A BIASED RANDOM KEY GENETIC ALGORITHM APPROACH FOR UNIT COMMITMENT PROBLEM

Luís A. C. Roque, Dalila B. M. M. Fontes, Fernando A. C. C. Fontes

2010

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 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, form the comparisons made it can be concluded that the results produced improve upon the best known solutions.

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Paper Citation


in Harvard Style

A. C. Roque L., B. M. M. Fontes D. and A. C. C. Fontes F. (2010). A BIASED RANDOM KEY GENETIC ALGORITHM APPROACH FOR UNIT COMMITMENT PROBLEM . In Proceedings of the International Conference on Evolutionary Computation - Volume 1: ICEC, (IJCCI 2010) ISBN 978-989-8425-31-7, pages 332-339. DOI: 10.5220/0003076703320339


in Bibtex Style

@conference{icec10,
author={Luís A. C. Roque and Dalila B. M. M. Fontes and Fernando A. C. C. Fontes},
title={A BIASED RANDOM KEY GENETIC ALGORITHM APPROACH FOR UNIT COMMITMENT PROBLEM},
booktitle={Proceedings of the International Conference on Evolutionary Computation - Volume 1: ICEC, (IJCCI 2010)},
year={2010},
pages={332-339},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003076703320339},
isbn={978-989-8425-31-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Evolutionary Computation - Volume 1: ICEC, (IJCCI 2010)
TI - A BIASED RANDOM KEY GENETIC ALGORITHM APPROACH FOR UNIT COMMITMENT PROBLEM
SN - 978-989-8425-31-7
AU - A. C. Roque L.
AU - B. M. M. Fontes D.
AU - A. C. C. Fontes F.
PY - 2010
SP - 332
EP - 339
DO - 10.5220/0003076703320339