Chaos-opposition-enhanced slime mould algorithm for minimizing the cost of energy for the wind turbines on high-altitude sites.

This paper presents a chaos-opposition-enhanced slime mould algorithm (CO-SMA) to minimize energy (COE) cost for the wind turbines on high-altitude sites. The COE model is established based on rotor radius, rated power, and hub height needed to achieve an optimal design model. In this context, an improved variant of SMA, named CO-SMA, is proposed based on a chaotic search strategy (CSS) and crossover-opposition strategy (COS) to cope with the potential weaknesses classical SMA while dealing with nonlinear tasks. First, the COS is introduced to enhance the diversity of solutions and thus improves the exploratory tendencies. The CSS is incorporated into the basic SMA to improve the exploitative abilities and thus avoids the premature convergence dilemma. The proposed CO-SMA is validated on the design of wind turbines with high-altitude sites. Furthermore, the sensitivity analysis based on the Taguchi method is developed to exhibit the impact of the COE model's optimized parameters. The influence of uncertainty based on the fuzziness scheme of wind resource statistics is also explored to depict a real scheme for the changes that occurred by seasonal time, atmospheric conditions, and topographic conditions. The proposed CO-SMA is compared with the PSO, WOA, GWO, MDWA, and SMA, where the COE values are recorded as 0.052408, 0.052462, 0.052435, 0.052409, 0.052413, and 0.052915, respectively. Furthermore, the proposed CO-SMA records the faster convergence than the others. On the other hand, the Taguchi method reveals that the rated power is the most significant parameter on the COE model. Also, the impact of the fuzziness scheme on COE is exhibited, where the increasing interval of vagueness can increase the value of COE.