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- W3128352168 abstract "Voltage dependency of load greatly impacts power system studies (e.g. voltage stability). The constant power load model generally used for analysis is inadequate and conservative to accurately represent voltage dependency of load. Estimation of these parameters in an online manner can enhance the accuracy of power system analysis. Phasor Measurement Units (PMUs) provide high resolution power grid data for improved real-time wide-area system monitoring and control. These high-resolution PMU data have made real-time estimation of ZIP parameters possible, but PMU data may hold multiple types of anomalies arising in the physical system or the cyber system (measurements and communication networks). Increasing the grid situational awareness for noisy and bad/anomalous measurement data has become significant for data-driven PMU applications. Many algorithms developed for anomaly detection have been only validated with simulated data and not with realistic synchophasor data. Approach to actual field data is really challenging due to confidentiality and security grounds. This paper presents a method for generating realistic synchrophasor data for the given synthetic network as well as online adaptive ZIP parameter estimation algorithm. The developed algorithm, firstly uses en-semble based anomaly detector (E-BAD) to flag all bad data present in PMU data streams and then an adaptive algorithm for estimation window formation and, a novel estimation method Least square assisted with sensitivity based variable elimination (LSVE-ZIP) are used for ZIP parameter estimation. Moreover, a confidence factor computation framework is proposed to give insight regarding accuracy of estimated parameters. Parameter estimation performance is validated using numerous PSS/E and RTDS generated scenarios with noise and bad data. These set of synchrophasor data will be made available publicly later for other researchers." @default.
- W3128352168 created "2021-02-15" @default.
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- W3128352168 date "2020-10-10" @default.
- W3128352168 modified "2023-09-24" @default.
- W3128352168 title "Real-time ZIP Load Parameter Tracking using Adaptive Window and Variable Elimination with Realistic Synthetic Synchrophasor Data" @default.
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- W3128352168 doi "https://doi.org/10.1109/ias44978.2020.9334878" @default.
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