access icon free Reliability analysis of phasor measurement unit incorporating hardware and software interaction failures

As the electrical power system has increased in its geographical sprawl, adequate measures for reliability analysis for the wide area measurement system (WAMS) and phasor measurement units (PMUs) have become necessary. However, existing PMU reliability models are constrained by the assumption that PMU failures may be encountered either because of hardware failures or because of software failures only. Most modem safety critical systems, like the PMU are characterised by close proximity of hardware and software operations which leads to correlated failures. This is referred to as hardware–software interaction failure and is disregarded by contemporary PMU reliability models. In this paper, a modelling framework has been developed using Markov process that captures hardware–software interaction failures, apart from the hardware specific and software specific failures, and presents a Markov model-based unified PMU reliability model. This paper also offers a novel Monte Carlo simulation (MCS) technique to estimate PMU failure data to account for scanty PMU failure data from field installations. The novel algorithms for MCS based PMU failure estimation are expounded along with detailed methodologies for fitting the simulated failure data to the unified reliability model. The results presented herein demonstrate the improved accuracy of the proposed method.

Inspec keywords: Monte Carlo methods; phasor measurement; power system reliability; Markov processes; power system control

Other keywords: power system monitoring; Markov process; phasor measurement units; Monte Carlo simulation; wide area measurement system; power system control; hardware–software interaction failure; geographically dispersed system; reliability analysis; PMU

Subjects: Monte Carlo methods; Power system control; Control of electric power systems; Power system measurement and metering; Markov processes; Reliability; Monte Carlo methods; Markov processes

References

    1. 1)
    2. 2)
    3. 3)
      • 1. IEEE standard for synchrophasors for power system’. IEEE C37.118, 2005.
    4. 4)
      • 7. WECC Synchro-Phasor Project Whitepaper, Version 3.0, 2009.
    5. 5)
    6. 6)
      • 10. Murthy, C., Mishra, A., Ghosh, D., Sinha Roy, D., Mohanta, D.K.: ‘Reliability analysis of phasor measurement unit using hidden Markov model’, IEEE Syst. J., 2014, in press, DOI: 10.1109/JSYST.2014.2314811.
    7. 7)
    8. 8)
    9. 9)
      • 11. Butner, S.E., Krishnan Iyer, R.: ‘A statistical study of reliability and system load at SLAC’. Center for Reliable Computing, Computer Systems Laboratory, Stanford University, 1980.
    10. 10)
    11. 11)
      • 9. Murthy, C., Varma, K.A., Roy, D.S., Mohanta, D.K.: ‘Reliability evaluation of phasor measurement unit using type-2 fuzzy set theory’, IEEE Syst. J., in press, DOI: 10.1109/JSYST.2014.2309191.
    12. 12)
    13. 13)
      • 14. Peng, Z.: ‘Wide area monitoring system and its application on power system low-frequency oscillation suppression’. PhD dissertation, Department of Electrical Engineering, Hong Kong Polytechnic University, 2012.
    14. 14)
      • 15. Billinton, R., Allan, R.N.: ‘Reliability evaluation of engineering systems’ (Plenum Press, New York, 1994, 2nd edn.).
    15. 15)
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-gtd.2014.0115
Loading

Related content

content/journals/10.1049/iet-gtd.2014.0115
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading