Next Article in Journal
Exploring the Electro-Thermal Parameters of Reliable Power Modules: Insulated Gate Bipolar Transistor Junction and Case Temperature
Previous Article in Journal
Total Cost of Ownership Based Economic Analysis of Diesel, CNG and Electric Bus Concepts for the Public Transport in Istanbul City
Previous Article in Special Issue
Scrutinising the Gap between the Expected and Actual Deployment of Carbon Capture and Storage—A Bibliometric Analysis
Article Menu
Issue 9 (September) cover image

Export Article

Open AccessArticle
Energies 2018, 11(9), 2370; https://doi.org/10.3390/en11092370

Correlation Analysis between Wind Speed/Voltage Clusters and Oscillation Modes of Doubly-Fed Induction Generators

1
School of Electronic Information and Electrical Engineering, Shanghai JiaoTong University, Shanghai 200240, China
2
Department of Electronic and Electrical Engineering, University of Bath, Bath BA2 7AY, UK
*
Author to whom correspondence should be addressed.
Received: 13 August 2018 / Revised: 28 August 2018 / Accepted: 5 September 2018 / Published: 8 September 2018
(This article belongs to the Special Issue Sustainable Energy Systems)
Full-Text   |   PDF [2948 KB, uploaded 8 September 2018]   |  

Abstract

Potential machine-grid interactions caused by large-scale wind farms have drawn much attention in recent years. Previous work has been done by analyzing the small–signal modeling of doubly-fed induction generators (DFIGs) to obtain the oscillation modes. This paper, by making use of the metered power data of wind generating sets, studies the correlation between oscillation modes of the DFIG system and influence factors which includes wind speed and grid voltage. After the metered data is segmented, the Prony algorithm is used to analyze the oscillation modes contained in the active power. Then, the relevant oscillation modes are extracted in accordance with the small-signal analysis results. Meanwhile, data segments are clustered according to wind speed and grid voltage. The Apriori algorithm is finally used to discuss the association rules. By training the mass of data of wind generating sets, the inevitable association rules between oscillation modes and influence factors can be mined. Therefore, the prediction of oscillation modes can be achieved based on the rules. The results show that the clustering number quite affects the association rules. When the optimal cluster number is adopted, part of the wind speed/voltage clusters can analyze the certain oscillation modes. The predicted results are quite consistent with the practical data. View Full-Text
Keywords: wind power; oscillation mode; correlation analysis; Apriori algorithm wind power; oscillation mode; correlation analysis; Apriori algorithm
Figures

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Miao, J.; Xie, D.; Gu, C.; Wang, X. Correlation Analysis between Wind Speed/Voltage Clusters and Oscillation Modes of Doubly-Fed Induction Generators. Energies 2018, 11, 2370.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Energies EISSN 1996-1073 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top