Title :
A continuous probability distribution for generating capacity reliability evaluation
Author :
Singh, C. ; Kim, J.O.
Author_Institution :
Texas A&M Univ., College Station, TX, USA
Abstract :
There are two broad categories of methods for generating capacity reliability evaluation. The traditional approach is based on obtaining generation capacity probability distribution by unit addition algorithms and convolving it with a suitable load model to obtain indices for generation reliability. The alternative approach used approximation of the discrete probability distribution by a continuous probability distribution. The techniques described in the available literature use some type of infinite expansion based on some well known distributions. The authors propose a different approach by using a multi-parameter probability distribution which by itself, without any expansion terms, provides a close approximation to the exact results. The distribution is a composite of gamma-distributions. Equations for obtaining the distribution parameters from the unit parameters are derived. When the number of parameters is increased, the accuracy of indices is enhanced and the results remain stable
Keywords :
electric power generation; power systems; probability; reliability; continuous probability distribution; gamma-distributions; generating capacity reliability evaluation; multi-parameter probability distribution;
Conference_Titel :
Probabilistic Methods Applied to Electric Power Systems, 1991., Third International Conference on
Conference_Location :
London
Print_ISBN :
0-85296-513-3