Issue |
MATEC Web Conf.
Volume 173, 2018
2018 International Conference on Smart Materials, Intelligent Manufacturing and Automation (SMIMA 2018)
|
|
---|---|---|
Article Number | 01028 | |
Number of page(s) | 6 | |
Section | Modeling, Analysis, and Simulation of Intelligent Manufacturing Processes | |
DOI | https://doi.org/10.1051/matecconf/201817301028 | |
Published online | 19 June 2018 |
The Method for Risk Assessment of SSR Caused by Doubly-Fed Wind Farms
School of Electrical and Information Engineering, Jiangsu University, Zhenjiang, China
Corresponding author : xiaoyu.eeps@gmail.com
The existing method for investigating the subsynchronous resonance (SSR) caused by wind powergeneration is mainly aimed at a deterministic condition. In order to analyse the impact of uncertain factors onSSR in wind farms, this paper defines the risk matrix and risk index, and develops a SSR-oriented riskassessment method of using probabilistic collocation method (PCM). Considering the uncertain of windspeeds, the proposed method is used to assess the SSR risk of a wind farm. The results show that under thesame wind speed distribution, the higher the series compensation level in the system is, the greater the SSRrisk of the system could be; under the same series compensation level, the SSR risks caused by different windspeed distribution are different, and the system in the areas with lower average wind speed obtains greater SSR risk.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.