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This paper proposes a new measure of wind power variability and investigates the impacts of wind power variability on the optimal sizing of Standalone Wind Power (SWP) systems. The proposed new measure of the wind power variability in the frequency domain, which mainly includes a cumulative energy distribution index and a fluctuation factor, is applied to assess the variability of wind power throughout 6 consecutive years from 6 far apart sites from latitude 0°–50° across America. Big data assessment results indicate the intermittent wind power at one site can be treated as Quasi-Time-Invariant (QTI) in the frequency domain. Big data simulations of the six SWP systems with the same residential load demand at the six sites provide QTI responses of the power supply reliability against the sizing of the system components in the mitigation of wind power variability. A case study of optimal sizing of a SWP system at Chicago, was carried out, which aims to minimize the system cost while satisfying the requirement of power supply reliability. It can be found from the study that, the proposed approach provides a new way to significantly reduce the computation in the optimal sizing of SWP systems. • A new measure of wind power variability is proposed in the frequency domain. • The wind power variability is quasi-time-invariant (QTI) in the frequency domain. • QTI analysis results can be used for simplifying the optimal sizing of SWP systems. [ABSTRACT FROM AUTHOR]