Optimal generation expansion planning via the Cross-Entropy method

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, availabil...

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Bibliographic Details
Published inProceedings of the 2009 Winter Simulation Conference (WSC) pp. 1482 - 1491
Main Authors Kothari, R.P., Kroese, D.P.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2009
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ISBN9781424457700
142445770X
ISSN0891-7736
DOI10.1109/WSC.2009.5429296

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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.
ISBN:9781424457700
142445770X
ISSN:0891-7736
DOI:10.1109/WSC.2009.5429296