Modelling of wind energy resources and wind farm power outputs using Nested Markov Chain approach

Abstract

Accurate representation of wind energy resources is essential for the correct assessment of outputs of wind-based electricity generation systems. This paper uses "Nested Markov Chains" (NMC) approach, instead of the standard Markov Chain methodologks, for a more accurate representation of statistical and temporal characteristics of the modelled wind energy resources, as well as for the estimation of the power/energy outputs of a wind farm. The presented NMC approach uses equivalent power curve of the whole modelled wind farm for the selection of NMC states, which is an approach directly related to the actual conversion process of wind energy into the electricity at the considered wind farm site. The presented NMC model is validated using recorded wind speed data sets, as well as recorded power outputs from an actual wind farm.