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A Data Analytics Framework for Smart Grids: Spatio-temporal Wind Power Analysis and Synchrophasor Data Mining

Abstract Under the framework of intelligent management of power grids by leveraging advanced information, communication and control technologies, a primary objective of this study is to develop novel data mining and data processing schemes for several critical applications that can enhance the reliability of power systems. Specifically, this study is broadly organized into the following two parts: I) spatio-temporal wind power analysis for wind generation forecast and integration, and II) data mining and information fusion of synchrophasor measurements toward secure power grids. Part I is centered around wind power generation forecast and integration. First, a spatio-temporal analysis approach for short-term wind farm generation forecasting is propo... (more)
Created Date 2013
Contributor He, Miao (Author) / Zhang, Junshan (Advisor) / Vittal, Vijay (Advisor) / Hedman, Kory (Committee member) / Si, Jennie (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Subject Electrical engineering / data analytics / power systems / renewable generation / smart grids
Type Doctoral Dissertation
Extent 189 pages
Language English
Reuse Permissions All Rights Reserved
Note Ph.D. Electrical Engineering 2013
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis