Abstract
An analysis model based on Data Mining is constructed for the power system voltage stability. Improvements of the traditional model of Data Mining are proposed. Data warehouse is established. Data preprocessing and data compression module are derived. The corresponding algorithms are also studied. Support vector machine is provided and discussed emphatically. There are a lot of advantages in this model such as contrary verification and self-perfect. An example is shown in order to testify the feasibility of this model.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Naiyan, D., Yingjie, T.: A new method in data mining-support vector machine. Science Publishing Company, Beijing (2004)
Fengjing, S., Zhongqing, Y.: Data mining-principle and algorithm, Beijing. China Water Resources and Hydropower Publishing Company (2003)
Zhiwei, L., Yaming, S.: Data mining technique and the application in power system. Automation of Electric Power Systems 25(11), 62–66 (2001)
Guang, L., Boming, Z., Hongbing, S.: Application of data warehouse and data mining techniques to power system. Power System Technology 25(8), 54–57 (2001)
Yanfang, L., Xueping, G.: Transient stability assessment of power systems based on support vector machines. Journal of North China Electric Power University 31(3), 26–29 (2004)
Theodoridis, S., Koutroumbas, K., Jingjiao, L., Zhiliang, Z., Wang Aixia translation: Pattern recognition, 2nd edn. Electronics Industry Publishing Company, Bingjing (2004)
Youping, F., Yunping, c., Wansheng, S., Xiaoxiao, M., Yi, C., Xiyue, H.: Algotithm for bi-directional reduce feature data based on the principal component analysis and immune clustering. Journal of System Simulation 17(1), 148–153 (2005)
Moulin, L.S., Alves da Silva, A.P., El-Sharkawi, M.A., Marks II, R.J.: Support vector machines for transient stability analysis of large-Scale power systems. IEEE Transactions on Power Systems 19(2), 818–825 (2004)
Tao, X.: Intelligent mining for power system security and stability. The PH.D of North China Electric Power University (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zhang, Xy., Wu, Y. (2009). Power System Voltage Stability Analysis Based on Data Mining. In: Cao, B., Li, TF., Zhang, CY. (eds) Fuzzy Information and Engineering Volume 2. Advances in Intelligent and Soft Computing, vol 62. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03664-4_179
Download citation
DOI: https://doi.org/10.1007/978-3-642-03664-4_179
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-03663-7
Online ISBN: 978-3-642-03664-4
eBook Packages: EngineeringEngineering (R0)