By Topic

Probabilistic optimal power flow incorporating wind power using point estimate methods

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

2 Author(s)
Ahmadi, H. ; Sch. of Electr. & Comput. Eng., Univ. of Tehran, Tehran, Iran ; Ghasemi, Hassan

Global tendency toward environmental-friendly sources of energy with lower generation costs led to increased penetration of renewable energies in power systems, especially wind power. Stochastic nature of wind speed has introduced new challenges to the conventional power system studies including optimal power flow (OPF) analysis, unit commitment, etc. In this paper, a Weibull distribution for wind speed with actual data is assumed and system loads are considered as random variables (RV) with normal distributions. Point estimate methods (PEM) are used here in order to handle the probabilistic OPF problem for a 6-Bus test system. The PEMs are compared with respect to Monte Carlo simulation (MCS) results. It is shown that these methods give acceptable results with significant reduction in computation burden. However, under certain conditions (e.g. RVs with high values of skewness and high order of nonlinearity in the OPF problem), PEMs may give inaccurate results. This inefficiency has not been observed in previous studies and is demonstrated in the test case used here.

Published in:

Environment and Electrical Engineering (EEEIC), 2011 10th International Conference on

Date of Conference:

8-11 May 2011