Научная статья на тему 'An Innovative Methodology for Evaluation of Reliability Indices of Electric Traction System'

An Innovative Methodology for Evaluation of Reliability Indices of Electric Traction System Текст научной статьи по специальности «Медицинские технологии»

CC BY
174
14
i Надоели баннеры? Вы всегда можете отключить рекламу.
Ключевые слова
Electric Traction System / Reliability / Failure Rate / Repair Rate

Аннотация научной статьи по медицинским технологиям, автор научной работы — Aditya Tiwary, Swati Tiwary

Evaluation of reliability is most important when we have to check the availability of supply in any electric power system. The basic reliability index which is of importance is failure rate, repair time and unavailability of the supply in any electric power system. In this paper evaluation of various basic reliability indices for the electric traction system is done. Electric traction system is very important as it is used for operation of passenger trains and freight trains across a large rail network throughout the world. As the traction system is very important therefore reliability evaluation of its various parameters are essential for proper and uninterrupted working of the whole electric traction system.

i Надоели баннеры? Вы всегда можете отключить рекламу.
iНе можете найти то, что вам нужно? Попробуйте сервис подбора литературы.
i Надоели баннеры? Вы всегда можете отключить рекламу.

Текст научной работы на тему «An Innovative Methodology for Evaluation of Reliability Indices of Electric Traction System»

An Innovative Methodology for Evaluation of Reliability Indices of Electric Traction System

Aditya Tiwary, Swati Tiwary •

Entrepreneur, Vijay Nagar, Indore, India raditya2002@gmail.com

Abstract

Evaluation of reliability is most important when we have to check the availability of supply in any electric power system. The basic reliability index which is of importance is failure rate, repair time and unavailability of the supply in any electric power system. In this paper evaluation of various basic reliability indices for the electric traction system is done. Electric traction system is very important as it is used for operation of passenger trains and freight trains across a large rail network throughout the world. As the traction system is very important therefore reliability evaluation of its various parameters are essential for proper and uninterrupted working of the whole electric traction system.

Keywords: Electric Traction System, Reliability, Failure Rate, Repair Rate.

I. Introduction

Reliability evaluation of a system or component or element is very important in order to predict its availability and other relevant indices. Reliability is the parameter which tells about the availability of the system under proper working conditions for a given period of time. A Markov cut-set composite approach to the reliability evaluation of transmission and distribution systems involving dependent failures was proposed by Singh et al. [1]. The reliability indices have been determined at any point of composite system by conditional probability approach by Billinton et al. [2]. Wojczynski et al. [3] discussed distribution system simulation studies which investigate the effect of interruption duration distributions and cost curve shapes on interruption cost estimates. New indices to reflect the integration of probabilistic models and fuzzy concepts was proposed by Verma et al. [4]. Zheng et al. [5] developed a model for a single unit and derived expression for availability of a component accounting tolerable repair time. Distributions of reliability indices resulting from two sampling techniques are presented and analyzed along with those from MCS by Jirutitijaroen and Singh [6]. Dzobe et al. [7] investigated the use of probability distribution function in reliability worth analysis of electric power system. Bae and Kim [8] presented an analytical technique to evaluate the reliability of customers in a micro grid including distribution generations. Reliability network equivalent approach to distribution system reliability assessment is proposed by Billinton and Wang [9].

Customer and energy based indices consideration for reliability enhancement of distribution system using Improved Teaching Learning based optimization is discussed [10]. An Innovative Self-Adaptive Multi-Population Jaya Algorithm based Technique for Evaluation and Improvement of Reliability Indices of Electrical Power Distribution System, Tiwary et al. [11].

Jirutitijaroen et al. [12] developed a comparison of simulation methods for power system reliability indexes and their distribution. Determination of reliability indices for distribution system using a state transition sampling technique accounting random down time omission, Tiwary et al. [13]. Tiwary et al. [14] proposed a methodology based on Inspection-Repair-Based Availability Optimization of Distribution System Using Bare Bones Particle Swarm Optimization. Bootstrapping based technique for evaluating reliability indices of RBTS distribution system neglecting random down time was evaluated [15].

