Statistical inference on the reliability performance index for electric power generation systems
A primary objective of this research is to analytically develop a probability density function for the Loss of Load, a widely used index in power systems reliability evaluation. The equations to compute the parameters of this distribution for any given load cycle are derived. The forced outage rate (F.O.R.) for a generating unit is instrumental in the computation of reliability indices. This research also suggests a method for obtaining a statistically consistent estimator of F.O.R. using a decision theoretic approach. In order to develop the theoretical structure for the problem stated, classical and decision theoretic (Bayesian) statistical inferences are used as major tools along with the univariate and multivariate asymptotic theory. Consequently, an approximate numerical multiple integration scheme is employed to compute the parameters of the asymptotic probability density function. The author believes that this statistical approach offers a more realistic alternative to the conventional calculation of an averaged value for the Loss of Load index where deterministic outage data are used.
- OSTI ID:
- 6217857
- Resource Relation:
- Other Information: Thesis (Ph. D.)
- Country of Publication:
- United States
- Language:
- English
Similar Records
More realistic reliability index for generating systems
Development and testing of improved statistical wind power forecasting methods.