Optimal generation expansion planning via the cross-entropy method

Kothari, Rishabh P. and Kroese, Dirk P. (2009). Optimal generation expansion planning via the cross-entropy method. In: M. D. Rossetti, R. R. Hill, B. Johansson, A. Dunkin and R. G. Ingalls, Proceedings of the 2009 Winter Simulation Conference. 2009 Winter Simulation Conference (ERA Rank B), Austin, Texas, (1482-1491). 13-16 December 2009. doi:10.1109/WSC.2009.5429296


Author Kothari, Rishabh P.
Kroese, Dirk P.
Title of paper Optimal generation expansion planning via the cross-entropy method
Conference name 2009 Winter Simulation Conference (ERA Rank B)
Conference location Austin, Texas
Conference dates 13-16 December 2009
Proceedings title Proceedings of the 2009 Winter Simulation Conference   Check publisher's open access policy
Journal name Proceedings of the 2009 Winter Simulation Conference (wsc 2009 ), Vol 1-4   Check publisher's open access policy
Place of Publication United States
Publisher IEEE - Inst Electrical Electronics Engineers Inc
Publication Year 2009
Sub-type Fully published paper
DOI 10.1109/WSC.2009.5429296
ISBN 9781424457717
ISSN 0891-7736
Editor M. D. Rossetti
R. R. Hill
B. Johansson
A. Dunkin
R. G. Ingalls
Volume 1-4
Start page 1482
End page 1491
Total pages 10
Collection year 2010
Language eng
Abstract/Summary The Generation Expansion Planning (GEP) problem is a highly constrained, large-scale, mixed integer nonlinear programming problem. The objective of the GEP problem is to evaluate the least cost investment plan for addition of power generating units over a planning period subject to demand, availability, and security constraints. In this paper, a GEP model is presented and the Cross-Entropy (CE) optimization method is developed to solve the problem. The CE method is an effective algorithm for solving large combinatorial optimization problems. The main advantage of the CE method over other metaheuristic techniques is that it does not require decomposition of the problem into a master problem and operation subproblems, greatly reducing the computational complexity. This method also provides a fast and reliable convergence to the optimal solution.
Subjects 970101 Expanding Knowledge in the Mathematical Sciences
010406 Stochastic Analysis and Modelling
Keyword Cross entropy
Cross-entropy method
Effective algorithm
Q-Index Code E1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Book Series: Winter Simulation Conference Proceedings

 
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in Thomson Reuters Web of Science Article
Scopus Citation Count Cited 5 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Wed, 31 Mar 2010, 16:24:03 EST by Kay Mackie on behalf of School of Mathematics & Physics