Estimating the Life-Distribution Parameters of Weibull-Life PV Systems Utilizing Non-Parametric Analysis

In this paper, a model is proposed to determine the life distribution parameters of the useful life region for the PV system utilizing a combination of non-parametric and linear regression analysis for the failure data of these systems. Results showed that this method is dependable for analyzing failure time data for such reliable systems when the data is scarce.

Authors:

• Saleem Z. Ramadan

Keywords:

• Masking
• Bathtub model
• reliability
• non-parametric analysis
• useful life.

References:

[1] E. F. Hitt, Battelle and O. H. Columbus, “Total ownership cost use in
management”, Digital Avionics Systems Conference, Proceedings, 17th
DASC. The AIAA/IEEE/SAE, Vol. 1, A32-1-5,(1998).
[2] Maish A, Atcitty C., Hester D. Greenberg D., Osborn D., Collier D.,
(1997). Photovoltaic Reliability, Proceedings of the 26th Photovoltic
Specialists Conference (PVSC) Anheim CA 1049.
[3] Begovic M., Pregelj A., Rohatgi A., (2000). Four-year Performance
Assessment of the 342 kW PV System at Georgia Tech, Proceedings of
the 28th Photovoltic Specialists Conference (PVSC) Anchorage AL.
[4] Guess, F. M., Usher, J. S., Hodgson, T. J. (1991). Estimating system and
component reliabilities under partial information on cause of failure. J.
Statist. Plann. Infer.29:75–85.
[5] Flehinger, B. J., Reiser, B., and Yashchin, E. (1998). Survival with
competing risks and masked causes of failures. Biometrika 85:151–164.
[6] Basu, S., Basu, A. P., and Mukhopadhyay, C. (1999). Bayesian analysis
for masked system failure data using non-identical weibull models. J.
Statist. Plann. Infer. 78:255–275.
[7] Chiranjit M. and Sanjib B., (2007). Bayesian Analysis of Masked Series
System Lifetime Data. Communications in Statistics—Theory and
Methods, 36: 329–348.
[8] Charles E., (2008). An Introduction to Reliability and Maintainability
Engineering,McGraw-Hill, New Delhi.
[9] Elsayed A., (1996). Reliability Engineering, Addison Wesley,
Massachusetts.