Volkanavski et al. [16] proposed application of fault tree analysis for assessment of the power system reliability. Li et al. [17] studies the impact of covered overhead conductors on distribution reliability and safety. Reliability enhancement of distribution system using Teaching Learning based optimization considering customer and energy based indices was obtained in Tiwary et al. [18]. Self-Adaptive Multi-Population Jaya Algorithm based Reactive Power Reserve Optimization Considering Voltage Stability Margin Constraints was obtained in Tiwary et al. [19]. A smooth bootstrapping based technique for evaluating distribution system reliability indices neglecting random interruption duration is developed [20]. Tiwary et al. [21] have developed an inspection maintenance based availability optimization methodology for feeder section using particle swarm optimization. The impact of covered overhead conductors on distribution reliability and safety is discussed [22]. Tiwary et al. [23] has discussed a methodology for reliability evaluation of an electrical power distribution system, which is radial in nature. Sarantakos et al. [24] introduced a method to include component condition and substation reliability into distribution system reconfiguration. Tiwary et al. [25] has discussed a methodology for evaluation of customer orientated indices and reliability of a meshed power distribution system. Reliability evaluation of engineering system is discussed [26]. Battu et al. [27] discussed a method for reliability compliant distribution system planning using Monte Carlo simulation. Application of non-parametric bootstrap technique for evaluating MTTF and reliability of a complex network with non-identical component failure laws is discussed [28]. Tiwary and Tiwary [29] have developed an innovative methodology for evaluation of customer orientated indices and reliability study of electrical feeder system.

In this paper basic reliability indices, failure rate, repair rate and unavailability of the electric traction system is evaluated. Electric traction system is very important as it is used for operation of passenger trains and freight trains across a large rail network throughout the world. As the traction system is very important therefore reliability evaluation of its various parameters are essential for proper and uninterrupted working of the whole electric traction system. Reliability block diagram which is a diagrammatic method for showing how different components are connected in a system is designed for the traction system considered and various indices related to reliability are obtained.

II. Reliability block diagram representation of electric traction system

Reliability block diagram which is a diagrammatic method for showing how different components are connected in a system is obtained for the electric traction system. Electrical traction system is that system that uses electrical power for traction system i.e. for railways, trams, trolleys, etc. The track electrification means to the type of source which is used while powering the electric locomotive systems. The two main types of electric traction systems that exist are as Direct Current (DC) electrification system and Alternating Current (AC) electrification system. The reliability block diagram of Direct Current (DC) electrification system is shown in Fig. 1. It consist of source, overhead wire, pantograph, motor control and motor as its important parts. Each and every component of the system is connected in series manner.

Source Overhead wire ^J Pantograph

Motor control Motor

Fig. 1. Reliability block diagram of Direct Current (DC) electrification system

The reliability block diagram of Alternating Current (AC) electrification system is shown in Fig. 2. It consist of source, overhead wire, pantograph, transformer, rectifier, motor control and motor as its important parts. It can be seen from Fig. 2 that each and every component is connected in series.

Fig. 2. Reliability block diagram of Alternating Current (AC) electrification system

III. Evaluation of reliability and its various indices of electric traction system

The system is having a constant failure rate and therefore the reliability of the system having constant failure rate is evaluated by using the following relation.

R(t) = e-xt (1)

Where R(t) represents the reliability of each and every component. A represents the failure rate per year and t represents time period which is taken as one year.

The mean time to failure (MTTF) can be obtained as follows: MTTF = 1 (2)

A series system is that system in which one component fails, the complete system will fail and for working of the whole system it is mandatory that all the component are in working condition. If one assumes time independent reliability n, r2...rn, then reliability of series system is given as:

R,

П-

In series configuration combined failure rate is calculated as follows.

ATotal =

Unavailability of series configuration is calculated by using following relation. UTotal =

Total repair rate of the components connected in series manner is obtained as follows. _ u

rTotal = T

(3)

(4)

(5)

(6)

IV. Result and Discussion

Table 1 shows the initial data such as failure rate per year and repair time in hours for the components of direct current (DC) electrification traction system. There are four components in the DC electrification traction system which are overhead wire, pantograph, motor control and motor and shown as components c1, c2, c3 and c4 respectively.

