An application of probabilistic collocation method in wind farms modelling and power system simulation

摘要

In this paper Probabilistic Collocation Method (PCM) is introduced to solve a stochastic model representing wind farms in South Australia (SA). The model is based upon historical acquisition of wind source data, and considering the spatial correlation of wind speeds at neighboring wind farms. This correlation is used to reduce the number of uncertain parameters of the model, and then reducing the cost of PCM computation. In addition, fuzzy logic optimization is applied to PCM to improve the accuracy of the model output. The paper concludes with presentation of an aggregated DC load flow model of SA that is used as an example to compare the computation efficiency of the PCM and traditional Monte Carlo (MC) simulation method.