A modified harmony search method for wind generator design

  • Authors:

  • Xiao-Zhi Gao;Xiaolei Wang;Kai Zenger

  • Affiliations:

  • Department of Automation and Systems Technology, School of Electrical Engineering, Aalto University, Otaniementie 17, FI-00076 Aalto, Finland;Department of Automation and Systems Technology, School of Electrical Engineering, Aalto University, Otaniementie 17, FI-00076 Aalto, Finland;Department of Automation and Systems Technology, School of Electrical Engineering, Aalto University, Otaniementie 17, FI-00076 Aalto, Finland

  • Venue:
  • International Journal of Bio-Inspired Computation
  • Year:
  • 2013

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Abstract

The harmony search HS method is an emerging meta-heuristic optimisation algorithm, which has been widely employed to deal with various optimisation problems during the past decade. However, like most of the evolutionary computation techniques, it sometimes suffers from a rather slow search speed, and even fails to find the global optima in an efficient way. In this paper, a new HS method with dual memory, namely DUAL-HS, is proposed and studied. The secondary memory in the DUAL-HS takes advantage of the opposition-based learning OBL to evolve so that the quality of all the harmony memory members can be significantly improved. Optimisation of 25 typical benchmark functions demonstrate that compared with the regular HS method, our DUAL-HS has an enhanced convergence property. The DUAL-HS is further applied for the wind generator design, in which it has also shown a satisfactory optimisation performance.