Table 1: Initial data for different components of the direct current electrification traction system.

component c1 c2 c3 c4

Failure rate/year 0.04 0.03 0.005 0.004

Repair time (hrs.) 3 4 5 6

Table 2 shows the initial data such as failure rate per year and repair time in hours for the components of alternating current (AC) electrification traction system. There are six components in the AC electrification traction system which are overhead wire, pantograph, transformer, rectifier, motor control and motor and shown as components c1, c2, c3, c4, c5 and c6 respectively.

Table 2: Initial data for different components of the alternating current electrification traction system.

component c1 c2 c3 c4 c5 c6

Failure rate/year 0.04 0.03 0.002 0.003 0.005 0.004

Repair time (hrs.) 3 4 6 4 5 6

Table 3 provides the evaluated reliability of each component of DC electrification traction system as 0.9608, 0.9704, 0.9950 and 0.9960 respectively. The overall reliability of the DC electrification traction system obtained is as 0.9240.

Table 4 provides the evaluated reliability of each component c1, c2, c3, c4, c5 and c6 of AC electrification traction system as 0.9608, 0.9704, 0.9980, 0.9950, 0.9950 and 0.9960 respectively. The overall reliability of the AC electrification traction system obtained is as 0.9175.

Table 3 Evaluated Reliability of each component of DC electrification traction system

Component Reliability

c1 0.9608

c2 0.9704

c3 0.9950

c4 0.9960

Table 4 Evaluated Reliability of each component of AC electrification traction system

Component Reliability

c1 0.9608

c2 0.9704

c3 0.9980

c4 0.9950

c5 0.9950

c6 0.9960

Table 5 and Table 6 provide the evaluated mean time to failure of DC electrification traction system and evaluated mean time to failure of AC electrification traction system respectively.

Table 5 Evaluated mean time to failure of DC electrification traction system

Component Evaluated mean time to failure

c1 25

c2 33.33

c3 200

c4 250

Table 6 Evaluated mean time to failure of AC electrification traction system

Component Evaluated mean time to failure

c1 25

c2 33.33

c3 500

c4 333.33

c5 200

c6 250

Evaluated unavailability for each and every component of the DC electrification traction system is shown in Table 7. The evaluated unavailability obtained are 0.12, 0.12, 0.025 and 0.024 respectively. The evaluated unavailability of each component of the AC electrification traction system are 0.12, 0.12, 0.012, 0.012, 0.025 and 0.024 respectively as shown in Table 8.

Table 7 Evaluated unavailability for each and every component of the DC electrification traction system component c1 c2 c3 c4

Unavailability 012 012 0.025 0.024

Table 8 Evaluated unavailability for each and every component of the AC electrification traction system

component c1_c2_c3_c4_c5_c6_

Unavailability 0.12_0.12_0.012 0.012 0.025 0.024

Table 9 and Table 10 provide the component level evaluated failure rate, repair rate and unavailability for each and every component of the DC electrification traction system and AC electrification traction system respectively.

Table 9 Component level evaluated failure rate, repair rate and unavailability for each and every component of the _DC electrification traction system._

Component Level C1 C2 C3 C4

Failure rate 0.04 0.07 0.075 0.079

Repair rate 3 3.4286 3.5333 3.6582

Unavailability 0.12 0.24 0.265 0.289

Table 10 Component level evaluated failure rate, repair rate and unavailability for each and every component of the AC electrification traction system.

Component Level C1 C2 C3 C4 C5 C6

Failure rate 0.04 0.07 0.072 0.075 0.08 0.084

Repair rate 3 3.4286 3.5 3.52 3.6125 3.7262

Unavailability 0.12 0.24 0.252 0.264 0.289 0.313

Fig. 3 and Fig. 4 provide the magnitude of evaluated reliability of each component of DC electrification traction system and AC electrification traction system respectively. Magnitude of evaluated mean time to failure of DC electrification traction system and that of AC electrification traction system is shown in Fig. 5 and Fig. 6 respectively.

Fig. 3 Magnitude of evaluated reliability of each component of DC electrification traction system

Fig. 4 Magnitude of evaluated reliability of each component of AC electrification traction system

Fig. 5 Magnitude of evaluated mean time to failure of Fig. 6 Magnitude of evaluated mean time to failure of DC electrification traction system AC electrification traction system

Fig. 7 and Fig. 8 provide the magnitude of evaluated unavailability for each and every component of the DC electrification traction system and AC electrification traction system respectively.

