A biased random key genetic algorithm approach for unit commitment problem

• Type: Article in International Conference Proceedings Book
• Date: 2010

Authors

roque, lac (Author) Other; fontes, dbmm (Author) FEP; fontes, facc (Author) FEUP

Conference proceedings International

Title: ICEC 2010 - Proceedings of the International Conference on Evolutionary Computation

Pages: 332-339

International Conference on Evolutionary Computation, ICEC 2010

Valencia, 24 October 2010 through 26 October 2010

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Other information

Authenticus ID: P-007-X3Z

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 8