| Issue |
MATEC Web Conf.
Volume 139, 2017
2017 3rd International Conference on Mechanical, Electronic and Information Technology Engineering (ICMITE 2017)
|
|
|---|---|---|
| Article Number | 00080 | |
| Number of page(s) | 6 | |
| DOI | https://doi.org/10.1051/matecconf/201713900080 | |
| Published online | 05 December 2017 | |
Assessment Method of Wind Farm Harmonic Emission Value Based on Improved Complex Linear Regression Model
1 State Grid Shanghai Municipal Electric Power Company, Shanghai, 200437, China
2 School of Electrical and Information, Sichuan University, Chengdu, 610065, China
* Corresponding author: author@e-mail.org
Wind turbine filter and reactive power compensation devices lead to the harmonic impedance of wind farm is not much larger than that of the utility, so the influence by the wind farm harmonic impedance can not be neglected while assessing the harmonic emission value of wind farm A method based on improved complex linear regression is proposed in this paper for assessing the harmonic emission value of wind farm. The linear regression model is established by using the harmonic current at PCC point as the explanatory variable and the harmonic voltage of the wind farm as the explanatory variable. The utility harmonic impedance is calculated by complex least squares method. For various of the topology of wind farm feeder network, an equivalent method of feeder network is proposed to calculate the wind farm harmonic impedance. Errors are analyzed by using the error marginal effect of the dispersion parameter. Simulation and measured data verify the effectiveness of the proposed method
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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.