Opposition-Based Modified Differential Evolution Algorithm for Power System Economic Load Dispatch

Abstract:

Opposition-based modified differential evolution algorithm (OMDE) is proposed for solving power System economic load dispatch in this paper. This algorithm integrates the opposition-based learning operation with the crossover operation to enhance the convergence of the algorithm and to prevent the algorithm from being trapped into the local optimum effectively. Besides, we employed a new strategy to dynamic adjust mutation rate (MR) and crossover rate (CR), which is aimed at further improving algorithm performance. Based on 6 units and 13 units power system experiment simulations, the OMDE has demonstrated stronger convergence and stability than original differential (DE) algorithm and other improved algorithms that reported in recent literature.

• Periodical: Applied Mechanics and Materials (Volumes 365-366)
• Pages: 178-181
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.365-366.178
• Online since: August 2013
• Authors: Hong Gang Xia, Wei Xiang Ding
• Keywords: Convergence, OMDE, Opposed-Learning, Stability, Strategy

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