Fig. 7 Magnitude of evaluated unavailability for each Fig. 8 Magnitude of evaluated unavailability for each and every component of the DC electrification traction and every component of the AC electrification traction system system

iНе можете найти то, что вам нужно? Попробуйте сервис подбора литературы.

Magnitude of component level evaluated failure rate for each and every component of the DC electrification traction system, magnitude of component level evaluated failure rate for each and every component of the AC electrification traction system, magnitude of component level evaluated repair rate for each and every component of the DC electrification traction system, magnitude of component level evaluated repair rate for each

Aditya Tiwary, Swati Tiwary

AN INNOVATIVE METHODOLOGY FOR EVALUATION OF RT&A, No 2(62) RELIABILITY INDICES OF ELECTRIC TRACTION SYSTEM_Volume 16, June 2021

and every component of the AC electrification traction system are provided in Fig. 9, Fig. 10, Fig. 11 and Fig. 12 respectively.

Fig. 9 Magnitude of component level evaluated failure rate for each and every component of the DC

Fig. 10 Magnitude of component level evaluated failure rate for each and every component of the AC electrification traction system.

electrification traction system.

cl c2 c3 c4

Mill

cl c2 c3 c4 c5 c6

l

0

Fig. 11 Magnitude of component level evaluated repair rate for each and every component of the DC electrification traction system.

Fig. 12 Magnitude of component level evaluated repair rate for each and every component of the AC electrification traction system.

Fig. 13 and Fig. 14 provides magnitude of component level evaluated unavailability for each and every component of the DC electrification traction system and magnitude of component level evaluated unavailability for each and every component of the AC electrification traction system respectively.

Fig. 13 Magnitude of component level evaluated Fig. 14 Magnitude of component level evaluated unavailability for each and every component of the DC unavailability for each and every component of the electrification traction system. AC electrification traction system.

V. Conclusion

Identifying various values of reliability is most important when we have to check the availability of supply in any system. Electric traction system is very important as it is used for operation of passenger trains and freight trains across a large rail network throughout the world. Reliability of each component of DC electrification traction system and AC electrification traction system is obtained. Mean time to failure and unavailability for each and every component of the DC electrification traction system and AC electrification traction system is also calculated. This paper has also evaluated the basic reliability indices such as failure rate, repair rate and unavailability at the component level for the DC electrification traction system and AC electrification traction system respectively.

References

[1] C. Singh. (1981). Markov cut-set approach for the reliability evaluation of transmission and distribution systems. IEEE Trans. on Power Apparatus and Systems, 100: 2719-2725.

[2] R. Billinton. (1969). Composite system reliability evaluation. IEEE Trans. on Power Apparatus and Systems, 88: 276-281.

[3] E. Wojczynski, R. Billinton. (1985). Effects of distribution system reliability index distributions upon interruption cost/reliability worth estimates. IEEE Trans. on Power Apparatus and Systems, 11: 3229-3235.

[4] A. K. Verma, A. Srividya, H. M. R. Kumar. (2002). A framework using uncertainties in the composite power system reliability evaluation. Electric Power Components and Systems, 30: 679-691.

[5] Z. Zheng, L. Cui, Alan G. Hawkes. (2006). A study on a single-unit Markov repairable system with repair time omission. IEEE Trans. on Reliability, 55: 182-188.

[6] P. Jirutitijaroen, C. singh. (2008). Comparison of simulation methods for power system reliability indexes and their distributions. IEEE Trans. on Power Systems, 23: 486-493.

[7] O. Dzobe, C. T. Gaunt, R. Herman. (2012). Investigating the use of probability distribution functions in reliability-worth analysis of electric power systems. Int. J. of Electrical Power and Energy Systems, 37: 110-116.

[8] I. S. Bae, J. O. Kim. (2008). Reliability evaluation of customers in a microgrid. IEEE Trans. on Power Systems, 23: 1416-1422.

[9] R. Billinton, P. Wang. (1998). Reliability-network-equivalent approach to distribution-system-reliability evaluation. IEE Proc. generation, transmission and distribution, 145: 149-153.

[10] A. Tiwary. (2017). Reliability enhancement of distribution system using Teaching Learning based optimization considering customer and energy based indices. International Journal on Future Revolution in Computer Science & Communication Engineering, 3: 58-62.

