Data Mining Applications to Power System Voltage Security Assessment

Voltage security assessment is an integral part of the modern Energy Management System. The traditional methods of contingency selection based on approximate or full AC load flow are either inaccurate or time consuming. To overcome these difficulties, development of fast, accurate and transparent voltage security assessment tools is required, so that in real-time, potentially dangerous operating conditions can be identified quickly and necessary corrective actions can be initiated within the given time frame of interest. Machine learning is a broad area of artificial intelligence, which is concerned with design and development of algorithms and techniques that allow computers to learn. Data mining is one of the branches of machine learning which uses past data for prediction of future results. In this book, data mining tools like fuzzy decision trees and case-based reasoning (CBR) is discussed in detail for application to voltage security assessment in power systems.

Hersteller:	LAP Lambert Academic Publishing
Anschrift:	Brivibas gatve 197 LV-1039 Riga
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Dr. Sonali Paunikar is working as Assistant Professor in Electrical Engg. Deptt, MA National Institute of Technology, Bhopal, India. She received Ph.D. in Power System from Nagpur University in 2019.Dr. N.P. Patidar is working as Professor & Head in Electrical Engg. Deptt, MANIT, Bhopal, received Ph.D. in Power System from IIT Roorkee in 2008.