

III. COST IMPORTANCE MEASURE We can prioritize the maintenance planning with the help of importance measure. Hence reliability of the system can be improved giving increased operating period. The classical measures like Birnbaum importance do not take component cost consideration. In practical application it is true that the effect of economical parameter need to be considered while designing and maintaining the components of any physical system. Because of this one can reduce the cost of maintaining the component of system and also cost of designing of system hence increase in the system reliability [9]. According to Rausand and Hoyland the importance of a component should depend on the following factors [10]:

I. INTRODUCTION Due to reduction in non renewable energy resources like coal, the requirement of renewable energy resources is rapidly increasing. Many renewable sources provide clean energy. Wind is one of the most important renewable energy resources. Wind turbine (WT) system generates energy using wind. Lots of research is going on to improve the wind turbine system efficiency. The cost importance measure (CIM) of wind turbine system is important.

In the literature various importance measures have been proposed like Birnboum importance [4, 6], Fussell-Vesely (FV) importance [1, 3], structure importance, risk reduction (RR), differential importance [2, 5] etc. but these do not consider cost issue that provides the strategy to maintain the system and to increase the system reliability. Attention of cost importance measure of component also helps us to improve the system performance. In this paper partial derivative (PD) importance measure is used to calculate the cost importance measure (IM) of turbine system.

 Component reliability of component  Component location in the system.

A. Definition of CIM CIM can be used to describe the efficiency of maintenance cost each component in the system which will be useful to making design and maintenance strategy for the system.

Mathematically Cost importance measure can be defined as:

PD  xi  CIM = Manuscript received February 20, 2015 Urvashi Chauhan, ICE Division ,Netaji Subhas Institute of Technology, Delhi University, New Delhi, India, Dr. G.L. Pahuja,EE Department, NIT Kurukshetra, Kurukshetra, India, (e-mail: pahuja.gl@gmail.com).

Dr. Vijender Singh, ICE Division ,Netaji Subhas Institute of Technology, Delhi University, New Delhi, India , Dr Asha Rani, ICE Division ,Netaji Subhas Institute of Technology, Delhi University, New Delhi, India

ci'  xi 

n

 c x  k 1

Where I,

PD  xk  ' k

(1)

k

xi be the mean failure probability of component

ci  xi  is the cost function, ci is derivable. Following

three conditions are considered for

ci that ci is positive

definite function, non-increasing, and rapidly increases as

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Criticality Analysis of Wind Turbine System Components Using Cost Importance Measure mean failure probability gets close to (1). Where PD is partial derivative IM and is defined as:

 

R xi xi

 

PD xi 

(2)

CIM is additive. Let there be number of subset of parameter xi , x j .....x p .Then CIM may be define as follows:





CIM xi , x j .....x p 



   

   

PD x j PD xi   ...  ' ' ci xi cj xj

   

n PD xk  k 1 c ' x k k



 

 

   

PD x p ' cp xp

(3)

 

CIM xi , x j .....x p  CIM xi  CIM x j  CIM xk (4) This shows additive property.

In this paper, under two condition CIM is measured. Under 1st condition CIM measures the component importance due to small change which is same for all components. Under 2nd condition CIM changes component parameter by same percentage according to effect on R. Where, R is system unreliability.

CIM under 1st condition: PD  xi  CIM =

ci'  xi 

PD  xk 

n

 c x  ' k

k 1

(5)

converter is used in WT configuration to match the grid connection.

A. Components of Wind Turbine The main components of wind turbine system are blades, gear box, pitch, shaft and bearing, sensor aerodynamic brake, yaw, generator etc. Speed of shaft is varying so mainly two types of shafts are used in WT namely low speed shaft and high speed shaft. Here we are going to explain some components of wind turbine system. Blades, connected to the rotor by hub, transmit the mechanical energy through the low speed shaft through gear box. Gear box is connected to the high speed shaft. Hence mechanical energy is transmitted to high speed shaft, which is connected to generator. Main bearing supports the low speed shaft and gearbox adjusts this speed. Yaw system is used to control the alignment to the direction of wind and pitch system is used to control the amount of power transmitted to the WT. Because all the components have different sizes and types hence the cost of the entire component will vary accordingly.

And cost of WTs also varies depending upon the configuration used. For example some WTs do not have gear box. So cost of these WTs will change. It is studied by other author that component of WTs like gearbox, blade/pitch, generator, power converter are faultier component [12] .

B. Wind Turbine Model Wind turbine system is shown in fig. 1. It consist of total four components namely bearing, gear box, generator and converter. All four components are connected in series. The cost importance measure of all these component are calculated in this paper. And then components are ranked according to their criticality.

k

nd

CIM under 2 condition: PD  xi 

CIM =

ci'  xi  n

ci  xi 

PD  xk 

 c x  k 1

' k

(6)

BEARING/SHAFT

GEAR BOX

GENERATOR

GENERATOR

k

B. Cost Function The cost function of each component of the Pareto growth model [11] is defined by equation below: Fig. 1: wind turbine system

1

 a  bi ci  xi    i    i  xi 

(7)

V. COST ANALYSIS

Where ai , bi ,  i are constants for each basic event. This Pareto class failure distribution is useful because it is an exponential generalization.

