The purpose of this paper is to analyse the performance of a wind electric generating power plant through the study of reliability measures. The enhancement of the performance of the wind power plant using various approaches is also an objective of this paper.
This paper describes two models of a wind electric generating power plant using the Markov process and supplementary variable technique and solved with the help of Laplace transformation. The first model has been analyzed without fault coverage and Gumbel-Hougaard family of copula, while the second model of the wind power plant employs fault coverage and Gumbel-Hougaard family of copula which are used to enhance the performance. The proposed methodology is then illustrated in detail considering numerical examples.
Numerous reliability characteristics such as availability, reliability and mean time to failure to examine the performance of the wind power plant have been investigated. Through the comparative study of both the models, the authors concluded that the plant can generate electricity over long periods of time by covering more and more detected faults, which is made possible with two types of repair facility.
In this work, the authors have developed a mathematical model based on a wind electric generating power plant. This work incorporates not only the component failures that stop or degrade the working of the plant but also deals with the catastrophic and repair strategy of the plant.
Goyal, N. and Ram, M. (2017), "Stochastic modelling of a wind electric generating power plant: Performance under multi-approaches", International Journal of Quality & Reliability Management, Vol. 34 No. 1, pp. 103-127. https://doi.org/10.1108/IJQRM-09-2015-0143
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