Abstract
As a critical component for evaluation of output power variability at wind farms, short duration power ramp distributions are typically evaluated as ensemble estimates across elaborate time-aggregated compilation of on-site field measurements. This paper proposes an algorithmic alternative to the above, by introducing statistical estimates both for probability density function (pdf) and cumulative distribution function (cdf) of power ramps. The estimates are pessimistic as possible real time filtering, attributable to turbine inertia and time-constants, is assumed to be negligible. The proposed algorithm is conveniently implemented on popular spreadsheet software, has limited dependence on source wind statistics, and easily accommodates turbulence conditions given by the IEC 61400-1 standards. Its application is illustrated for the popular Vestas V-90 3 MW turbine, assumed to operate at a site with source wind accordingly specified.
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