Multi-team perturbation guiding Jaya algorithm for optimization of wind farm layout

Abstract This study proposes a Multi-team perturbation-guiding Jaya (MTPG-Jaya) algorithm which uses multiple teams to explore the search space. Each team uses the same set of a population, and there is a different perturbation or movement equation for each team. During the search process, the set of the population moves to new positions by each team uniquely. The moving equation of the worst performing team is updated online by the superiority of solutions produced by each team. The superiority of the solutions for each team is calculated based on fitness value and boundary violations of solutions. The proposed algorithm is examined using unconstrained benchmark functions and CEC-2005 test functions. Computational test results have demonstrated the effectiveness of the MTPG-Jaya algorithm when compared to other well-known approaches. Furthermore, the performances of the Jaya and MTPG-Jaya algorithms have investigated in optimizing wind farm layout. The proposed algorithm tested using three cases of wind farm layout optimization (WFLO) problem: fixed wind speed and direction (case-I); fixed wind speed with changing wind direction (case-II); both wind speed and direction are variable (case-III). The computational results revealed that in all the three cases the MTPG-Jaya algorithm performs better than or is competitive to Jaya and other compared algorithms.

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