[11] A. Tiwary. (2018). An Innovative Self-Adaptive Multi-Population Jaya Algorithm based Technique for Evaluation and Improvement of Reliability Indices of Electrical Power Distribution System. International Journal on Future Revolution in Computer Science & Communication Engineering, 4: 299-302.

[12] Jirutitijaroen P, singh C. (2008). Comparison of simulation methods for power system reliability indexes and their distribution. IEEE Trans Power Syst, 23: 486-92.

[13] A. Tiwary, R. Arya, S. C. Choube, L. D. Arya. (2013). Determination of reliability indices for distribution system using a state transition sampling technique accounting random down time omission. Journal of The Institution of Engineers (India): series B (Springer), 94: 71-83.

[14] A. Tiwary. (2019). Inspection-Repair-Based Availability Optimization of Distribution System Using Bare Bones Particle Swarm Optimization. Chapter in Book Series Computational Intelligence: Theories, Applications and Future Directions - Volume II, Advances in Intelligent Systems and computing, 799.

[15] A. Tiwary, R. Arya, L. D. Arya, S. C. Choube. (2017). Bootstrapping based technique for evaluating reliability indices of RBTS distribution system neglecting random down time. The IUP Journal of Electrical and Electronics Engineering, X: 48-57.

[16] Volkanavski, Cepin M, Mavko B. (2009). Application of fault tree analysis for assessment of the power system reliability. Reliab Eng Syst Safety, 94: 1116-27.

[17] Li BM, Su CT, Shen CL. (2010). The impact of covered overhead conductors on distribution reliability and safety. Int J Electr Power Energy Syst, 32: 281-9.

[18] A. Tiwary. (2017). Reliability enhancement of distribution system using Teaching Learning based optimization considering customer and energy based indices. International Journal on Future Revolution in Computer Science & Communication Engineering, 3: 58-62.

[19] A. Tiwary. (2018). Self-Adaptive Multi-Population Jaya Algorithm based Reactive Power Reserve Optimization Considering Voltage Stability Margin Constraints. International Journal on Future Revolution in Computer Science & Communication Engineering, 4: 341-345.

[20] R. Arya, A. Tiwary, S. C. Choube, L. D. Arya. (2013). A smooth bootstrapping based technique for evaluating distribution system reliability indices neglecting random interruption duration. Int. J. of Electrical Power and Energy System, 51: 307-310.

[21] A. Tiwary. (2018). Inspection-Maintenance-Based Availability Optimization of Feeder Section Using Particle Swarm optimization. Soft Computing for Problem Solving-Advances in Intelligent Systems and Computing, 816: 257-272.

[22] M. BinLi, C. TzongSu, C. LungShen. (2010). The impact of covered overhead conductors on distribution reliability and safety. Int. J. of Electrical Power and Energy System, 32: 281-289.

[23] AdityaTiwary. (2019). Reliability evaluation of radial distribution system - A case study. Int. J. of Reliability: Theory and Applications, 14, 4(55): 9-13.

[24] I. Sarantakos, D. M. Greenwood, J. Yi, S. R. Blake, P. C. Taylor. (2019). A method to include component condition and substation reliability into distribution system reconfiguration. Int. J. of Electrical Power and Energy System, 109: 122-138.

[25] A. Tiwary. (2020). Customer orientated indices and reliability evaluation of meshed power distribution system. Int. J. of Reliability: Theory and Applications, 15, 1(56): 10-19.

[26] A. Tiwary, P. Patel. (2020). Reliability Evaluation of Hose Reel System - A Practical Approach. Journal of Industrial Safety Engineering, 7: 30-34.

[27] N. R. Battu, A. R. Abhyankar, N. Senroy. (2019). Reliability Compliant Distribution System Planning Using Monte Carlo Simulation. Electric power components and systems, 47: 985-997.

[28] A. Tiwary. (2020). Application of Non-Parametric Bootstrap Technique for evaluating MTTF and Reliability of a Complex Network with Non-Identical Component Failure Laws. Reliability: Theory and Applications, 15: 62-69.

[29] A. Tiwary, S. Tiwary. (2020). Evaluation of Customer Orientated Indices and Reliability Study of Electrical Feeder System. Reliability: Theory and Applications, 15: 36-43.

i Надоели баннеры? Вы всегда можете отключить рекламу.