@inproceedings{cf483488766a4d719234a13f2f27a140,
title = "An application of probabilistic collocation method in wind farms modelling and power system simulation",
abstract = "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.",
keywords = "fuzzy logic, power system simulation, Probabilistic Collocation Method, uncertainty, Wind power generation",
author = "Hang Yin and Rastko Zivanovic",
year = "2016",
month = dec,
day = "22",
doi = "10.1109/ISGT-Asia.2016.7796467",
language = "English",
series = "IEEE PES Innovative Smart Grid Technologies Conference Europe",
publisher = "IEEE Computer Society",
pages = "681--686",
booktitle = "2016 IEEE Innovative Smart Grid Technologies - Asia, ISGT-Asia 2016",
address = "United States",
note = "2016 IEEE Innovative Smart Grid Technologies - Asia, ISGT-Asia 2016 ; Conference date: 28-11-2016 Through 01-12-2016",
}