Abstract: Abstract: To improve the performance of Yin-Yang-pair Optimization- Simulated annealing1 ( YYPO-SA1 ), an enhanced algorithm Newton- Yin-Yang-pair Optimization ( N-YYPO ) was proposed. In order to dynamically tune the probability of D-way splitting ,Newton decay mechanism was adopted and chaos perturbation mechanism was applied in splitting stage. The dynamic adjustment mechanism was applied to enable N-YYPO to use a large D-direction segmentation probability in the early stage of search, and use a smaller D-direction segmentation probability in the late stage of search, which enhanced the global search ability of the algorithm. Meanwhile, the diversity of solution was enriched ,and the ability of the algorithm to jump out of local optimal was enhanced by chaotic perturbation strategy. At last, N-YYPO was applied to the parametric optimization design problem of wind-driven generator.15 functions was selected, including unimodal, multimodal, and composited functions, as benchmark to evaluate performance of N-YYPO ,with YYPO-SA1, and 6 state-of the art single-objective: Particle Swarm Optimization ( PSO ), Flower Pollination Algorithm ( FPA ), Gray Wolf Optimizer ( GWO ), Whale Optimization Algorithm ( WOA ), Crow Search Algorithm ( CSA ), and Sparrow Search Algorithm ( SPA ), compared with YYPO-SA1 algorithm, N-YYPO obtains 12 orders of magnitude improvement in f1 function. In Friedman test, NYYPO ranks 2.87, 2.0 and 1.93 respectively, ranking first in all of them. Experimental result show that N-YYPO can achieve significant performance advantage in statistical sense. N-YYPO also achieves better optimization results in the parameter optimization problem of wind-driven generator.