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In this work, a searching space minimization-based particle swarm optimization (SSM-PSO) scheme has been proposed for maximum power point tracking (MPPT) in a doubly fed induction generator (DFIG) based wind energy conversion system (WECS). DFIG displays non-linearity in <inline-formula> <tex-math notation="LaTeX">$P-\omega $ </tex-math></inline-formula>characteristics. So different types of conventional and optimization-based schemes are developed for MPPT. The drawbacks in the conventional perturb and observe (P&#x0026;O) scheme has been successfully abolished by the proposed SSM-PSO method. Because of its weather-insensitive nature, the conventional P&#x0026;O MPP tracking scheme results in the fluctuation of DFIG output under a sudden change in wind speed. To avoid this problem, maximum and minimum limits for the optimal rotor speed have been determined in the proposed SSM-PSO scheme. Further, the obtained limits for rotor speed are employed to improve the searching space within the non-linear <inline-formula> <tex-math notation="LaTeX">$P-\omega $ </tex-math></inline-formula> curve. This initial confinement of particles to a limited searching space in SSM-PSO results in a faster response of the system. Since the proposed SSM-PSO is atmosphere sensitive, it avoids fluctuations under an abrupt variation in wind velocity. The improved initialization part of SSM-PSO leads to better dynamic characteristics compared to existing P&#x0026;O and optimization-based schemes. The proposed SSM-PSO scheme is implemented for a 2MW DFIG system in MATLAB Simulink atmosphere and showed satisfactory results.