Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/70363
Author(s): Luís A.C. Roque
Dalila B.M.M. Fontes
Fernando A.C.C. Fontes
Title: A Biased Random Key Genetic Algorithm Approach for Unit Commitment Problem
Issue Date: 2011
Abstract: A Biased Random Key Genetic Algorithm (BRKGA) is proposed to find solutions for the unit commitment problem. In this problem, one wishes to schedule energy production on a given set of thermal generation units in order to meet energy demands at minimum cost, while satisfying a set of technological and spinning reserve constraints. In the BRKGA, solutions are encoded by using random keys, which are represented as vectors of real numbers in the interval [0, 1]. The GA proposed is a variant of the random key genetic algorithm, since bias is introduced in the parent selection procedure, as well as in the crossover strategy. Tests have been performed on benchmark large-scale power systems of up to 100 units for a 24 hours period. The results obtained have shown the proposed methodology to be an effective and efficient tool for finding solutions to large-scale unit commitment problems. Furthermore, from the comparisons made it can be concluded that the results produced improve upon some of the best known solutions.
Subject: Economia e gestão
Economics and Business
Scientific areas: Ciências sociais::Economia e gestão
Social sciences::Economics and Business
URI: https://repositorio-aberto.up.pt/handle/10216/70363
Source: EXPERIMENTAL ALGORITHMS
Document Type: Artigo em Livro de Atas de Conferência Internacional
Rights: openAccess
License: https://creativecommons.org/licenses/by-nc/4.0/
Appears in Collections:FEP - Artigo em Livro de Atas de Conferência Internacional

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