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An Event-Oriented Method for Online Load Modeling Based on Synchrophasor Data
Yinyin Ge,Flueck, Alexander J.,Dae-Kyeong Kim,Jong-Bo Ahn,Jae-Duck Lee,Dae-Yun Kwon IEEE 2015 IEEE transactions on smart grid Vol.6 No.4
<P>The objective of this paper is to present a new “event-oriented” method of online load modeling for the Illinois Institute of Technology (IIT) microgrid based on synchrophasor data produced by phasor measurement units. Several load models and their parameter estimation methods are proposed. The online load modeling process is based on an adjustable sliding window applied to two different types of load step changes. The load modeling tests and related analysis of the synchrophasor data from the IIT microgrid are demonstrated.</P>
Yinyin Ge,Flueck, Alexander J.,Dae-Kyeong Kim,Jong-Bo Ahn,Jae-Duck Lee,Dae-Yun Kwon IEEE 2015 IEEE transactions on smart grid Vol.6 No.4
<P>The aim of this paper is to present methods on real-time event detection and data archival reduction based on synchrophasor data produced by phasor measurement unit (PMU). Event detection is performed with principal component analysis and a second order difference method with a hierarchical framework for the event notification strategy on a small-scale microgrid. Compared with the existing methods, the proposed method is more practical and efficient in the combined use of event detection and data archival reduction. The proposed method on data reduction, which is an “event oriented auto-adjustable sliding window method,” implements a curve fitting algorithm with a weighted exponential function-based variable sliding window accommodating different event types. It works efficiently with minimal loss in data information especially around detected events. The performance of the proposed method is shown on actual PMU data from the Illinois Institute of Technology campus microgrid, thus successfully improving the situational awareness of the campus power system network.</P>