IV. WIND TURBINE There are various configurations of wind turbine with more advance technology that have been developed during last decade for increasing power. Commonly configuration used is horizontal axis WT having three blades, for that different combination of power control, drive train configuration, rotational speed can be used. In this paper

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Fig.2 shows the Reliability Block Diagram of wind turbine system. Here four components are connected in series.

Parameters of the Wind turbine system and mean failure probability of all the component of WT are given in Table.2 1

2

3

4

Fig.2. Reliability model of WT

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International Journal of Engineering, Management & Sciences (IJEMS) ISSN-2348 –3733, Volume-2, Issue-5, May 2015

Table 1. Parameter of WT system Name Component

of

Mean Probability

failure

Parameter



A

B

.06

2

0.8

Gear box

0.1

1.5

Generator

0.18

2

0.8

0

Converter

0.2

1

0.6

0

Bearing/shaft

(

)

Rank of componen t

Name of component Bearing/ shaft

Gear

generator

Inverter

CIM-1

4

3

2

1

CIM-2

4

3

1

2

From table 3 it is clear that in 1st condition inverter is more critical component. Hence need to be paying more attention.

In 2nd condition generator is more critical component.

0

0.86

0

The values of these parameter a, b, and c are taken from the Pareto growth model [11]. The minimal cut sets of the network are {1}, {2}, {3}, {4}. If any one of component will fail that causes system to fail. The system unavailability R can be defined in terms of component failure probability as:

R  x1  x2  x3  x4

(8)

R   x1  x2  x3  x4    x1 x2  x1 x3  x1 x4  x2 x3  x2 x4  x3 x4    x1 x2 x3  x1 x2 x4  x1 x3 x4  x2 x3 x4   x1 x2 x3 x4 Using rare event approximation neglecting higher terms R  x1  x2  x3  x4 From (1) partial derivative of component is calculated as:

(9)

  PD  x2   1 PD  x3   1 PD  x4   1 PD x1  1

The Cost Importance measure of all the components of wind turbine system is shown in table 2. These numerical values are obtained using equations (1) to (6). The mean probability failure data is taken from Koutoulakos [13].

Fig.3. Cost importance measure under 1st and 2nd condition.

Table2. CIM(1) and CIM(2) for individual components of wind turbine system Cost Component of wind turbine importance Bearing/ Gear generator Inverter measure shaft CIM-1 .03058 .1884 .36210 .41915 CIM-2

.12060

.21608

.36181

The result of the application of cost importance measure under 1st and 2nd condition to the component to wind turbine system is shown in fig 3.

VI. CONCLUSION

.30148

Importance measure plays very important role in designing and maintaining the system. In this paper we have studied the cost importance measure of components of wind turbine

Table3. Ranking of components of WT

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Criticality Analysis of Wind Turbine System Components Using Cost Importance Measure system under two conditions and also derive the information about most critical component in the system and their ranking has been obtained that is helpful in deciding the prioritization of risk, maintainability and reliability improvement tasks in cost optimum manner.

REFERENCES [1] [2] [3]

ACKNOWLEDGMENT I express my whole hearted gratitude to my guides Dr. G. L. Pahuja, (Professor) Electrical Engineering Department, National Institute of Technology Kurukshetra, Dr Vijander Singh (Associate Professor) and Dr Asha Rani (Associate Professor) ICE Division, Netaji Subhas Institute of Technology, who spent their valuable time in guiding me in selection and completion of my dissertation. I feel it to be a great privilege to work under their guidance. Especially I thank for their excellent encouragement in every direction for the successful completion of the project. Without their support, it would not have been possible to bring the project in its present form. Last but not the least, I express my thanks to all those who directly or indirectly extended help and co-operation in bringing out this work in its present form.

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Urvashi Chauhan, she is M.Tech 2nd year student from Netaji Subhas Institute of Technology, University of Delhi, ICE Division. She has completed B.Tech Degree in 2011 from Anand Enginnering College Agra, affiliated to Uttar Pradesh Technical University, after that she work as a lecturer in K.P. engineering college Agra for 2 years. Her two research paper have been presented till now.

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International Journal of Engineering, Management & Sciences (IJEMS) ISSN-2348 –3733, Volume-2, Issue-5, May 2015 Dr G.L. Pahuja, he is working as Professor and head of the department in Electrical Engineering Department, National Institute of Technology Kurukshetra. He received M.Tech and Phd degree in electrical engineering. Many researchers have been completed their research work under his guidance.

Dr Vijander Singh, he is Associate Professor in Instrumentation & Control Engineering Division, Netaji Subhas Institute of Technology. He has guided several researchers in their M.Tech and Phd thesis work.

Dr Asha Rani, she is Associate Professor in Instrumentation & Control Engineering Division, Netaji Subhas Institute of Technology, University of Delhi. Many M Tech and Phd student have been completed their research work under her guidance.

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