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An Improved Differential Evolution Scheme for the Solution of Large-Scale Unit Commitment Problems
Volume 21, Issue 2 (2010), pp. 175–190
Chen-Sung Chang  

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https://doi.org/10.15388/Informatica.2010.281
Pub. online: 1 January 2010      Type: Research Article     

Received
1 July 2008
Published
1 January 2010

Abstract

This paper presents an improved differential evolution (IDE) method for the solution of large-scale unit commitment (UC) problems. The objective of the proposed scheme is to determine the generation schedule which minimizes the total operating cost over a given time horizon subject to a variety of constraints. Through its use of enhanced acceleration and migration processes, the IDE method limits the population size required in the search procedure and is therefore an ideal candidate for the solution of large-scale combinatorial optimization problems. The effectiveness of the proposed approach is verified by performing a series of simulations based upon the practical Tai-Power System (TPS) and various other power systems presented in the literature. In general, the results show that the IDE scheme outperforms existing deterministic and stochastic optimization methods both in terms of the quality of the solutions obtained and the computational cost. Furthermore, it is found that the magnitude of the cost savings achieved by the IDE scheme compared to that obtained by the other optimization techniques increases as the number of generating units within the power system increases. Therefore, the proposed scheme represents a particularly effective technique for the solution of large-scale UC problems.

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Keywords
unit commitment differential evolution improved differential evolution

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INFORMATICA

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