With the advent of open transmission access, power transfers in interconnected networks have increased. The transfer capability between two buses or areas is a random variable, but the current available transfer capability (ATC) postings by the transmission service providers are deterministic. For a market participant, managing transmission risks requires a statistical forecast for the expected range of transfer capability. From this viewpoint, it is worthwhile to approach the ATC problem as a probabilistic one. A simple bootstrap technique is proposed to determine the probability distribution of an ATC which reflects the market activities and operational risks. The proposed method draws with replacement from recent bus injection datasets many times to create a pseudo-population of system situations from which ATCs are calculated. The obtained ATC distributions can be used to evaluate the risk of curtailment for incremental levels of transfers, thus permitting more informed decisions in arranging transmission services.
[1]
K.R.C. Mamandur,et al.
Efficient Simulation of Line and Transformer Outages in Power Systems
,
1982,
IEEE Transactions on Power Apparatus and Systems.
[2]
Feng Xia,et al.
A methodology for probabilistic simultaneous transfer capability analysis
,
1996
.
[3]
Boualem Boashash,et al.
The bootstrap and its application in signal processing
,
1998,
IEEE Signal Process. Mag..
[4]
G. C. Ejebe,et al.
Available transfer capability calculations
,
1998
.
[5]
G.T. Heydt,et al.
A stochastic model in simultaneous interchange capacity calculations
,
1975,
IEEE Transactions on Power Apparatus and Systems.
[6]
Robert Tibshirani,et al.
An Introduction to the Bootstrap
,
1994
.
[7]
A.C.G. Melo,et al.
Simultaneous transfer capability assessment by combining interior point methods and Monte Carlo simulation
,
1997
.