By Topic

Probabilistic Methodologies for Determining the Optimal Number of Substation Spare Transformers

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Leite da Silva, A.M. ; Inst. of Electr. Syst. & Energy, Fed. Univ. of Itajuba, Itajuba, Brazil ; de Carvalho Costa, J.G. ; Chowdhury, A.A.

This paper presents new probabilistic methodologies for computing the optimal number of transformer spares for power distribution substations. The basic idea consists of three steps: (1) the reliability evaluation of a given system of transformers with inventory of spares; (2) the calculation of investment and operational costs of the system for different alternatives of inventory composition; and (3) the identification of the number of spares that minimizes the total cost. Two new models are proposed for the reliability evaluation step. In the first one, the system operational states are represented by a Markov process. The second one uses a chronological Monte Carlo simulation model to assess the reliability performance of a system with inventory of spares. Both models are able to provide indices such as probability, frequency, and duration of failures, as well as estimates of energy not supplied and the corresponding costs. The proposed methodologies are applied to a 72-kV distribution transformer system, and the obtained results are compared to those from a widely used model based on a Poisson distribution.

Published in:

Power Systems, IEEE Transactions on  (Volume:25 ,  Issue: 1 )